Software Engineering Institute (SEI) Podcast Series

To make secure software by design a reality, engineers must intentionally build security throughout the software development lifecycle. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Timothy A. Chick, technical manager of the Applied Systems Group in the SEI’s CERT Division, discusses building, designing, and operating secure systems.

Harmful biases in large language models (LLMs) make AI less trustworthy and secure. Auditing for biases can help identify potential solutions and develop better guardrails to make AI safer. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Katie Robinson and Violet Turri, researchers in the SEI’s AI Division, discuss their recent work using role-playing game scenarios to identify biases in LLMs.

In the wake of widespread adoption of artificial intelligence (AI) in critical infrastructure, education, government, and national security entities, adversaries are working to disrupt these systems and attack AI-enabled assets. With nearly four decades in vulnerability management, the Carnegie Mellon University Software Engineering Institute (SEI) recognized a need to create an entity that would identify, research, and identify mitigation strategies for AI vulnerabilities to protect national assets against traditional cybersecurity, adversarial machine learning, and joint cyber-AI attacks. In this SEI podcast, Lauren McIlvenny, director of threat analysis in the SEI’s CERT Division, discusses best practices and lessons learned in standing up an AI Security Incident Response Team (AISIRT).  

The exposed and public nature of application programming interfaces (APIs) come with risks including the increased network attack surface. Zero trust principles are helpful for mitigating these risks and making APIs more secure. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), McKinley Sconiers-Hasan, a solutions engineer in the SEI CERT Division, discusses three API risks and how to address them through the lens of zero trust.  

Capability-Based Planning (CBP) defines a framework that has an all-encompassing view of existing abilities and future needs for strategically deciding what is needed and how to effectively achieve it. Both business and government acquisition domains use CBP for financial success or to design a well-balanced defense system. The definitions understandably vary across these domains. In this SEI podcast, Anandi Hira, a data scientist, and William R. Nichols, an initiative lead for Software Engineering Measurement and Analysis, introduce CBP and its use and application in software acquisition.

What can the recently discovered vulnerabilities related to Rust tell us about the security of the language? In this podcast from the Carnegie Mellon University Software Engineering Institute, David Svoboda discusses two vulnerabilities, their sources, and how to mitigate them.

Cybersecurity risks aren’t just a national concern. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), the CERT division’s Tracy Bills, senior cybersecurity operations researcher and team lead, and James Lord, security operations technical manager, discuss the SEI’s work developing Computer Security Incident Response Teams (CSIRTs) across the globe.

Developers know that static analysis helps make code more secure. However, static analysis tools often produce a large number of false positives, hindering their usefulness. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), David Svoboda, a software security engineer in the SEI’s CERT Division, discusses Redemption, a new open source tool from the SEI that automatically repairs common errors in C/C++ code generated from static analysis alerts, making code safer and static analysis less overwhelming.

Not all paths to cybersecurity careers look the same. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Randy Trzeciak, deputy director of cyber risk and resilience in the SEI’s CERT division, discusses his career journey, resources for pursuing a career in cybersecurity, and the importance of building a diverse workforce.

Sam Procter started out studying computer science at the University of Nebraska, but he didn’t love it. It wasn’t until he took his first software engineering course that he knew he’d found his career path. In this podcast from the Carnegie Mellon University Software Engineering Institute, Sam Procter discusses the early influences that shaped his career, the importance of embracing different types of diversity in his research and work, and the value of a work-life balance.

With the increasing complexity of software systems, the use of third-party components has become a widespread practice. Cyber disruptions, such as SolarWinds and Log4j, demonstrate the harm that can occur when organizations fail to manage third-party components in their software systems. In this podcast from the Carnegie Mellon University Software Engineering Institute, Carol Woody, principal researcher, and Michael Bandor, a senior software engineer, discuss a Software Bill of Materials (SBOMs) framework to help promote the use of SBOMs and establish a more comprehensive set of practices and processes that organizations can leverage as they build their programs. They also offer guidance for government agencies who are interested in incorporating SBOMs into their work. 

In this podcast from the Carnegie Mellon University Software Engineering Institute, Carol Ware, a senior cybersecurity engineer in the SEI’s CERT Division, discusses her career path, the value of mentorship, and the importance of diversity in cybersecurity.

In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Suzanne Miller, a principal researcher in the SEI’s Software Solutions Division, discusses her career path, the value of mentorship, and the importance of diversity in software engineering.

Across the globe, women account for less than 30 percent of professionals in technical fields. That number drops to 22 percent in the field of Artificial Intelligence (AI). In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Violet Turri, a software developer in the SEI’s AI Division, discusses the evolution of her career in AI and the importance of diversity in the field. 

At the request of the White House, the Office of the Director of National Intelligence (ODNI) began exploring use cases for large language models (LLMs) within the Intelligence Community (IC). As part of this effort, ODNI sponsored the Mayflower Project at Carnegie Mellon University’s Software Engineering Institute (SEI) from May 2023 through September 2023. The Mayflower Project attempted to answer the following questions:

How might the IC set up a baseline, stand-alone LLM? How might the IC customize LLMs for specific intelligence use cases? How might the IC evaluate the trustworthiness of LLMs across use cases?

In this SEI Podcast, Shannon Gallagher, AI engineering team lead, and Rachel Dzombak, special advisor to the director of the SEI’s AI Division, discuss the findings and recommendations from the Mayflower Project and provides additional background information about LLMs and how they can be engineered for national security use cases.

Modern software engineering practices of Agile and DevSecOps have provided a foundation for producing working software products faster and more reliably than ever before. Far too often, however, these practices do not address the non-software concerns of business mission and capability delivery even though these concerns are critical to the successful delivery of a software product. Through our work with government organizations, we have found that expanding DevSecOps beyond product development enables other teams to increase their capabilities and improve their processes. Agile methodologies are also being used for complex system and hardware developments. In this podcast from the Carnegie Mellon University Software Engineering Institute, Lyndsi Hughes, a senior systems engineer and David Sweeney, an associate software developer, both with the SEI CERT Division, share their experiences leveraging DevSecOps pipelines in atypical situations in support of teams focused on the capability delivery and business mission for their organizations.

