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Challenges and Opportunities of Big Data Against Cyber Crime

Submission Deadline: 9 March 2018

Submission Deadline: 9 March 2018

IEEE Access invites manuscript submissions in the area of Challenges and Opportunities of Big Data Against Cyber Crime.

Cyber crime is growing at an unprecedented pace that greatly affects the Internet industry and the global economy. Increasingly sophisticated attack and offensive methods used by cyber criminals and the growing role of data-driven and intelligence-driven adversaries demonstrate that traditional approaches to mitigate cyber threats are becoming ineffective. Big Data has been creating a profound paradigm shift in addressing the growing cyber crime threats. The technological breakthrough in Big Data makes it possible for large-scale diversified and unstructured security data collecting, storage, aggregating, and processing across the defined scope in real time. Big Data analytics enables data-intensive solutions and threat intelligence to identify lurking malicious or at least suspicious activities from massive and/or misrepresented data sets. Modern Big Data technologies also spark automated controls for prompt response to detect cyber crime threats, such as disrupting clearly identified malware attacks.

This Special Section in IEEE Access aims to present cutting-edge research in addressing cybercrime challenges in the Big Data era. We solicit theoretical and practical contributions as well as surveys with clear use cases.

The topics of interest include, but are not limited to:

  • Big Data forensics
  • Anti-phishing and pharming using Big Data analytics
  • Big Data architectures for cyber security
  • Criminal use of IoT in the Big Data context
  • Cryptography and Big Data
  • Privacy preserving retrieval, transmission, processing, and analysis of Big Data
  • Data-intensive detection and prevention of online identify theft
  • Access control of Big Data
  • Big Data analytics for Online Social Networks threats
  • Malware & botnets analysis using Big Data
  • Big Data techniques in intrusion detection
  • Data mining and machine learning in anti-cyber crime
  • Formal models and ontologies for online criminal behavior
  • Criminal abuse of Big Data technologies and resources
  • Steganography/steg analysis and covert/subliminal channels
  • DoS/DDoS defense using Big Data
  • Adversary-resilient Big Data technologies
  • Standardization advances in Big Data for cyber security

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Jun Huang, Chongqing University of Posts and Telecommunications, China

Guest Editors:

  1. Zheng Wang, National Institute of Standards and Technology, USA
  2. Shui Yu, Deakin University, Australia
  3. Zheng Chang, University of Jyväskylä, Finland
  4. Nirwan Ansari, New Jersey Institute of Technology, USA

Relevant IEEE Access Special Sections:

  1. Advanced Big Data Analysis for Vehicular Social Networks
  2. Ambient Intelligence Environments with Wireless Sensor Networks from the Point of View of Big Data and Smart & Sustainable Cities
  3. Real-Time Edge Analytics for Big Data in Internet of Things

 

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://mc.manuscriptcentral.com/ieee-access

For inquiries regarding this Special Section, please contact:  xiaoniuadmin@gmail.com