This blog post was co-authored by Will Klieber.
Each software application installed on a mobile smartphone, whether a new app or an update, can introduce new, unintentional vulnerabilities or malicious code. These problems can lead to security challenges for organizations whose staff uses mobile phones for work. In April 2014, we published a blog post highlighting DidFail (Droid Intent Data Flow Analysis for Information Leakage), which is a static analysis tool for Android app sets that addresses data privacy and security issues faced by both individual smartphone users and organizations. This post highlights enhancements made to DidFail in late 2014 and an enterprise-level approach for using the tool.
As recent news headlines about Shellshock, Sony, Anthem, and Target have demonstrated, software vulnerabilities are on the rise. The U.S. General Accounting Office in 2013 reported that "operational vulnerabilities have increased 780 percent over the past six years." These vulnerabilities can be hard and expensive to eradicate, especially if introduced during the design phase. One issue is that design defects exist at a deeper architectural level and thus can be hard to find and address. Although coding-related vulnerabilities are preventable and detectable, until recently scant attention has been paid to vulnerabilities arising from requirements and design defects.
Mismatched assumptions about hardware, software, and their interactions often result in system problems detected too late in the development lifecycle, which is an expensive and potentially dangerous situation for developers and users of mission- and safety-critical technologies. To address this problem, the Society of Automotive Engineers (SAE) released the aerospace standard AS5506, named the Architecture Analysis & Design Language (AADL). The AADL standard,defines a modeling notation based on a textual and graphic representation used by development organizations to conduct lightweight, rigorous--yet comparatively inexpensive--analyses of critical real-time factors, such as performance, dependability, security, and data integrity.
As part of an ongoing effort to keep you informed about our latest work, I would like to let you know about some recently published SEI technical reports and notes. These reports highlight the latest work of SEI technologists in resilience, metrics, sustainment, and software assurance. This post includes a listing of each report, author(s), and links where the published reports can be accessed on the SEI website.
The Department of Defense (DoD) and other government agencies increasingly rely on software and networked software systems. As one of over 40 federally funded research and development centers sponsored by the United States government, Carnegie Mellon University's Software Engineering Institute (SEI) is working to help the government acquire, design, produce, and evolve software-reliant systems in an affordable and secure manner. The quality, safety, reliability, and security of software and the cyberspace it creates are major concerns for both embedded systems and enterprise systems employed for information processing tasks in health care, homeland security, intelligence, logistics, etc. Cybersecurity risks, a primary focus area of the SEI's CERT Division, regularly appear in news media and have resulted in policy action at the highest levels of the US government (See Report to the President: Immediate Opportunities for Strengthening the Nation's Cybersecurity ).
This blog post was co-authored by Eric Werner.
Graph algorithms are in wide use in Department of Defense (DoD) software applications, including intelligence analysis, autonomous systems, cyber intelligence and security, and logistics optimizations. In late 2013, several luminaries from the graph analytics community released a position paper calling for an open effort, now referred to as GraphBLAS, to define a standard for graph algorithms in terms of linear algebraic operations. BLAS stands for Basic Linear Algebra Subprograms and is a common library specification used in scientific computation. The authors of the position paper propose extending the National Institute of Standards and Technology's Sparse Basic Linear Algebra Subprograms (spBLAS) library to perform graph computations. The position paper served as the latest catalyst for the ongoing research by the SEI's Emerging Technology Center in the field of graph algorithms and heterogeneous high-performance computing (HHPC). This blog post, the second in our series, describes our efforts to create a software library of graph algorithms for heterogeneous architectures that will be released via open source.
As software continues to grow in size and complexity, software programmers continue to make mistakes during development. These mistakes can result in defects in software products and can cause severe damage when the software goes into production. Through the Personal Software Process (PSP), the Carnegie Mellon University Software Engineering Institute has long advocated incorporating discipline and quantitative measurement into the software engineer's initial development work to detect and eliminate defects before the product is delivered to users. This blog post presents an approach for incorporating formal methods with PSP, in particular, Verified Design by Contract, to reduce the number of defects earlier in the software development lifecycle while preserving or improving productivity.
As part of an ongoing effort to keep you informed about our latest work, I would like to let you know about some recently published SEI technical reports and notes. These reports highlight the latest work of SEI technologists in software assurance, social networking tools, insider threat, and the Security Engineering Risk Analysis Framework (SERA). This post includes a listing of each report, author(s), and links where the published reports can be accessed on the SEI website.