Journal Information
Journal of Network and Computer Applications
Impact Factor:

Call For Papers
The Journal of Network and Computer Applications welcomes research contributions, surveys and notes in all areas relating to computer networks and applications thereof. The following list of sample-topics is by no means to be understood as restricting contributions to the topics mentioned:

    new design techniques, interesting or novel applications, components or standards
    computer networks with tools such as WWW
    emerging standards for internet protocols
    Wireless networks
    Mobile Computing
    emerging computing models such as cloud computing, grid computing
    emerging network protocols such as sensor networks, delay tolerant networks, Internet of things
    applications of networked systems for remote collaboration and telemedicine
    applications of an educational, transactional and cooperational nature
    applications of security in computer and networks
Last updated by Dou Sun in 2018-07-23
Special Issues
Special Issue on AI-Driven Security and Privacy
Submission Date: 2020-01-01

Artificial Intelligence (AI) has started to deeply influence people’s daily lives. AI-driven security solutions have already found applications in next generation firewalls, automatic intrusion detection systems, encrypted traffic identification, malware detection, and so on. Researchers are now assisted by AI-driven solutions to optimize algorithm design and release cryptanalysis efforts. Also, automatic data protection solutions based on deep learning technology have recently started appearing in academia. Conversely, an individual’s privacy is becoming under great threat given AI-based cyberattacks. The rise of AI-enabled cyberattacks could cause an explosion of network penetration, personal data theft, and epidemic spread of intelligent computer viruses. This raises the concern to defend against AI-driven attacks. Subsequently, AI-driven technologies require a training process, introducing additional problems of protecting training data and algorithms. Many machine learning and deep learning models have shown to be vulnerable against well-designed adversarial input samples. Outsourcing data and algorithms for training requires integrity in the training stage. Furthermore, end user data privacy and learning models must be protected. Thus, privacy preservation of big data in AI is becoming a key issue in the field of cyber security. Topics of interest include (but are not limited to): •Applications of AI technologies in cyber security and privacy •Security-related big data capture, classification and analytics •Data mining and knowledge discovery for security •Intelligent systems for security and privacy •Theoretical studies on big data privacy and security •Privacy-preserving machine/deep learning and data mining •AI-driven attacks and mitigation methods
Last updated by Dou Sun in 2019-08-24
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