Increasingly in government acquisition of software-intensive systems, we are seeing programs using Agile development methodology and earned value management. While there are many benefits to using both Agile and EVM, there are important considerations that software program managers must first address. In this podcast, Patrick Place, a senior engineer, and Stephen Wilson, a test engineer, both with the SEI Agile Transformation Team, discuss seven considerations for successful use of Agile and EVM.

As developers continue to build greater autonomy into cyber-physical systems (CPSs), such as unmanned aerial vehicles (UAVs) and automobiles, these systems aggregate data from an increasing number of sensors. However, more sensors not only create more data and more precise data, but they require a complex architecture to correctly transfer and process multiple data streams. This increase in complexity comes with additional challenges for functional verification and validation, a greater potential for faults, and a larger attack surface. What’s more, CPSs often cannot distinguish faults from attacks. To address these challenges, researchers from the SEI and Georgia Tech collaborated on an effort to map the problem space and develop proposals for solving the challenges of increasing sensor data in CPSs. In this podcast from the Carnegie Mellon University Software Engineering Institute, Jerome Hugues, a principal researcher in the SEI Software Solutions Division, discusses this collaboration and its larger body of work, Safety Analysis and Fault Detection Isolation and Recovery (SAFIR) Synthesis for Time-Sensitive Cyber-Physical Systems.

To better understand the potential uses of large language models (LLMs) and their impact, a team of researchers at the Carnegie Mellon University Software Engineering Institute CERT Division conducted four in-depth case studies. The case studies span multiple domains and call for vastly different capabilities. In this podcast, Matthew Walsh, a senior data scientist in CERT, and Dominic Ross, Multi-Media Design Team lead, discuss their work in developing the four case studies as well as limitations and future uses of ChatGPT.

Research and development of quantum computers continues to grow at a rapid pace. The U.S. government alone spent more than $800 million on quantum information science research in 2022. Thomas Scanlon, who leads the data science group in the SEI CERT Division, was recently invited to be a participant in the Workshop on Cybersecurity of Quantum Computing, co-sponsored by the National Science Foundation (NSF) and the White House Office of Science and Technology Policy, to examine the emerging field of cybersecurity for quantum computing. In this podcast from the Carnegie Mellon University Software Engineering Institute, Scanlon discusses how to create the discipline of cyber protection of quantum computing and outlines six areas of future research in quantum cybersecurity.

Far too often software programs continue to collect metrics for no other reason than that is how it has always been done. This leads to situations where, for any given environment, a metrics program is defined by a list of metrics that must be collected. A top-down, deterministic specification of graphs or other depictions of data required by the metrics program can distract participants from the potentially useful information that the metrics reveal and illuminate. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Will Hayes, who leads the Agile Transformation Team, and Patrick Place, a principal engineer on that team, discuss with principal researcher Suzanne Miller, how user stories can help put development in the context of who is using the system and lead to a conversation about why a specific metric is being collected. 

In working with software and systems teams developing technical products, Judy Hwang, a senior software engineer in the SEI CERT Division, observed that teams were not investing the time, resources and effort required to manage the product lifecycle of a successful product. These activities include thoroughly exploring the problem space by talking to users, assessing existing solutions, understanding the competition, and positioning the product to create value for customers. In this podcast from the Carnegie Mellon University Software Engineering Institute, Hwang talks with principal researcher Suzanne Miller about the importance of implementing foundational product management principles in software and systems development and offers resources for audience members who looking to strengthen their Agile product delivery practices.

The ability of artificial intelligence (AI) to partner with the software engineer, doctor, or warfighter depends on whether these end users trust the AI system to partner effectively with them and deliver the outcome promised. To build appropriate levels of trust, expectations must be managed for what AI can realistically deliver. In this podcast from the SEI’s AI Division, Carol Smith, a senior research scientist specializing in human-machine interaction, joins design researchers Katherine-Marie Robinson and Alex Steiner, to discuss how to measure the trustworthiness of an AI system as well as questions that organizations should ask before determining if it wants to employ a new AI technology.

In this podcast from the Carnegie Mellon University Software Engineering Institute, Bill Nichols and Julie Cohen talk with Suzanne Miller about how automation within DevSecOps product-development pipelines provides new opportunities for program managers (PMs) to confidently make decisions with the help of readily available data.

As in commercial companies, DoD PMs are accountable for the overall cost, schedule, and performance of a program. The PM’s job is even more complex in large programs with multiple software-development pipelines where cost, schedule, performance, and risk for the products of each pipeline must be considered when making decisions, as well as the interrelationships among products developed on different pipelines. Nichols and Cohen discuss how PMs can collect and transform unprocessed DevSecOps development data into useful program-management information that can guide decisions they must make during program execution. The ability to continuously monitor, analyze, and provide actionable data to the PM from tools in multiple interconnected pipelines of pipelines can help keep the overall program on track.

In the wake of the COVID pandemic, the workforce decentralized and shifted toward remote and hybrid environments. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Dan Costa, technical manager of enterprise threat and vulnerability management, and Randy Trzeciak, deputy director of Cyber Risk and Resilience, both with the SEI’s CERT Division, discuss how remote work in the post-pandemic world is changing expectations about employee behavior monitoring and insider risk detection.

Independent verification and validation (IV&V) is a significant step in the process of deploying systems for mission-critical applications in the Department of Defense (DoD). In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Justin Smith, senior Agile transformation leader in the SEI Software Solutions Division, talks with principal researcher Suzanne Miller about how to bring concepts from Lean and Agile software development into the practice of IV&V.

Smith describes his experiences at NASA’s Katherine Johnson IV&V Facility as a project manager for the Orion IV&V team. On that project, the developer employed Scaled Agile Framework (SAFe) as their development process, which had challenging consequences for established IV&V practices within NASA IV&V. Smith also discusses the ways in which NASA adapted to this change and describes strategies and tactics for reconciling Agile and IV&V.

