Entries Tagged as 'Malware '

Using Machine Learning to Detect Malware Similarity

Machine Learning , Malware 3 Comments »

By Sagar Chaki, Senior Member of the Technical Staff
Research, Technology, and System Solutions

Sagar Chaki Malware, which is short for “malicious software,” consists of programming aimed at disrupting or denying operation, gathering private information without consent, gaining unauthorized access to system resources, and other inappropriate behavior. Malware infestation is of increasing concern to government and commercial organizations. For example, according to the Global Threat Report from Cisco Security Intelligence Operations, there were 287,298 “unique malware encounters” in June 2011, double the number of incidents that occurred in March. To help mitigate the threat of malware, researchers at the SEI are investigating the origin of executable software binaries that often take the form of malware. This posting augments a previous posting describing our research on using classification (a form of machine learning) to detect “provenance similarities” in binaries, which means that they have been compiled from similar source code (e.g., differing by only minor revisions) and with similar compilers (e.g., different versions of Microsoft Visual C++ or different levels of optimization).

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Fuzzy Hashing Techniques in Applied Malware Analysis

CERT , Fuzzy Hashing , Malware 3 Comments »

By David French,
CERT Senior Researcher

David French 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.

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A New Approach to Modeling Malware using Sparse Representation

Malware No Comments »

by William Casey,
CERT Senior Researcher

Will Casey 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.

 

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New & Upcoming SEI Research Initiatives

Binaries , Malware No Comments »

By Douglas C. Schmidt,
Chief Technology Officer

Doug SchmidtIn response to a comment on my initial post introducing the SEI blog, I wanted to provide some additional information on new and upcoming SEI research initiatives. In this post, I describe these areas, and include a “sneak preview” of upcoming blog postings in each area.

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Learning a Portfolio-Based Checker for Provenance-Similarity of Binaries

Binaries , Malware No Comments »

By Sagar Chaki, Senior Member of the Technical Staff
Research Technology and System Solutions (RTSS)

Sagar Chaki As software becomes an ever-increasing part of our daily lives, organizations find themselves relying on software that originates from unknown and untrusted sources. The vast majority of such software is available only as executables, known as “binaries.” Many binaries—such as malware or different versions and builds of a software package—are simply minor variants of old programs (or in some cases exact copies) that have been run through a different compiler. This blog post explains how the ability to detect similarities among binaries is an important tool in malware detection and a growing area of research.

 

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