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Call for Special Issue: Navigating Fairness in the Convergence of Cybersecurity and Generative AI (NFCCG-AI)

2024-03-02

This special issue thoroughly investigates the intersection of cybersecurity and generative artificial intelligence (AI), exploring the complex relationship between these fields and highlighting the importance of fairness.

  1. Ethically-minded advancements in adversarial techniques:

   - Conventional approaches: As cybersecurity deals with weaknesses, the integration of generative AI, namely via Generative Adversarial Networks (GANs), brings forward new ethical concerns. Adversarial assaults now use Generative Adversarial Networks (GANs) to create highly misleading counterfeit data, which poses a significant challenge to conventional security measures and emphasises the need of ethical concerns in AI-based defence systems.

   - The ethical implications of the evolution of cyber threats include malicious individuals using Generative Adversarial Networks (GANs) to produce convincing phishing materials, imitate genuine login interfaces, and construct advanced malware. This prompts us to consider ethical considerations. The conventional cybersecurity toolbox encounters ethical dilemmas while identifying and combating these emergent threats.

 

  1. Strengthening Defenses with Fairness in Focus:

- Sophisticated Threat Environment: In an unexpected turn, generative AI emerges as a tool to enhance cybersecurity defences, setting higher standards for fairness. AI-powered systems demonstrate exceptional proficiency in analysing information, recognising trends, and finding irregularities, all while prioritising fairness in algorithmic decision-making. This signifies a proactive stance towards cybersecurity that prioritises justice as its fundamental principle.

   - Equitable Anomaly Identification: GANs enhance fairness by producing artificial data that captures several facets of typical system functioning. By incorporating a well-proportioned combination of genuine and artificially generated data into the training process of security systems, the improvement of intrusion detection techniques is accompanied by the integration of fairness as a fundamental aspect.

 

  1. Examining the Fairness Implications of Biometric Security Challenges:

   The user did not provide any text. Principles of Facial Recognition: The convergence of generative artificial intelligence (AI) with biometric security, specifically in the context of using face recognition for identification, presents novel obstacles when considering the concept of fairness. The advent of lifelike deepfake photos gives rise to problems of fair accessibility and impartial verification. Ensuring the inclusion of biometric systems necessitates prioritising fairness in innovations.

 

  1. Dimensions pertaining to ethics, privacy, and fairness:

   - Implications for privacy: The incorporation of generative AI into cybersecurity raises privacy issues, underscoring the need of equitable data management. Achieving a fair balance between implementing effective security measures and respecting user privacy is of utmost importance.

   - Fair and Ethical Imperatives: In addition to ethical issues, it is crucial to prioritise fairness while using generative AI in cybersecurity. Measures to prevent abuse must be in line with ideals of justice in order to build confidence in these developing technologies.

 

This special issue highlights the merging of generative AI with cybersecurity, with a particular focus on the importance of fairness. The ethical concerns, competitive developments, and protective tactics in this field are examined from the perspective of fairness, emphasising the need for fair, impartial, and inclusive methods to navigate the changing world of cyber risks and AI progress. Continued cooperation between the cybersecurity and AI groups is crucial for promoting equity in technical advancement.

This special issue is handled is handled by:

  1. Guest Editor: Assist.Prof.Dr.Mohd Arfian Ismail, Faculty of Computing, College of Computing and Applied Sciences, Universiti Malaysia Pahang, Malaysia

Email: arfian@ump.edu.my

  1. Assist.Prof.Dr. Mohammad Aljanabi

Email: mohammad.aljanabi@aliraqia.edu.iq

Department of Computer, College of Education, Al-Iraqia University, IRAQ

 

  1. Guest Editor: Dr.Mohammed A. Fadhel

            Email: m.fadhel@uos.edu.iq

            College of Computer Science & Information Technology, University of Sumer, IRAQ

Vol. 2024

Issue in Progress 

 

Published: 2024-02-28

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