Zero trust architecture has the potential to improve an enterprise’s security posture. There is still considerable uncertainty about the zero trust transformation process, however, as well as how zero trust architecture will ultimately appear in practice. Recent executive orders have accelerated the timeline for zero trust adoption in the federal sector, and many private-sector organizations are following suit. Researchers in the CERT Division at the Carnegie Mellon University Software Engineering Institute (SEI) hosted Zero Trust Industry Days to enable industry stakeholders to share information about implementing zero trust. In this SEI podcast, CERT researchers Matthew Nicolai and Nathaniel Richmond discuss five zero trust best practices identified during the two-day event, explain their significance, and provide commentary and analysis on ways to empower your organization’s zero trust transformation. 

In Ansible, roles allow system administrators to automate the loading of certain variables, tasks, files, templates, and handlers based on a known file structure. Grouping content by roles allows for easy sharing and reuse. When developing roles, users must deal with various concerns, including what operating system(s) and version(s) will be supported and whether a single node or a cluster of machines is needed. In this podcast from the Carnegie Mellon University Software Engineering Institute, Matthew Heckathorn, an integration engineer with the SEI’s CERT Division, offers guidance for systems engineers, system administrators, and others on developing Ansible roles and automating infrastructure as code.

While the memory safety and security features of the Rust programming language can be effective in many situations, Rust’s compiler is very particular on what constitutes good software design practices. Whenever design assumptions disagree with real-world data and assumptions, there is the possibility of security vulnerabilities–and malicious software that can take advantage of those vulnerabilities. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), David Svoboda and Garret Wassermann, researchers with the SEI's CERT Division, explore tools for understanding vulnerabilities in Rust whether the original source code is available or not. These tools are important for understanding malicious software where source code is often unavailable, as well as commenting on possible directions in which tools and automated code analysis can improve.

In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Gregory J. Touhill, director of the SEI CERT Division, talks with principal researcher Suzanne Miller about the 2020 attack on Solar Winds software and how to prevent a recurrence of another major attack on key systems that are in widespread use. Solar Winds is the name of a company that provided software to the U.S. federal government. In late 2020, news surfaced about a cyberattack that had already been underway for several months and that had reportedly compromised 250 government agencies, including the Treasury Department, the State Department, and nuclear research labs. In addition to compromising data, the attack resulted in financial losses of more than $90 million and was probably one of the most dangerous modern attacks on software and software-based businesses and government agencies in the recent past. The SolarWinds incident demonstrated the challenges of securing systems when they are the product of complex supply chains.

In this podcast, Touhill discusses topics including the need for systems to be secure by design and secure by default, the importance of transparency in the reporting of vulnerabilities and anomalous system behavior, the CERT Acquisition Security Framework, the need to secure data across a wide range of disparate devices and systems, and tactics and strategies for individuals and organizations to safeguard their data and the systems they rely on daily.

In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI)  Marisa Midler and Samantha Chaves, penetration testers with the SEI’s CERT Division, talk with Suzanne Miller about a penetration-testing repository that they helped to build. The repository is a source of information for active directory, phishing, mobile technology, systems and services, web applications, and mobile- and wireless-technology weaknesses that could be discovered during a penetration test. The repository is intended to help assessors provide reports to organizations using standardized language and standardized names for findings, and to save assessors time on report generation by having descriptions, standard remediations, and other resources available in the repository for their use. The repository is available at https://github.com/cisagov/pen-testing-findings

Societal-scale software systems, such as today’s commercial social media platforms, are among the most widely used software systems in the world, with some platforms reporting billions of daily active users. These systems have created new mechanisms for global communication and connect people with unprecedented speed. Despite the numerous benefits of societal-scale systems, these systems are designed to optimize user engagement and scale by using psychology (such as gaming and reward mechanisms) to influence users. Individual users struggle with privacy of their data and bias in these systems, while governments face new threats of misinformation. In this podcast from the Carnegie Mellon University Software Engineering Institute, John Robert and Forrest Shull discuss issues that must be considered when engineering societal-scale systems.

In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI) Gregory J. Touhill, director of the SEI CERT Division, talks with Suzanne Miller about secure by design, secure by default, a longstanding tenet of the work of the SEI and CERT in particular. The SEI has been in the forefront of secure software development, promoting an approach where security weaknesses are addressed, prevented, or eliminated earlier in the software development lifecycle, which not only helps to ensure secure systems, but also saves time and money. Touhill also discusses the CERT strategy in support of SEI sponsors in the U.S. Department of Defense (DoD), the Department of Homeland Security (DHS), and the Cybersecurity Infrastructure Security Agency (CISA) and his vision for the future of cybersecurity and the role of the CERT Division.

Secure by design means performing more security and assurance activities earlier in the product and system lifecycles. A secure-by-design mindset addresses the security of systems during the requirements, design, and development phases of lifecycles rather than waiting until the system is ready for implementation. The need for a secure-by-design mindset is exacerbated by the amount of interconnectedness of today’s systems and the increasing amount of automation that characterizes system development. These trends have led to increased levels of risk and made implementation of security controls during test and patching systems after deployment increasingly unsustainable. In this podcast from the Carnegie Mellon University Software Engineering Institute, Robert Schiela, technical manager of the Secure Coding group, and Carol Woody, a principal researcher in the SEI’s CERT Division, talk with Suzanne Miller about the importance of integrating the practices and mindset of secure by design into the acquisition and development of software-reliant systems. 

Like all technical debt, enterprise technical debt consists of choices expedient in the short term, but often problematic over the long term. In enterprise technical debt, the impact reaches beyond the scope of a single system or project. Because ignoring enterprise technical debt can have significant consequences, software and systems architects should be alert for it, and they should not let it get overlooked or ignored when they come across it. Enterprise technical debt often results in multi-project or organization-wide risks that increase the organization’s cost, efficiency, or security risks. Remediation of enterprise technical debt requires intervention by governance structures whose scope is broader than that of individual teams or projects. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Stephany Bellomo, a principal engineer in the SEI’s Software Solutions Division, talks with principal researcher Suzanne Miller about identifying and remediating enterprise technical debt.

