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Outgoing data filtration for detecting spyware on personal computers

  • Khalid Samara
    ,
  • Aishwarya Afzulpurkar
    ,
  • Mouza Alshemaili
Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Abstract

One of the most critical issues emerging from the Internet is the diverse number of spyware and bots. When a spyware is installed in your PC then it will be difficult to detect, mainly because it deploys covert channels to communicate with outbound data transmissions. These attacks are usually sent from PCs infected with a bot that communicates with malicious controllers over an encrypted channel. However, the available pattern-based intrusion detection system (IDS) and antivirus systems (AVs) are unable to detect the infected PC. This paper presents a Monitoring and Filtering method (SMF) for outgoing packets based on machine learning and behavioral-based methods that can help in the protection of PCs. In addition, this paper presents recent research contributions and emerging tools in the field of spyware detection and identifies existing gaps in the literature. The paper then presents a High-level Architecture to inspect the outgoing packet from the hardware and the software installed in PCs as a solution.

Publication Information

Output type

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Original language

English

Publication milestones

  • Accepted/In press - 06/02/2019
  • Published - 06/02/2019

Publication status

Published - 06/02/2019

Publisher

Springer, Japan, India, Australia, Germany, United States, United Arab Emirates, Austria, Switzerland, Italy, China, United Kingdom, Netherlands, Brazil, France, Singapore

ISBN (Print)

9783030128388

ISBN (Electronic)

9783030128395

External Publication IDs

  • handle.net: 10547/625447
  • Scopus: 85082322307

Host publication title

Lecture Notes on Data Engineering and Communications Technologies

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