Insider threat is the threat to organization's critical assets posed by trusted individuals - including employees, contractors, and business partners - authorized to use the organization's information technology systems. Insider threat programs within an organization help to manage the risks due to these threats through specific prevention, detection, and response practices and technologies. The National Industrial Security Program Operating Manual (NISPOM), which provides baseline standards for the protection of classified information, is considering proposed changes that would require contractors that engage with federal agencies, which process or access classified information, to establish insider threat programs.
More and more, suppliers of software-reliant Department of Defense (DoD) systems are moving away from traditional waterfall development practices in favor of agile methods. As described in previous posts on this blog, agile methods are effective for shortening delivery cycles and managing costs. If the benefits of agile are to be realized effectively for the DoD, however, personnel responsible for overseeing software acquisitions must be fluent in metrics used to monitor these programs. This blog post highlights the results of an effort by researchers at the Carnegie Mellon University Software Engineering Institute to create a reference for personnel who oversee software development acquisition for major systems built by developers applying agile methods. This post also presents seven categories for tracking agile metrics.
As recent news attests, the rise of sociotechnical ecosystems (STE)--which, we define as a software system that engages a large and geographically-distributed community in a shared pursuit--allows us to work in a mind space and a data space that extends beyond anything that we could have imagined 20 or 30 years ago. STEs present opportunities for tackling problems that could not have even been approached previously because the needed experts and data are spread across multiple locations and distance.
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 assuring software reliability, future architectures, Agile software teams, insider threat, and HTML5. This post includes a listing of each report, author(s), and links where the published reports can be accessed on the SEI website.
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.
If you're considering migrating to IPv6, you may be asking, Am I ready? That's a good question to ask, but you also have to ask, Is my ISP ready? If your Internet service provider (ISP) isn't ready for an IPv6...