The recent growth of applications that leverage large language models, including ChatGPT and Copilot, has spurred reactions ranging from fear and uncertainty to adoration and lofty expectations. In this podcast from the Carnegie Mellon University Software Engineering Institute, Jay Palat, senior engineer and technical director of AI for mission, and Dr. Rachel Dzombak, senior advisor to the director of the SEI’s AI Division, discuss the current landscape of large language models (LLMs), common misconceptions about LLMs, how to leverage tools built on top of LLMs, and the need for critical thinking around both the outputs of the tools and the trends in their use. 

DevSecOps practices, including continuous-integration/continuous-delivery (CI/CD) pipelines, enable organizations to respond to security and reliability events quickly and efficiently and to produce resilient and secure software on a predictable schedule and budget. Despite growing evidence and recognition of the efficacy and value of these practices, the initial implementation and ongoing improvement of the methodology can be challenging. In this podcast from the Carnegie Mellon University Software Engineering Institute, senior engineers Vanessa Jackson and Lyndsi Hughes discuss with principal researcher Suzanne Miller the DevSecOps adoption framework, which guides organizations in the planning and implementation of a roadmap to functional CI/CD pipeline capabilities. 

Rust is growing in popularity. Its unique security model promises memory safety and concurrency safety, while providing the performance of C/C++. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), David Svoboda and Joe Sible, both engineers in the SEI’s CERT Division, talk with principal researcher Suzanne Miller about the Rust programming language and its security-related features. Svoboda and Sible discuss Rust’s compile-time safety guarantees, the kinds of vulnerabilities that Rust fixes and those that it does not, situations in which users would not want to use Rust, and where interested users can go to get more information about the Rust programming language. 

Coordinated vulnerability disclosure (CVD) begins when at least one individual becomes aware of a vulnerability, but it can’t proceed without the cooperation of many. Software supply chains, software libraries, and component vulnerabilities have evolved in complexity and have become as much a part of the CVD process as vulnerabilities in vendors’ proprietary code. Many CVD cases now require coordination across multiple vendors. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Allen Householder, a senior vulnerability and incident researcher in the SEI’s CERT Division, talks with principal researcher Suzanne Miller about Vultron, a protocol for multi-party coordinated vulnerability disclosure (MPCVD).

In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Dr. Carol Woody, a principal researcher in the SEI's CERT Division, talks with Suzanne Miller about the SEI’s newly released Acquisition Security Framework, which helps programs coordinate the management of engineering and supply-chain risks across system components including hardware, network interfaces, software interfaces, and mission capabilities.

In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Scott Hissam, a researcher within the SEI’s Software Solutions Division who works on software assurance in Department of Defense (DoD) systems, talks with Linda Parker Gates, initiative lead for the SEI’s Software Acquisition Pathways, about the use of free and open-source software (FOSS) in the DoD, building on insights that surfaced in a recent workshop held for producers and consumers of FOSS for DoD systems.

In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Dr. Sam Procter and Lutz Wrage, researchers with the SEI, discuss the Guided Architecture Trade Space Explorer (GATSE), a new SEI-developed model-based tool to help with the design of safety-critical systems. The GATSE tool allows engineers to evaluate more design options in less time than they can now. This prototype language extension and software tool partially automates the process of model-based systems engineering so that systems engineers can rapidly explore combinations of different design options.

In aiming for correctness and security of product, as well as for development speed, software development teams often face tension in their objectives. During a recent customer engagement that involved the development of a continuous-integration (CI) pipeline, developers wanted to develop features and deploy to production, deferring non-critical bugs as technical debt, whereas cyber engineers wanted compliant software by having the pipeline fail on any security requirement that was not met. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Alejandro Gomez, a researcher in the SEI’s CERT Division who worked on the customer project, talked with principal researcher Suzanne Miller about how the team explored—and eventually resolved—the two competing forces of developer velocity and cybersecurity enforcement by implementing DevSecOps practices.

The shift to a cloud environment provides significant benefits. Cloud resources can be scaled quickly, updated frequently, and widely accessed without geographic limitations. Realizing these benefits, however, requires organizations to manage associated organizational and technical risks. In this podcast from the Carnegie Mellon University Software Engineering Institute, Chris Alberts, principal cybersecurity analyst in the SEI’s CERT Division, discusses with principal researcher Suzanne Miller a prototype set of cloud adoption risk factors and describes a method that managers can employ to assess their cloud initiatives against these risk factors.

Competitive pressures in many domains, as well as development paradigms such as Agile and DevSecOps, have led to the increasingly common practice of continuous delivery or continuous deployment where frequent updates to software systems are rapidly and reliably fielded. In today’s systems, releases can occur at any time—possibly hundreds of releases per day—and each can be instigated by a different team within an organization. Being able to release frequently means that bug fixes and security patches do not have to wait until the next scheduled release, but rather can be made and released as soon as a bug is discovered and fixed. It also means that new features can be put into production at any time and don’t have to wait to be bundled into a release. In this podcast, Rick Kazman, an SEI visiting scientist and coauthor of Software Architecture in Practice, talks with principal researcher Suzanne Miller about using patterns for software deployability. These patterns fall into two broad categories: complete replacement of services and canary testing.

In this podcast from the Carnegie Mellon University Software Engineering Institute, Thomas Podnar and Dustin Updyke, both senior cybersecurity engineers with the SEI’s CERT Division, discuss their work to apply machine learning to increase the realism of non-player characters (NPCs) in cyber training exercises.

