AIAS project together with other EU-funded research projects NITRO (DIGITAL, GA no: 101145872) RESCALE (HORIZON, GA no: 101120962) ERATOSTHENES (H2020, GA no: 101020416) CYBERUNITY (DIGITAL, GA no: 101128024) CHRISS (HORIZON, GA no: 101082440) ENTRUST (HORIZON, GAS no: 101095634) aerOS (HORIZON, GA no: 101069732) COBALT (HORIZON, GA no: 101119602) CyberSuite (DIGITAL, GA no: 101145861) FAME (HORIZON, GA no: 101092639) OASSES (HORIZON, GA no: 101092702) ODEON (HORIZON, GA no: 101136128) SAFE-6G (HORIZON, GA no: 101139031) SOVEREIGN (HORIZON, GA no: 101131481) TRUSTEE (HORIZON, GA no: 101070214) co-organize the 4th International Workshop on Advances on Privacy Preserving Technologies and Solutions (IWAPS) to be held in conjunction with the 19th International Conference on Availability, Reliability and Security (ARES).
The availability of massive amounts of data, coupled with high-performance cloud computing platforms, has driven significant progress in ML (ML) and artificial Intelligence (AI) and optimization applications. At the same time, it has increased exponentially the fertile threat landscape for cyber-attacks, skyrocketing the cyber risk of involved industries and impacting several areas, including computer vision, natural language processing, transportation, trust computing, identity management and psychological manipulation.
This workshop aims to strengthen security and privacy through research and relevant activities for the design of secure, privacy-preserving and trust architectures, investments in cyber-defense, data analyses, fusion platforms, protocols, algorithms, services, and applications for next generation systems and solutions. Security and privacy solutions employing innovative ML techniques are especially encouraged, to tackle the issues of large data volume inspection, cyberattacks, as well as theoretical and practical challenges for IoT platforms, particularly oriented to the design of privacy-preserving AI systems and algorithms. Moreover, such privacy-preserving AI systems and algorithms should have strong multidisciplinary components, including soliciting contributions about policy, legal issues, and societal impact of privacy and affect the cyber risk of the participating entities.
The 2024 IWAPS will bring together researchers, engineers, and practitioners for presenting and discussing the latest advances and innovations in theories, infrastructure, schemes, and applications for secure computation, privacy technologies, security economics, human computer interaction, as well as to identify emerging research topics and define the future trends.
Authors are invited to submit novel and unpublished work describing research or experience in all areas of privacy preserving and security technologies and solutions. A variety of research methods, including both qualitative and quantitative approaches will be considered within the scope of the workshop. Submitted papers will be judged based on their scientific quality, and contribution to the field.
Important Dates
Submission Deadline Apr 30, 2024
Author Notification May 17, 2024
Proceedings Version Jun 18, 2024
Conference Jul 30 — Aug 02, 2024 in Vienna, Austria
Topics of interest include, but are not limited to
- Economic Implications of Adversarial AI
- Ethical Considerations in Adversarial AI
- Architectures and protocols for scalable, secure, robust and privacy enhancing technologies
- Cryptographic approaches for security and privacy
- Threat and attack models in IoT
- End-to-end system security models for IoT
- ML for security and privacy in privacy preserving technologies
- ML technique for deep packet inspection
- Privacy-preserving and machine-learning-based data analytics
- ML technique to predict psychological manipulation
- Game Theoretic approach to predict attacking paths
- Privacy preserving security/privacy policies
- Applications of privacy-preserving AI systems
- Differential privacy: theory and applications
- Human rights and privacy
- Privacy policies and legal issues
- Privacy preserving test cases and benchmarks
- Security economics
- AI/ML techniques in Cyber Threat Intelligence
- Weakest link in Cybersecurity
- ML in automated software testing
- Human Factors in Adversarial AI
- Adversarial AI in Cybersecurity
- Ethical, psychological, sociological, or anthropological aspects of usable security and privacy
- Trust frameworks and management models for IoT systems
- Intrusion and malware detection for IoT systems
- Deep Learning and privacy preserving
- Protection solutions against adversarial ML attacks
- ML to analyze cryptographic protocols
- Analysis of mitigations and automating
- ML in predicting the weakest link in an architecture
- Privacy enhancing and anonymization techniques
- Privacy preserving technologies/solutions for IoT systems
- Attacks on data privacy
- Distributed privacy-preserving algorithms
- Security controls and budget allocation
- Privacy preserving optimization and ML
- Surveillance and societal issues
- Investments in cyber-defense
- Human firewall
- Security and privacy frameworks
- Cybersecurity risk management
Workshop chairs:
Christos Xenakis, University of Piraeus, Greece xenakis@unipi.gr
Aristeidis Farao, InQbit Innovation SRL, Romania aris.farao@inqbit.io
Technical Program Committee Chairs
Alexios Lekidis, University of Thessaly, Greece alekidis@uth.gr
Apostolis Zarras, Foundation for Research and Technology, Greece zarras@ics.forth.gr
Ilias Politis, ATHENA Research Centre, Greece ilpolitis@isi.gr
Chistoforos Dadoyan, Ionian University, Greece dadoyan@ionio.gr
Dissemination Chairs
Aggeliki Panou, University of Piraeus, Greece apanou@unipi.gr
Raisia Gorbunov, InQbit Innovation SRL, Romania raisia.gorbunov@inqbit.io