The Dark Side of AI: Privacy Invasions and Data Vulnerabilities (DSAI-PIDV 2025)

The DSAI-PIDV 2025 book aims to explore the risks and challenges posed by AI in terms of privacy invasions and data security vulnerabilities. This will serve as a platform for researchers, practitioners, and industry experts to discuss state-of-the-art methodologies, legal frameworks, and technological safeguards to address AI-related privacy concerns. The book will bring together cutting-edge research and real-world applications to assess the impact of AI-driven surveillance, data breaches, and privacy risks across multiple domains.

Submission Guidelines

Authors are invited to contribute original research, case studies, and review articles that align with the themes of the book. All submissions should adhere to the following guidelines:

• Full-length chapter: Maximum 12 pages (including abstract and references)

• Papers should be formatted according to the CRC Press (Taylor & Francis) template. https://www.routledge.com/rsc/downloads/Manuscript_preparation_guide.pdf?

• Submissions must be original and not published elsewhere.

• Papers must be submitted in PDF format.

List of Topics

• Evolution of privacy challenges in the AI era

• Role of AI in data mining and profiling

• Ethical implications of personal data collection

• Exploitation of AI vulnerabilities by adversaries

• Impacts of AI-powered surveillance systems

• Privacy concerns with facial recognition technologies

• Risks of data breaches in AI-driven medical systems

• Balancing AI innovation with patient privacy

• AI’s role in enhancing and threatening cybersecurity

• Cyber-attacks exploiting AI weaknesses

• Global policies for AI and privacy

• Legal frameworks for data protection in AI systems

• Designing AI systems with privacy by design principles

• Transparency and accountability in AI algorithms

• AI’s role in targeted advertising and user profiling

• Risks of privacy invasions on social platforms

• Innovations in privacy-preserving AI technologies

• Role of federated learning in secure AI systems

• Tools and techniques for ensuring secure AI operations

Publication Details

The book will be published by CRC Press, Taylor & Francis Group, ensuring high visibility and indexing in major databases.

Important Dates

• 30th April 2025 – Abstract Submission Deadline

• 15th May 2025 – Acceptance Notification

• 31st May 2025 – Full-Chapter Submission

• 15th June 2025 – T&F and Author Agreement

• 30th June 2025 – Final Submission to T&F

Contact

All questions about submissions should be emailed to bookchapters2k@gmail.com