In this podcast from the Carnegie Mellon University Software Engineering Institute, Douglass Post and Richard Kendall, authors of "Creating and Using Virtual Prototyping Software: Principles and Practices" discuss with principal researcher Suzanne Miller experiences and insights that they gleaned from applying virtual prototyping in CREATE (Computational Research and Engineering Acquisition Tools and Environments), a multiyear DoD program to develop and deploy software for systems like ships, air vehicles, ground vehicles, and radio-frequency antennas. CREATE enabled engineers and scientists to design these complex systems and to accurately predict their performance.

In this podcast from the Carnegie Mellon University Software Engineering Institute, visiting scientist Rick Kazman and principal researcher Suzanne Miller discuss software architecture patterns and the effect that certain architectural patterns have on quality attributes, such as availability and robustness. Kazman also provides examples of mechanisms—such as architectural tactics and patterns—and the effects they have on availability and robustness, especially in cloud-based systems.

DevSecOps encompasses all the best software engineering principles known today with an emphasis on faster delivery through increased collaboration of all stakeholders resulting in more secure, useable, and higher-quality software systems. In this podcast from the Carnegie Mellon University Software Engineering Institute, researchers Tim Chick and Joe Yankel present a DevSecOps Platform-Independent Model (PIM), which uses model based systems engineering (MBSE) to formalize the practices of DevSecOps pipelines and organize relevant guidance. This first-of-its-kind model gives software development enterprises the structure and articulation needed for creating, maintaining, securing, and improving DevSecOps pipelines.

In this podcast from the Carnegie Mellon University Software Engineering Institute, Jason Larkin and Daniel Justice, researchers in the SEI’s AI Division, discuss a paper outlining their efforts to simulate the performance of Quantum Approximate Optimization Algorithm (QAOA) for the Max-Cut problem and compare it with some of the best classical alternatives, for exact, approximate, and heuristic solutions.

To ensure trust, artificial intelligence systems need to be built with fairness, accountability, and transparency at each step of the development cycle. In this podcast from the Carnegie Mellon University Software Engineering Institute, Carol Smith, a senior research scientist in human machine interaction, and Dustin Updyke, a senior cybersecurity engineering in the SEI’s CERT Division, discuss the construction of trustworthy AI systems and factors influencing human trust of AI systems. 

In this podcast from the Carnegie Mellon University Software Engineering Institute, Shannon Gallagher, a data scientist with SEI’s CERT Division, and Dominic Ross, multimedia team lead for the SEI, discuss deepfakes, their exponential growth in recent years, their increasing technical sophistication, and the problems they pose for individuals and organizations. Gallagher and Ross also discuss the SEI’s recent research in assessing the technology underlying the creation and detection of deepfakes and understanding current and future threat levels. 

Digital engineering uses digital tools and representations in the process of developing, sustaining, and maintaining systems, including requirements, design, analysis, implementation, and test. The digital modeling approach is intended to establish an authoritative source of truth for the system, in which discipline-specific views of the system are created using the same model elements. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), William “Bill” Nichols, a senior member of the technical staff with the SEI’s Software Solutions Division, discusses with principal researcher Suzanne Miller the challenges in making the transition from traditional development practices to digital engineering.

Over the past several years, zero trust architecture has emerged as an important topic within the field of cybersecurity. Heightened federal requirements and pandemic-related challenges have accelerated the timeline for zero trust adoption within the federal sector. Private sector organizations are also looking to adopt zero trust to bring their technical infrastructure and processes in line with cybersecurity best practices. Real-world preparation for zero trust, however, has not caught up with existing cybersecurity frameworks and literature. NIST standards have defined the desired outcomes for zero trust transformation, but the implementation process is still relatively undefined. As the nation’s first federally funded research and development center with a clear emphasis on cybersecurity, the Carnegie Mellon University Software Engineering Institute (SEI) is uniquely positioned to bridge the gap between NIST standards and real-world implementation. In this podcast, Tim Morrow and Matthew Nicolai, researchers with the SEI’s CERT Division, have outlined 4 steps that organizations can take to implement and maintain zero trust architecture.

In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Hasan Yasar, technical director, Continuous Deployment of Capability at the SEI, and Jay Palat, interim director of AI for Mission in the SEI’s AI Division, discuss how to engineer AI systems with DevSecOps and explore the relationship between MLOps and DevSecOps.

In this podcast from the Carnegie Mellon University Software Engineering Institute, Jonathan Spring, a senior vulnerability researcher, discusses with Suzanne Miller the findings in a paper he published recently analyzing the number of undiscovered vulnerabilities in information systems. This paper examines the paradigm that the number of undiscovered vulnerabilities is manageably small through the lens of mathematical concepts from the theory of computing. 

As the field of artificial intelligence (AI) has matured, increasingly complex opaque models have been developed and deployed to solve hard problems. Unlike many predecessor models, these models, by the nature of their architecture, are harder to understand and oversee. When such models fail or do not behave as expected or hoped, it can be hard for developers and end-users to pinpoint why or determine methods for addressing the problem. Explainable AI (XAI) meets the emerging demands of AI engineering by providing insight into the inner workings of these opaque models. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Violet Turri and Rachel Dzombak, both with the SEI's AI Division, discuss explainable AI, which encompasses all the techniques that make the decision-making processes of AI systems understandable to humans. 

In this podcast from the Carnegie Mellon University Software Engineering Institute, senior researchers Jerome Hugues and Joe Yankel discuss ModDevOps, an extension of DevSecOps that embraces model-based systems engineering (MBSE) practices and technology. Hugues and Yankel also discuss how making this integration between DevSecOps and MBSE explicit unlocks both the speed of DevSecOps and the risk reduction of MBSE.

Organizations are turning to DevSecOps to produce code faster and at lower cost, but the reality is that much of the code is actually coming from the software supply chain through code libraries, open source, and third-party components where reuse is rampant. The downside is that this reused code contains defects unknown to the new user, which, in turn, propagate vulnerabilities into new systems. This is troubling news in an operational climate already rife with cybersecurity risk. Organizations must develop a cybersecurity engineering strategy for systems that addresses the integration of DevSecOps with the software supply chain. In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Carol Woody, a principal researcher in the SEI’s CERT Division, talks with Suzanne Miller about supply-chain issues and the planning needed to integrate software from the supply chain into operational environments. The discussion includes building a cybersecurity engineering strategy for DevSecOps that addresses those supply-chain challenges.

