Evolutionary Computing for AI-Driven Security and Privacy: Advancing the state-of-the-art applications
EvoCompAISecurity&Privacy 2022
- URL: https://www.journals.elsevier.com/intelligent-systems-with-applications/call-for-papers/evolutionary-computing-for-ai-driven-security-and-privacy-advancing-the-state-of-the-art-app
- Event Date: ~
- Submission Date: 2023-01-01
Advent of Artificial Intelligence (AI)-enabled cyber threats may result in increased data theft, virus spread, and network penetration. This leads to a problem of protecting against AI-driven attacks.
Scope
The advent of Artificial Intelligence (AI)-enabled cyber threats may result in increased data theft, virus spread, and network penetration. This leads to a problem of protecting against AI-driven attacks. As a result, AI-driven technologies require a training process, raising new concerns about the security of trained algorithms. We require scalable, resilient, and efficient network security systems to protect the broad cyber-infrastructure. These systems must be able to make smart decisions to detect a wide range of cyberattacks. Evolutionary computing (EC) methods appear to be a promising way to improve cybersecurity, and have been frequently employed in AI-driven security and privacy systems. EC methods are inspired by the biological immune system, which is a strongly distributive adaptive defense system. Unlike other computational problems, the design of intelligent cybersecurity solutions through EC techniques must be resistant to determined attackers who can target any responsive cyber-physical device. Cyber Intelligence should be able to ensure that everybody emerges through our cyber-connected world. Combining EC and Cybersecurity will ensure that our connected future is secure, stable, and prosperous. The primary purpose is to cover both the theoretical and applications of several EC algorithms and their advanced variants to address cybersecurity issues. It intends to present a rational platform for researchers and scientists in academia and engineers to present their most recent research results in EC techniques to recognize potential AI-driven security and privacy issues.
Topics of interest include but are not limited to:
EC based optimization for privacy and security.
Feature selection and feature fusion using EC for network intrusion detection
Swarm Intelligence and EC techniques for spam and botnet attack detection.
Hybridization of Swarm Intelligence and EC techniques for fraud-detection systems.
Brain-inspired Computation for biometric recognition: security and privacy concerns.
Random Search Technique with differential privacy
Hybridization of Swarm Intelligence and EC techniques for crime analysis.
Cybersecurity in robotics using memetic transmission
Self-adaptive memetic schemes for biometric recognition: security and privacy concerns.
Securing Wireless Sensor Networks (WSNs) using evolutionary game theory.
Genetic programming for smart house security system.
Cybersecurity in healthcare systems using swarm and nature inspired optimizers.
Cybersecurity in agriculture using swarm and nature inspired optimizers.
Cybersecurity in IoT and WSNs using swarm and nature inspired optimizers.
Manuscript submission information:
Submission Instructions:
You are invited to submit your manuscript at any time before the submission deadline. For any inquiries about the appropriateness of contribution topics, please contact Prof. Robertas Damaševičius via robertas.damasevicius@polsl.pl.
The journal’s submission platform (Editorial Manager®) is now available for receiving submissions to this Special Issue. Please refer to the Guide for Authors to prepare your manuscript, and select the article type of “EvoCompAISecurity&Privacy” when submitting your manuscript online. Both the Guide for Authors and the submission portal could be found on the Journal Homepage here: https://www.journals.elsevier.com/intelligent-systems-with-applications
Timeline:
Submission open: December 1, 2021
Submission deadline: January 1, 2023
Notification June 15, 2023
Keywords:
- Artificial Intelligence;
- Evolutionary Computing;
- Nature-inspired optimisation;
- Swarm Intelligence;
- Metaheuristics;
- Cybersecurity
Guest Editors:
Prof. Dr. Robertas Damaševičius, Faculty of Applied Mathematics, Silesian University of Technology, Gliwice, Poland
Prof. Dr. Chi-Hua Chen, College of Mathematics and Computer Science, Fuzhou University, Fuzhou City, China
Dr. Hafiz Tayyab Rauf, Centre for Smart Systems, AI and Cybersecurity, Staffordshire University, Stoke-on-Trent, United Kingdom
Scope
The advent of Artificial Intelligence (AI)-enabled cyber threats may result in increased data theft, virus spread, and network penetration. This leads to a problem of protecting against AI-driven attacks. As a result, AI-driven technologies require a training process, raising new concerns about the security of trained algorithms. We require scalable, resilient, and efficient network security systems to protect the broad cyber-infrastructure. These systems must be able to make smart decisions to detect a wide range of cyberattacks. Evolutionary computing (EC) methods appear to be a promising way to improve cybersecurity, and have been frequently employed in AI-driven security and privacy systems. EC methods are inspired by the biological immune system, which is a strongly distributive adaptive defense system. Unlike other computational problems, the design of intelligent cybersecurity solutions through EC techniques must be resistant to determined attackers who can target any responsive cyber-physical device. Cyber Intelligence should be able to ensure that everybody emerges through our cyber-connected world. Combining EC and Cybersecurity will ensure that our connected future is secure, stable, and prosperous. The primary purpose is to cover both the theoretical and applications of several EC algorithms and their advanced variants to address cybersecurity issues. It intends to present a rational platform for researchers and scientists in academia and engineers to present their most recent research results in EC techniques to recognize potential AI-driven security and privacy issues.
Topics of interest include but are not limited to:
EC based optimization for privacy and security.
Feature selection and feature fusion using EC for network intrusion detection
Swarm Intelligence and EC techniques for spam and botnet attack detection.
Hybridization of Swarm Intelligence and EC techniques for fraud-detection systems.
Brain-inspired Computation for biometric recognition: security and privacy concerns.
Random Search Technique with differential privacy
Hybridization of Swarm Intelligence and EC techniques for crime analysis.
Cybersecurity in robotics using memetic transmission
Self-adaptive memetic schemes for biometric recognition: security and privacy concerns.
Securing Wireless Sensor Networks (WSNs) using evolutionary game theory.
Genetic programming for smart house security system.
Cybersecurity in healthcare systems using swarm and nature inspired optimizers.
Cybersecurity in agriculture using swarm and nature inspired optimizers.
Cybersecurity in IoT and WSNs using swarm and nature inspired optimizers.
Manuscript submission information:
Submission Instructions:
You are invited to submit your manuscript at any time before the submission deadline. For any inquiries about the appropriateness of contribution topics, please contact Prof. Robertas Damaševičius via robertas.damasevicius@polsl.pl.
The journal’s submission platform (Editorial Manager®) is now available for receiving submissions to this Special Issue. Please refer to the Guide for Authors to prepare your manuscript, and select the article type of “EvoCompAISecurity&Privacy” when submitting your manuscript online. Both the Guide for Authors and the submission portal could be found on the Journal Homepage here: https://www.journals.elsevier.com/intelligent-systems-with-applications
Timeline:
Submission open: December 1, 2021
Submission deadline: January 1, 2023
Notification June 15, 2023
Keywords:
- Artificial Intelligence;
- Evolutionary Computing;
- Nature-inspired optimisation;
- Swarm Intelligence;
- Metaheuristics;
- Cybersecurity
Guest Editors:
Prof. Dr. Robertas Damaševičius, Faculty of Applied Mathematics, Silesian University of Technology, Gliwice, Poland
Prof. Dr. Chi-Hua Chen, College of Mathematics and Computer Science, Fuzhou University, Fuzhou City, China
Dr. Hafiz Tayyab Rauf, Centre for Smart Systems, AI and Cybersecurity, Staffordshire University, Stoke-on-Trent, United Kingdom
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