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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, …
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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,…
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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)…
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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 solu…
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How can we effectively use large language models (LLMs) for cybersecurity tasks? In this Carnegie Mellon University Software Engineering Institute podcast, Jeff Gennari and Sam Perl discuss applications for LLMs in cybersecurity, potential challenges, and recommendations for evaluating LLMs.
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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 understa…
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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 R…
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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 Rede…
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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 dive…
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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 …
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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 …
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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…
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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 Septe…
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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 success…
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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 engine…
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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 proc…
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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 seni…
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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 Compu…
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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 m…
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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 …
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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 f…
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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 co…
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