In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), director Paul Nielsen talks with principal researcher Suzanne Miller about how the advent of smart systems has led to a growing need for effective collaboration and cross-pollination between the disciplines of systems engineering and software engineering.

In this podcast from the Carnegie Mellon University Software Engineering Institute, Gavin Jurecko, who leads the Resilience Diagnostics Team, talks with Katie Stewart about risks associated with the supply chains of the defense industrial base (DIB), and how the SEI works with the U.S. Department of Defense to help secure the DIB supply chain.

In this podcast from the Carnegie Mellon University Software Engineering Institute (SEI), Jeffrey Gennari, a senior malware reverse engineer, and Garret Wassermann, a vulnerability analyst, both with the SEI’s CERT Division, discuss Kaiju, a series of tools that they have developed that allows for malware analysis and reverse engineering. Kajiu helps analysts take better advantage of Ghidra, the National Security Agency’s reverse-engineering tool.

In this SEI Podcast, Anita Carleton, director of the Software Solutions Division at the SEI, and Forrest Shull, lead for defense software acquisition policy research in the Software Solutions Division of the SEI, discuss the recently published SEI-led study Architecting the Future of Software Engineering: A National Agenda for Software Engineering Research & Development. In creating this multi-year research and development vision and roadmap for engineering next-generation software-reliant systems, the SEI engaged the software engineering community and assembled an advisory board of senior thought leaders across commercial industry, academia, and government, with participation from Microsoft, Google, SpaceX, Lockheed Martin, Boeing, DARPA, and others.

In this podcast from the Carnegie Mellon University Software Engineering Institute, Carol Smith, a senior research scientist in Human Machine Interaction, and Alexandrea Van Deusen, an assistant design researcher, both with the SEI’s AI Division, discuss a recent project in which they helped the Defense Innovation Unit (DIU) of the U.S. Department of Defense develop guidelines for responsible use of artificial intelligence (AI), based on the DoD’s Ethical Principles for AI. These guidelines can serve as a guide for organizations in industry and government to implement responsible AI considerations into practice in real-world programs.

In this SEI Podcast, Nickolas Guertin, a senior systems engineer with the SEI’s Software Solutions Division, and Douglas Schmidt, associate provost of research at Vanderbilt University and former chief technical officer at the SEI, discuss strategies for creating architectures for large-scale, complex systems that comprise functions with a wide range of requirements. This is one of the most challenging areas in U.S. Department of Defense acquisition, and this approach and the strategies discussed are important to the future of our large systems.

Mismatches between the perspectives and practices of the roles involved in the development and fielding of ML systems—data scientists, software engineers, and operations personnel—can affect the ability of systems to achieve their intended missions. In this SEI Podcast, Grace Lewis, a principal researcher and lead for the Tactical and AI-Enabled Systems Initiative, and Ipek Ozkaya, technical director of Engineering Intelligent Software Systems, discuss their research into characterizing, codifying, and mitigating such mismatches.

In this SEI Podcast, Mike Konrad, a principal researcher in the SEI's Software Solutions Division, talks with 2020 IEEE Computer Society SEI Watts Humphrey Software Quality Award winner Rajendra Prasad of Accenture about automation and how SEI-developed process improvement methods and tools provided the foundation for his leadership role.

Organic software sustainment organizations within the Department of Defense are expanding beyond their traditional purview of software maintenance into software engineering and development. Instead of repairing and maintaining legacy software in already deployed systems, software sustainment teams must now shift to designing and implementing new software architectures and code. Unfortunately, many of these sustainment teams are taking on these new responsibilities without proper guidance and an understanding of the people, process, and technology issues that must first be addressed in these new roles. In this podcast, Thomas Evans, a senior software architect at the SEI, and Douglas C. Schmidt, associate provost of research at Vanderbilt University and former chief technical officer at the SEI, discuss the challenges that software sustainment teams face while making this transition and strategies for success.

In this podcast from the Carnegie Mellon University Software Engineering Institute, Carol Smith, a senior research scientist in human-machine interaction, and Jonathan Spring, a senior vulnerability researcher, discuss the hidden sources of bias in artificial intelligence (AI) systems and how systems developers can raise their awareness of bias, mitigate consequences, and reduce risks.

In this SEI Podcast in the “My Story in Computing” series, Rachel Dzombak discusses her journey integrating biomedical, mechanical, and civil engineering to her current leadership role at the SEI as digital transformation lead in artificial-intelligence (AI) engineering.

The rapid pace of change in software development, in business, and in the world has many organizations struggling to execute daily operations, wrangle big projects, and feel confident that there is a long-term strategy at play. Incorporating agile principles into strategic planning and execution is a highly effective way to drive strategy development, strategy execution, data-driven decision making, and results. In this SEI Podcast, Linda Parker Gates, initiative lead, Software Acquisition Pathways, and Suzanne Miller, principal researcher in the SEI’s Software Solutions Division, discuss the principles of Agile Strategic Planning and methods for success.

In this SEI Podcast, Dr. Leigh Metcalf and Dr. Jonathan Spring, both researchers with the Carnegie Mellon University Software Engineering Institute’s CERT Division, discuss the application of scientific methods to cybersecurity. As described in their recently published book, Using Science in Cybersecurity, Metcalf and Spring describe a common-sense approach and practical tools for applying scientific rigor to the field of cybersecurity.

Zero trust adoption is a security initiative that an enterprise must understand, interpret, and implement. Enterprise security initiatives are never simple, and their goal to improve cybersecurity posture requires the alignment of multiple stakeholders, systems, acquisitions, and exponentially changing technology. This alignment is always a complex undertaking and requires cybersecurity strategy and engineering to succeed. In this SEI Podcast, Geoff Sanders, a senior network defense analyst in the CERT Division at Carnegie Mellon University's Software Engineering Institute, discusses zero trust adoption and its benefits, applications, and available resources.

