Security and Communication Networks

AI-Driven Cyber Security Analytics and Privacy Protection


Publishing date
01 Mar 2019
Status
Published
Submission deadline
12 Oct 2018

Lead Editor
Guest Editors

1Central China Normal University, Hubei, China

2University of Aizu, Aizuwakamatsu, Japan

3Xidian University, Xi'an, China


AI-Driven Cyber Security Analytics and Privacy Protection

Description

The cyber security techniques have gone through a rapid development in today’s internet connected world. With the wide application of the booming technologies such as the Internet of things (IoT) and cloud computing, huge amount of data is generated and collected. While the data can be used to better serve the corresponding business needs, it also poses big challenges for the cyber security and privacy protection. It becomes difficult to discover the malicious behavior among the big data in real time. Thus, this gives rise to the cyber security solutions which are driven by AI-based technologies, such as machine learning, statistical inference, big data analysis, and deep learning.

AI-driven cyber security analytics has already found its applications in the next generation firewall, automatic intrusion detection system, encrypted traffic identification, malicious software detection and so on. Researchers are now assisted by the AI-driven solution to optimize the algorithm design and reduce the cryptanalysis effort. Also automatic data protection solution based on the deep learning technology starts to appear in academia. On the other hand, individual’s privacy is under threat given the AI-based systems. The rise of AI-enabled cyberattacks is expected to cause an explosion of network penetrations, personal data thefts, and an epidemic-level spread of intelligent computer viruses. This brings the concern to defend AI-driven attacks by using AI-driven techniques, which could possibly lead to an AI arms race. AI-driven security solution is among the fastest growing fields which bring together researchers from multiple areas such as machine learning, statistics, big data analytics, network, and cryptography to fight against the advanced cyber security threats.

This special issue is focused on the cutting-edge research from both academia and industry, with a particular emphasis on the new tools, techniques, concepts, and applications concerning the AI-driven cyber security analytics and privacy protection. Only technical papers describing previously unpublished, original, state-of-the-art research and not currently under review by a conference or a journal will be considered. Extended work must have a significant number of "new and original" contributions along with more than 60% brand "new" material.

Potential topics include but are not limited to the following:

  • Applications of machine learning in network security and privacy
  • Automated design of cryptographic primitives
  • Automated and intelligent cryptanalysis
  • Automated Vulnerability Assessment/ Penetration Testing
  • Cloud computing and social media security and privacy
  • Cybercrime and cyberwar
  • Denial of Service/ Distributed Denial of Service (DoS/DDoS)
  • Intrusion detection/prevention systems
  • Intelligent encrypted traffic identification
  • Malware (Virus, Worms, Trojans, Backdoors) analysis
  • Multiparty/multiagent access control
  • Privacy and personal information protection

Articles

  • Special Issue
  • - Volume 2019
  • - Article ID 1859143
  • - Editorial

AI-Driven Cyber Security Analytics and Privacy Protection

Jiageng Chen | Chunhua Su | Zheng Yan
  • Special Issue
  • - Volume 2019
  • - Article ID 8357241
  • - Research Article

CCA Secure Public Key Encryption against After-the-Fact Leakage without NIZK Proofs

Yi Zhao | Kaitai Liang | ... | Liqun Chen
  • Special Issue
  • - Volume 2019
  • - Article ID 7541269
  • - Research Article

Secure Information Sharing System for Online Patient Networks

Hyun-A Park
  • Special Issue
  • - Volume 2019
  • - Article ID 7140480
  • - Research Article

Mining the Key Nodes from Software Network Based on Fault Accumulation and Propagation

Huang Guoyan | Wang Qian | ... | Yan Huaizhi
  • Special Issue
  • - Volume 2019
  • - Article ID 8391425
  • - Research Article

A Buffer Overflow Prediction Approach Based on Software Metrics and Machine Learning

Jiadong Ren | Zhangqi Zheng | ... | Huaizhi Yan
  • Special Issue
  • - Volume 2019
  • - Article ID 3898951
  • - Research Article

An Insider Threat Detection Approach Based on Mouse Dynamics and Deep Learning

Teng Hu | Weina Niu | ... | Yuan Liu
  • Special Issue
  • - Volume 2019
  • - Article ID 2674684
  • - Research Article

A Feature Extraction Method of Hybrid Gram for Malicious Behavior Based on Machine Learning

Yuntao Zhao | Bo Bo | ... | Bo Yu
  • Special Issue
  • - Volume 2019
  • - Article ID 9595081
  • - Research Article

Identifying Known and Unknown Mobile Application Traffic Using a Multilevel Classifier

Shuang Zhao | Shuhui Chen | ... | Jinshu Su
Security and Communication Networks
 Journal metrics
Acceptance rate31%
Submission to final decision83 days
Acceptance to publication42 days
CiteScore4.200
Impact Factor1.288
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