Malware--generically defined as software designed to access a computer system without the owner's informed consent--is a growing problem for government and commercial organizations. In recent years, research into malware focused on similarity metrics to decide whether two suspected malicious files are similar to one another. Analysts use these metrics to determine whether a suspected malicious file bears any resemblance to already verified malicious files. Using these metrics allows analysts to potentially save time, by identifying opportunities to leverage previous analysis. This post will describe our efforts to develop a technique (known as fuzzy hashing) to help analysts determine whether two pieces of suspected malware are similar.
Malicious software (known as "malware") is increasingly pervasive with a constant influx of new, increasingly complex strains that wreak havoc by exploiting computers or personal and business information stored therein for malicious or criminal purposes. Examples include code that is designed to pilfer personal and digital credentials; plunder sensitive information from government or business enterprises; or interrupt, misdirect, or render inoperable computer hardware and computer-controlled equipment. This post describes our work to create a rapid search capability that allows analysts to quickly analyze a new piece of malware.
Large-scale DoD acquisition programs are increasingly being developed atop reusable software platforms--known as Common Operating Environments (COEs) --that provide applications and end-users with many net-centric capabilities, such as cloud computing or Web 2.0 applications, including data-sharing, interoperability, user-centered design, and collaboration. Selecting an appropriate COE is critical to the success of acquisition programs, yet the processes and methods for evaluating COEs had not been clearly defined. I explain below how the SEI developed a Software Evaluation Framework and applied it to help assess the suitability of COEs for the US Army.
Continuous technological improvement is the hallmark of the hardware industry. In an ideal world--one without budgets or schedules--software would be redesigned and redeveloped from scratch to leverage each such improvement. But applying this process for software is often infeasible--if not impossible--due to economic constraints and competition. This posting discusses our research in applying verification, namely regression verification, to help the migration of real-time embedded systems from single-core to multi-core platforms.
Malware--generically defined as software designed to access a computer system without the owner's informed consent--is a growing problem for government and commercial organizations. In recent years, research into malware focused on similarity metrics to decide whether two suspected malicious files...