In this SEI Podcast, Dr. Eric Heim, a senior machine learning research scientist at Carnegie Mellon University's Software Engineering Institute (SEI), discusses the quantification of uncertainty in machine-learning (ML) systems. ML systems can make wrong predictions and give inaccurate estimates for the uncertainty of their predictions. It can be difficult to predict when their predictions will be wrong. Heim also discusses new techniques to quantify uncertainty, identify causes of uncertainty, and efficiently update ML models to reduce uncertainty in their predictions. The work of Heim and colleagues at the SEI Emerging Technology Center closes the gap between the scientific and mathematical advances from the ML research community and the practitioners who use the systems in real-life contexts, such as software engineers, software developers, data scientists, and system developers.  

In this SEI Podcast, Aaron Greenhouse, a senior architecture researcher with Carnegie Mellon University’s Software Engineering Institute, talks with principal researcher Suzanne Miller about use of the Bell–LaPadula mathematical security model in concert with the Architecture Analysis and Design Language (AADL) to model and validate confidentiality. Greenhouse and Miller also discuss 11 analysis rules that must be enforced over an AADL instance to ensure the consistency of a security model. Mapping Bell–LaPadula to AADL allows the expression of key concepts within the AADL model so that they can be analyzed automatically. 

Nataliya (Natasha) Shevchenko and Mary Popeck, both senior researchers in the CERT Division at Carnegie Mellon University’s Software Engineering Institute, discuss the use of model-based systems engineering (MBSE), which, in contrast to document-centric engineering, puts models at the center of system design. MBSE is used to support the requirements, design, analysis, verification, and validation associated with the development of complex systems.

In this SEI Podcast, Grace Lewis hosts a panel discussion with Ipek Ozkaya, Nathan West, and Jay Palat about diversity in software engineering. The panelists, all researchers with the Carnegie Mellon University Software Engineering Institute, share their perspectives about their own experiences in the software engineering field, the value of diversity to enhance problem solving from multiple perspectives, and strategies for supporting and encouraging underrepresented groups to become involved in the field.

Author Daniel H. Pink recently examined the factors that lead to job satisfaction among knowledge workers and summarized them in three components: autonomy, skill mastery, and purpose. In this SEI Podcast, Hasan Yasar, technical director of Continuous Deployment of Capability at Carnegie Mellon University’s Software Engineering Institute, relates these components to DevSecOps and summarizes a recent survey affirming that DevSecOps practices do indeed make developers and other stakeholders in their organizations happier.

In this SEI Podcast, digital transformation lead Dr. Rachel Dzombak and research scientist Carol Smith, both with the SEI’s Emerging Technology Center at Carnegie Mellon University, discuss how AI Engineering can support organizations to implement AI systems. The conversation covers the steps that organizations need to take (as well as the hard conversations that need to occur) before they are AI ready.

In this SEI Podcast, the latest in the My Story in Computing series, Marisa Midler, a cybersecurity engineer in the SEI’s CERT Division, discusses her career path. After growing up on a farm in Pennsylvania, Midler graduated from college with a degree in communications and English writing and then traveled to Seattle and worked a variety of jobs, including as a bouncer at a Seattle night club. Midler returned to Pittsburgh to obtain a second bachelor’s degree in information science followed by a master’s degree in information security policy and management from Carnegie Mellon University. Throughout it all Midler has been guided by her mantra: never settle.

The robustness and security of artificial intelligence, and specifically machine learning (ML), is of vital importance. Yet, ML systems are vulnerable to adversarial attacks. These can range from an attacker attempting to make the ML system learn the wrong thing (data poisoning), do the wrong thing (evasion attacks), or reveal the wrong thing (model inversion). Although there are several efforts to provide detailed taxonomies of the kinds of attacks that can be launched against a machine learning system, none are organized around operational concerns. In this podcast, Jonathan Spring, Nathan VanHoudnos, and Allen Householder, all researchers at the Carnegie Mellon University Software Engineering Institute, discuss the management of vulnerabilities in ML systems as well as the Adversarial ML Threat Matrix, which aims to close this gap between academic taxonomies and operational concerns.

In this SEI Podcast, Rachel Dzombak and Jay Palat discuss growth in the field of artificial intelligence (AI) and how organizations can hire and train staff to take advantage of the opportunities afforded by AI and machine learning—and the critical need for an AI engineering discipline to grow the AI workforce.

DevSecOps is a set of principles and practices that provide faster delivery of secure software capabilities by improving the collaboration and communication between software development teams, IT operations, and security staff within an organization, as well as with acquirers, suppliers, and other stakeholders in the life of a software system. In this SEI podcast, Hasan Yasar, technical director of the Continuous Deployment of Capability group in the Software Solutions Division of the SEI, discusses the transition from DevOps to DevSecOps.

In this SEI Podcast, the latest in the “My Story in Computing” series, which explores the unique paths people take into the field of computing, David Zubrow discusses his path from a PhD in applied history and social sciences and an administrative position at Carnegie Mellon University to a career as a manager and technical leader at the SEI.

In this SEI Podcast, Keith Korzec discusses the Mission-Based Prioritization method for prioritizing Agile backlogs. This method overcomes the shortcomings of prioritization based on “weighted shortest job first” and utilizes objective, mission-focused criteria while allowing ongoing re-prioritization to be conducted with minimal overhead.

Those who work in computing today bring a wide array of backgrounds and experiences to the profession. In this podcast, part of the My Story in Computing series, learn how Carol Smith, who trained as a photojournalist, discusses how a love of telling people’s stories led to a career in human-computer interaction working in artificial intelligence with the SEI’s Emerging Technology Center.

