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Cybersecurity: timeline malware analysis and classification

Cybersecurity: timeline malware analysis and classification

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In this chapter, we address the introduction to cybersecurity and problems associated with cybersecurity in particular malicious activities in cyber space. The proliferation and exponential increase of malware has continued to present a serious threat to the security of information systems. Furthermore, with the development of evermore sophisticated methods of evading detection, malware has posed serious challenges to combat it. Moreover, due to the continuous changes in malware design, antimalware (AM) strategy that has been successful in a given time period will not work at a much later date. In this chapter, we propose the challenges of malware in cyberspace and its detection approach called cumulative timeline analysis (CTA) that retains high accuracy over an extended time period. The effectiveness of the proposed approach is tested on malware executables collected over a span of 10 years with almost constant accuracy.

Chapter Contents:

  • 10.1 Introduction
  • 10.1.1 Significance
  • 10.1.2 Problems
  • 10.2 Timeline malware analysis and classification
  • 10.3 Related work
  • 10.4 Malware sample collection
  • 10.4.1 The methodology
  • 10.4.2 Data collection
  • 10.5 Cumulative timeline analysis
  • 10.5.1 CTA data preprocessing
  • 10.5.2 CTA feature vector generation
  • 10.5.2.1 Static vector generation
  • 10.5.2.2 Dynamic vector generation
  • 10.6 CTA malware detection method
  • 10.6.1 Environment
  • 10.6.2 Evaluation process
  • 10.7 Experiments and results
  • 10.7.1 Timeline classification results using FLF features
  • 10.7.2 Timeline classification results using PSI features
  • 10.7.3 Timeline classification results using dynamic features
  • 10.8 Conclusions and future work
  • References

Inspec keywords: information systems; invasive software

Other keywords: cybersecurity; serious threat; timeline malware analysis; information systems; cyber space; cumulative timeline analysis; malicious activities

Subjects: Data security

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