Cybersecurity Data Science

A special issue of Network (ISSN 2673-8732).

Deadline for manuscript submissions: closed (7 February 2022) | Viewed by 443

Special Issue Editors


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Guest Editor
School of Mathematical and Computer Science, Heriot Watt University, Edinburgh EH14 4AS, UK
Interests: malware data science; natural language processing; intrusion detection; access control systems; machine learning; peer-to-peer systems

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Guest Editor
School of Mathematical and Computer Science, Heriot Watt University, Edinburgh EH14 4AS, UK
Interests: computer science; machine learning; knowledge management; big data
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Guest Editor
Department of Computer Science College of Sciences, University of Sharjah, Sharjah, United Arab Emirates
Interests: cyber security; software fingerprinting; malware analysis; secure software and systems engineering

Special Issue Information

Dear Colleagues,

Applying data science methodologies and techniques to network security is becoming a popular trend. The last decade has witnessed a proliferation in academic proposals in this field. Furthermore, commercial cybersecurity products, e.g., SIEM and anti-malware, are increasingly shipping their software packages with data visualization, analysis, machine learning, and big data functionalities. The ultimate goal of cybersecurity data science is to extract useful insights from the analyzed data and build data-driven intelligent cybersecurity models for more automated and smart cybersecurity solutions.

In the context of cybersecurity, data can take several and different forms, including security and system logs, network traffic, configuration information, source code, and binaries. Each data type comes with its own challenges and might suggest different methodologies to be applied to it.

This Special Issue focuses on cybersecurity data science and aims to represent the most recent innovations in that field. The scope of this Special Issue includes but is not limited to the application of data science to the following fields:

  • Malware behavior analytics and detection;
  • Network intrusion detection;
  • Open-source intelligence processing;
  • Security orchestration, automation, and response;
  • Automatic vulnerability identification;
  • Malware author characterization and identification;
  • Digital forensics and incident response;
  • Autonomous vehicle technologies security;
  • User and entity behavior analytics;
  • Next-generation security operation centers;
  • IoT security;
  • Cloud security;
  • Data protection.

Dr. Hani Ragab Hassen
Dr. Abrar Ullah
Dr. Djedjiga Mouheb
Guest Editors

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Keywords

  • network security
  • cybersecurity
  • data science
  • deep learning
  • machine learning
  • malware analysis
  • intrusion detection
  • security operations
  • incident response
  • next-generation cybersecurity
  • security intelligence
  • big data
  • analytics
  • data visualization

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Published Papers

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