The Department of Defense is increasingly relying on biometric data, such as iris scans, gait recognition, and heart-rate monitoring to protect against both cyber and physical attacks. "Military planners, like their civilian infrastructure and homeland security counterparts, use video-linked 'behavioral recognition analytics,' leveraging base protection and counter-IED operations," according to an article in Defense Systems. Current state-of-the-art approaches do not make it possible to gather biometric data in real-world settings, such as border and airport security checkpoints, where people are in motion. This blog post presents the results of exploratory research conducted by the SEI's Emerging Technology Center to design algorithms that extract heart rate from video of non-stationary subjects in real time.
This blog post is also authored by Josh Hammerstein.
There are many opportunities for front-line soldiers to use cyber tactics to help them achieve their missions. For example, a soldier on a reconnaissance mission who enters a potentially hostile or dangerous space, such as a storefront in enemy territory, might be able to gain access to an open wireless access point in the area or exploit vulnerabilities in the building's alarm-communication system. These exploits would allow the soldier to provide indicators and warnings to other soldiers in the area about possible enemy activity and threats. Soldiers can expand their arsenal through greater awareness of specific lethal and non-lethal cyber tactics available to them. This blog post describes a new prototype tool developed at the SEI designed to help the soldier identify and exploit cyber opportunities in the physical environment.
Blockchain technology was conceived a little over ten years ago. In that short time, it went from being the foundation for a relatively unknown alternative currency to being the "next big thing" in computing, with industries from banking to insurance to defense to government investing billions of dollars in blockchain research and development. This blog post, the first of two posts about the SEI's exploration of DoD applications for blockchain, provides an introduction to this rapidly emerging technology.
When I was pursuing my master's degree in information security, two of the required classes were in cognitive psychology and human factors: one class about how we think and learn and one about how we interact with our world. Students were often less interested in these courses and preferred to focus their studies on more technical topics. I personally found them to be two of the most beneficial. In the years since I took those classes, I've worked with people in many organizations in roles where it is their job to think: security operations center (SOC) analysts, researchers, software developers, and decision makers. Many of these people are highly technical, very intelligent, and creative. In my interactions with these groups, however, the discussion rarely turns to how to think about thinking. For people whose jobs entail pulling together and interpreting data to answer a question or solve a problem (i.e. analyze), ignoring human factors and how we and others perceive, think, and remember can lead to poor outcomes. In this blog post, I will explore the importance of thinking like an analyst and introduce a framework to help guide security operations center staff and other network analysts.
The crop of Top 10 SEI Blog posts in the first half of 2017 (judged by the number of visits by our readers) represents the best of what we do here at the SEI: transitioning our knowledge to those who need it. Several of our Top 10 posts this year are from a series of posts on best practices for network security that we launched in November 2016 in the wake of the Dyn attack. In this post, we will list the Top 10 posts with an excerpt from each post as well as links to where readers can go for more information about the topics covered in the SEI blog.
As part of an ongoing effort to keep you informed about our latest work, this blog post summarizes some recently published SEI technical reports, white papers, podcasts and webinars on supply chain risk management, process improvement, network situational awareness, software architecture, network time protocol as well as a podcast interview with SEI Fellow Peter Feiler. These publications highlight the latest work of SEI technologists in these areas. This post includes a listing of each publication, author(s), and links where they can be accessed on the SEI website.
During the wars in Iraq and Afghanistan, insurgents' use of improvised explosive devices (IEDs) proliferated. The United States ramped up its development of counter-IED equipment to improve standoff detection of explosives and explosive precursor components and to defeat IEDs themselves as part of a broader defense capability. One effective strategy was jamming or interrupting radio frequency (RF) communications to counter radio-controlled IEDs (RCIEDs). This approach disrupts critical parts of RF communications, making the RCIED's communication to activate ineffective, saving both warfighter and civilian lives and property. For some time now, the cyber world has also been under attack by a diffused set of enemies who improvise their own tools in many different varieties and hide them where they can do much damage. This analogy has its limitations; however, here I want to explore the idea of disrupting communications from malicious code such as ransomware that is used to lock up your digital assets, or data-exfiltration software that is used to steal your digital data.
Many organizations want to share data sets across the enterprise, but taking the first steps can be challenging. These challenges range from purely technical issues, such as data formats and APIs, to organizational cultures in which managers resist sharing data they feel they own. Data Governance is a set of practices that enable data to create value within an enterprise. When launching a data governance initiative, many organizations choose to apply best practices, such as those collected in the Data Management Association's Body of Knowledge (DAMA-BOK). While these practices define a desirable end state, our experience is that attempting to apply them broadly across the enterprise as a first step can be disruptive, expensive, and slow to deliver value. In our work with several industry and government organizations, SEI researchers have developed an incremental approach to launching data governance that delivers immediate payback. This post highlights our approach, which is based on six principles.