Digital engineering is an integrated digital approach that uses authoritative sources of systems data and models as a continuum across disciplines to support lifecycle activities from concept through disposal. With digital engineering, models are developed for everything, not just for software, but for all components of a system of systems, hardware and software. The models and associated data are stored in a singular repository of knowledge and are the single source that is used by all contractors and everyone working on the project. In this SEI Podcast, David Shepard, a researcher with the Carnegie Mellon University Software Engineering Institute, discusses digital engineering and its relationship with DevSecOps.

Brett Tucker, a technical manager for cyber risk in the SEI CERT Division, discusses the Operationally Critical Threat, Asset, and Vulnerability Evaluation for the Enterprise (OCTAVE FORTE) Model, which helps organizations evaluate security risks and use principles of enterprise risk management to bridge the gap between executives and practitioners. In this SEI Podcast, Tucker outlines OCTAVE FORTE's 10-step framework to guide organizations in managing risk.

If organizations take more steps to address security-related activities now, they will be less likely to encounter security incidents in the future. When it comes to application containers, security is achieved through adopting a series of best practices and guidelines. In this SEI Podcast, Tom Scanlon and Richard Laughlin, researchers with the SEI's CERT Division, discuss seven steps that developers can take to engineer security into ongoing and future container adoption efforts.

In this SEI Podcast, Marisa Midler and Tim Shimeall, network defense analysts within the SEI's CERT Division, discuss the growing problem of ransomware including the rise of ransomware as a service threats. Ransom payments from Quarter 3 of 2019 were on average $42,000, and in Quarter 1 of 2020, that average increased $70,000 to $112,000. The volume of attacks also increased by 25 percent in Quarter 4 of 2019 and by another 25 percent in Quarter 1 of 2020. The sophistication of the attacks has increased alongside their severity. Midler and Shimeall discuss steps and strategies that organizations can adopt to minimize their exposure to the risks and threats associated with ransomware.

Software vulnerability coordination at the CERT Coordination Center (CERT/CC) has traditionally relied on a hub-and-spoke model, with reports submitted to analysts at the CERT/CC analysts who would then work with contact affected vendors. To scale communications and increase the level of collaboration between vulnerability reporters, coordinators, and software vendors, the CERT/CC team has created a web-based platform for software vulnerability reporting and coordination called the Vulnerability Information and Coordination Environment (VINCE). In this SEI Podcast, Emily Sarneso, the architect of VINCE, and Art Manion, technical manager of the Vulnerability Analysis Team in the SEI’s CERT Division, discuss the rollout of VINCE, how to use it, and future work in vulnerability coordination.

The COVID-19 pandemic has forced significant changes in enterprise work practices, including an increased use of telecommunications technologies required by the new work-from-home policies that most organizations have instituted in response. In this podcast, Phil Groce, a senior network defense analyst in the CERT Division of the Carnegie Mellon University Software Engineering Institute, discusses the security implications of this dramatic increase in the number of people in organizations who are working from home, examines the threats and vulnerabilities associated with the increase in remote work, and offers practical solutions to individuals and enterprises for operating securely in this new environment.

The Cybersecurity Maturity Model Certification (CMMC) 1.0 for Defense Industrial Base (DIB) suppliers defines specific cybersecurity practices across five levels of maturity while also measuring the degree to which those practices are institutionalized within an organization. The CMMC model draws on maturity processes and cybersecurity best practices from multiple standards, including the National Institute of Standards and Technology (NIST) frameworks and references, as well as input from DIB entities and the Department of Defense. CMMC requires that DIB organizations complete an assessment of all CMMC practices at a particular level and become certified by a CMMC third-party assessment organization. When fully implemented, CMMC will require all DIB companies to achieve certification at one of the five CMMC levels, which includes both technical security practices and maturity processes. In this SEI Podcast, Andrew Hoover and Katie Stewart, researchers at the Carnegie Mellon University Software Engineering Institute and architects of the model, discuss the CMMC assessment guides, how they were developed, and how they can be used.

The Cybersecurity Maturity Model Certification (CMMC) 1.0 for Defense Industrial Base (DIB) suppliers defines specific cybersecurity practices across five levels of maturity while also measuring the degree to which those practices are institutionalized within an organization. The CMMC model draws on maturity processes and cybersecurity best practices from multiple standards, including the National Institute of Standards and Technology (NIST) frameworks and references, as well as input from DIB entities and the Department of Defense. CMMC requires that DIB organizations complete an assessment of all CMMC practices at a particular level and become certified by a CMMC third-party assessment organization. When fully implemented, CMMC will require all DIB companies to achieve certification at one of the five CMMC levels, which includes both technical security practices and maturity processes. In this SEI podcast, Andrew Hoover and Katie Stewart, architects of the CMMC model and researchers at Carnegie Mellon University's Software Engineering Institute, discuss the Level 3 Assessment Guide for the CMMC and how it differs from the Level 1 Assessment Guide.

The Cybersecurity Maturity Model Certification (CMMC) 1.0 for Defense Industrial Base (DIB) suppliers defines specific cybersecurity practices across five levels of maturity while also measuring the degree to which those practices are institutionalized within an organization. The CMMC model draws on maturity processes and cybersecurity best practices from multiple standards, including the National Institute of Standards and Technology (NIST) frameworks and references, as well as input from DIB entities and the Department of Defense. CMMC requires that DIB organizations complete an assessment of all CMMC practices at a particular level and become certified by a CMMC third-party assessment organization. When fully implemented, CMMC will require all DIB companies to achieve certification at one of the five CMMC levels, which includes both technical security practices and maturity processes. In this SEI Podcast, Andrew Hoover and Katie Stewart, architects of the CMMC model, discuss the Level 1 Assessment Guide for the CMMC.

Authority to Operate (ATO) is a process that certifies a system to operate for a certain period of time by evaluating the risk of the system's security controls. ATO is based on the National Institute of Standards and Technology’s Risk Management Framework (NIST 800-37). In this podcast, Shane Ficorilli and Hasan Yasar, both with the Carnegie Mellon University Software Engineering Institute, discuss continuous ATO, including challenges, the role of DevSecOps, and cultural issues that organizations must address.