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IJBDSI - GV Press
Aim and Scope

The International Journal of Big Data Security Intelligence (IJBDSI) provides a chance for academic and industry professionals to discuss recent progress in the area of Big Data Security. IJBDSI publishes scholarly research articles, reviews and case studies on all aspects of big data and their emerging technologies. With major security breaches and fraud incidents making international headlines, organizations are taking steps to address the growing problems of advanced persistent threats, fraud, and insider attacks.The lack of sophisticated capabilities and visibility required to detect and protect against such attacks, let researchers and institutions to use Big Data analytics to obtain actionable intelligence in real time to identify the security holes. Big Data enables various capabilities, for instance, forensics and the analysis of long-term historical trends. By collecting data on a large scale and analyzing historical trends, you would be able identify when an attack started, and what were the steps that the attacker took to get ahold of your systems. Even if you did not detect the original attack in your systems, you can go back and do an historical correlation in your database and systems to identify the attack. So long-term historical analysis is one advantage. There are many other intelligence techniques that can be used to enforce higher security.

Topics Covered

The main topics include but will not be limited to: (Excellent surveying works, summary or introduction of new or fresh idea in these areas are welcome, too).

  • Big Data Analytics Security
  • Security Information and Event Management
  • Identity and Access Management
  • Fraud Protection
  • Governance, Risk and Compliance
  • Big Data Security Standards
  •  Computational Models for Big Data Security
  • Secure Big Data Infrastructures (including Cloud/Grid/Cluster/Stream/High Performance)
  • Intelligence Based Security for Big Data
  • Security Attacks on Big Data
  • Security and Intruder Detection Recommenders 
  • Big Data Security Holes Visualization
  • Big Data Privacy, Protection and Policies

 

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