Journal Information
Security and Communication Networks (SCN)
Impact Factor:

Call For Papers
Security and Communication Networks is an international journal publishing original research and review papers on all security areas including network security, cryptography, cyber security, etc. The emphasis is on security protocols, approaches and techniques applied to all types of information and communication networks, including wired, wireless and optical transmission platforms.

The journal provides a prestigious forum for the R&D community in academia and industry working at the inter-disciplinary nexus of next generation communications technologies for security implementations in all network layers.

Answering the highly practical and commercial importance of network security R&D, submissions of applications-oriented papers describing case studies and simulations are encouraged as well as research analysis-type papers.

The most recent Impact Factor for Security and Communication Networks is 0.806 according to the 2015 Journal Citation Reports released by Thomson Reuters in 2016.

Content published prior to 2017 is hosted on the Wiley Online Library.

Security and Communication Networks currently has an acceptance rate of 17%. The average time between submission and final decision is 56 days and the average time between acceptance and publication is 44 days. 
Last updated by Dou Sun in 2020-12-19
Special Issues
Special Issue on Security Threats to Artificial Intelligence-Driven Wireless Communication Systems 2021
Submission Date: 2021-04-16

Due to the openness of wireless channels, wireless communication systems are extremely vulnerable to attacks, counterfeiting, and eavesdropping. With the widespread adoption of artificial intelligence (AI) technologies in fifth generation (5G) and beyond fifth generation (B5G) networks, AI-based attacks have emerged as new threats to wireless communication systems. Deep learning-based end-to-end communication systems are extremely susceptible to physical adversarial attacks which can cause a serious reduction in the accuracy of signal classification or radio modulation recognition. Intelligent threats can utilise AI to attack future networks, related services, and applications that use deep learning algorithms where small disturbances can be easily designed and generated by attackers. However, researchers still need to consider how best to protect 5G and B5G networks from AI-related attacks. Furthermore, defense strategies of adversarial attacks for future communication systems are still underdeveloped and inefficient. The aim of this Special Issue is to solicit original articles, as well as review articles, analysing the security threats, challenges, and mechanisms inherent in AI-driven wireless communication systems. Submissions discussing potential defense approaches, and strategies to combat intelligent attacks on such systems are particularly encouraged. Potential topics include but are not limited to the following: Architectures, simulators, scenarios, and applications tuned to security and privacy issues for AI-driven wireless communication systems Adversarial attacks on AI-based signal classification or radio modulation recognition White-box or black-box-based attacks on signal/modulation classifiers Effective attacks detection and prediction based on deep learning techniques, e.g. autoencoder (AE), deep neural network (DNN), generative adversarial network (GAN) and deep reinforcement learning (DRL) Defense mechanisms and theories of adversarial attacks against end-to-end communication systems Adversarial modelling or adversarial deep learning for future wireless networks Security threats to 5G and B5G-based applications, services and IoT devices Defense strategies and solutions for AI-related attacks on wireless communication systems Robust algorithms to protect against AI-related attacks on wireless communication systems
Last updated by Dou Sun in 2020-12-19
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