Accelerating Malware Detection via a Graphics Processing Unit

Abstract

Real-time malware analysis requires processing large amounts of data storage to look for suspicious files. This is a time consuming process that (requires a large amount of processing power) often affecting other applications running on a personal computer. This research investigates the viability of using Graphic Processing Units (GPUs), present in many personal computers, to distribute the workload normally precessed by the standard Central Processing Unit (CPU). Three experiments are conducted using an industry standard GPU, the NVIDIA GeForce 9500 GT card. Experimental results show that a GPU can calculate a MD5 signature hash and scan a database of malicious signatures 82% faster then a CPU for files between 0 - 96 kB. If the file size is increased to 97 - 192 kB the GPU is 85% faster than the CPU. This demonstrates that the GPU can provide a greater performance increase over a CPU.These results could help achieve faster anti-malware products, faster network intrusion detection system response times, and faster firewall applications.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2010
Accession Number
ADA529467

Entities

People

  • Nicholas S. Kovach

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Cyber

DTIC Thesaurus Topics

  • Air Force
  • Anti-Virus Software
  • Central Processing Units
  • Computer Programming
  • Computer Programs
  • Computer Viruses
  • Computers
  • Cybersecurity
  • Detection
  • Image Processing
  • Information Science
  • Instruction Set Architecture
  • Intrusion Detection
  • Intrusion Detection Systems
  • Intrusion Detectors
  • Malware
  • Operating Systems

Fields of Study

  • Computer science

Readers

  • Parallel and Distributed Computing.

Technology Areas

  • Cyber