Recognition of Computer Viruses by Detecting Their Gene of Self Replication

Abstract

An approach to the detection of malicious software by detecting its ability to self-replicate is proposed, implemented and tested. The approach is justified by the following realities most malicious programs propagate themselves through the Internet to maximize the impact of the information attack; self-replication of legitimate programs is quite uncommon; number of practical self-replication techniques is quite limited and is to be repeatedly used by new malicious codes. A Source Code Analyzer operating as a specialized compiler (interpreter) and a special syntax library were developed for the detection of self-replication functionality in source codes /scripts prior to execution. Major building blocks of the existing self-replication techniques were defined in the domain of system calls and their attributes, and a procedure for the reconstruction of these blocks by analyzing the flow of system call was established. A dynamic Code Analyzer and System Calls Monitor were developed for the run-time detection of the attempted self-replication in executable and encrypted executable codes. The efficiency of the developed technology, including the ability to detect previously unknown malicious programs has been experimentally demonstrated.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2006
Accession Number
ADA448622

Entities

People

  • Douglas Summerville
  • Victor Skormin

Organizations

  • Binghamton University

Tags

Communities of Interest

  • Cyber
  • Engineered Resilient Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Application Software
  • Computer Network Security
  • Computer Networks
  • Computer Program Documentation
  • Computer Programming
  • Computer Programs
  • Computer Viruses
  • Computers
  • Detection
  • Electronic Mail
  • Graphical User Interface
  • Malware
  • Network Protocols
  • Operating Systems
  • Word Processors

Fields of Study

  • Computer science

Readers

  • Cybersecurity.
  • Database Systems and Applications
  • Sensor Fusion and Tracking Systems.