Archive: 2014-08

According to a 2013 report examining 25 years of vulnerabilities (from 1998 to 2012), buffer overflow causes 14 percent of software security vulnerabilities and 35 percent of critical vulnerabilities, making it the leading cause of software security vulnerabilities overall. As of July 2014, the TIOBE index indicates that the C programming language, which is the language most commonly associated with buffer overflows, is the most popular language with 17.1 percent of the market. Embedded systems, network stacks, networked applications, and high-performance computing rely heavily upon C. Embedded systems can be especially vulnerable to buffer overflows because many of them lack hardware memory management units. This blog post describes my research on the Secure Coding Initiative in the CERT Division of the Carnegie Mellon University Software Engineering Instituteto create automated buffer overflow prevention.

In today's systems it's very hard to know where systems end and software begins. Software performs an integrating function in many systems, often serving as the glue interconnecting other system elements. We also find that many of the problems in software systems have their roots in systems engineering, which is an interdisciplinary field that focuses on how to design and manage complex systems over their life cycles. For that reason, staff at the Carnegie Mellon University Software Engineering Institute (SEI) often conduct research in the systems engineering realm. Process frameworks, architecture development and evaluation methods, and metrics developed for software are routinely adapted and applied to systems. Better systems engineering supports better software development, and both support better acquisition project performance. This blog post, the latest in a serieson this research, analyzes project performance based on systems engineering activities in the defense and non-defense industries.

The term big data is a subject of much hype in both government and business today. Big data is variously the cause of all existing system problems and, simultaneously, the savior that will lead us to the innovative solutions and business insights of tomorrow. All this hype fuels predictions such as the one from IDC that the market for big data will reach $16.1 billion in 2014, growing six times faster than the overall information technology market, despite the fact that the "benefits of big data are not always clear today," according to IDC. From a software-engineering perspective, however, the challenges of big data are very clear, since they are driven by ever-increasing system scale and complexity. This blog post, a continuation of my last poston the four principles of building big data systems, describes how we must address one of these challenges, namely, you can't manage what you don't monitor.

Organizations are continually fending off cyberattacks in one form or another. The 2014 Verizon Data Breach Investigations Report, which included contributions from SEI researchers, tagged 2013 as "the year of the retailer breach." According to the report, 2013 also witnessed "a transition from geopolitical attacks to large-scale attacks on payment card systems." To illustrate the trend, the report outlines a 12-month chronology of attacks, including a January "watering hole" attack on the Council on Foreign Relations website followed in February by targeted cyber-espionage attacks against The New York Times and The Wall Street Journal. The well-documented Target breachbrought 2013 to a close with the theft of more than 40 million debit and credit card numbers. This blog post highlights a recent research effort to create a taxonomy that provides organizations a common language and set of terminology they can use to discuss, document, and mitigate operational cybersecurity risks.