International Workshop on Security and Privacy Enhancing Technologies for Visual Data

to be held in conjunction with the 19th International Conference on Availability, Reliability and Security

July 30 – August 02, 2024

Visual data, such as images, videos, and 3D models, have a significant impact on our daily lives. It is increasingly captured for purposes such as safety, tracking movements, monitoring activities, diagnosing diseases, and behaviour prediction in smart systems (homes, healthcare, transportation, etc.). From casual snapshots to complex satellite images, visual information can reveal personal or sensitive information, including facial recognition, license plates, address/locations of landmarks, disease type, and sensitive documents, which can be exploited by malicious actors. Furthermore, the increasing sophistication of Artificial Intelligence (AI) based recognition technologies raises privacy concerns. Conventional automated intelligent systems do not promise privacy or personal data security. Visual data protection requires a multifaceted approach involving technological solutions, strong legal frameworks, ethical practices, transparency, accountability, and individual awareness. Therefore, privacy protection, along with secured data retention and delivery is the biggest challenge in the design and deployment of intelligent and reliable visual analytics systems.
SPETVid workshop aims to connect visual data security and privacy, exploring advanced cryptographic methods, visual obfuscation, PETs, anonymization, pseudonymization, privacy-preserving analysis, machine learning, blockchain, data minimization, summarization, synthetic/generative data, and emerging technologies that will shape visual data privacy and security.
SPETViD workshop bridges academia, practitioners, law enforcement, and industry for secure and privacy-preserving visual data research. It seeks theoretical, conceptual, and experimental contributions to visual data security and privacy, enabling participants to exchange and discuss the latest findings and solutions.

Topics of interest include, but are not limited to

Authentication of visual data (authentication algorithms, PKI and hashing)
Blockchain technology for Visual Chain-of-Evidence / Tamper-proof visual data
Computer vision for visual privacy
Cryptography and steganography techniques for visual data
Emerging threats and vulnerabilities on visual data (Deepfakes, Zero-day attacks on visual recognition systems, and data poisoning techniques)
Ethical processing of Visual data
Federated and Distributed Analytics
Generative / Synthetic Data Generation Techniques / Generative AI Media
Global and European Policy and Regulatory Frameworks (e.g., GDPR)
Image processing and Machine Learning for tampering detection techniques
Image processing for privacy protection
Implications of GDPR on visual information
Laws affecting visual surveillance in public and private places
Machine learning in distributed imaginary systems
Object detection for security applications

Privacy-preserved tracking and activity recognition
Privacy-enhancing visual data management
Privacy-preserving AI and Machine Learning (including Explainable AI (XAI))
Privacy-preserving technologies for visual data
Pseudonymization and anonymization Techniques
Safeguarding visual data With Differential Privacy
Secure analysis and retrieval of visual data
Secure Multimedia Internet of Things (MIoT)
Secure visual data pipelines and storage techniques
Secure and Verifiable Computation on Encrypted Data
Standardization and Interoperability
Summarization, data minimization, and annotation for visual data
Threat modelling for Visual Data
Video redaction/obfuscation Techniques
Visual data enchantment (manipulation/tempering/video quality) techniques

Important Dates

Submission Deadline May 7, 2024
Author Notification May 27, 2024
Proceedings Version June 18, 2024
ARES Conference July 30 – August 02, 2024

Workshop Chairs

Mamoona Asghar
University of Galway, Ireland

Amna Shifa
University of Galway, Ireland

Nadia Kanwal
Keele University, UK

Program Committee

Asra Aslam, University of Leeds, UK
Gazi Erkan Bostanci, Ankara University, Turkey
Ihsan Ullah, University of Galway, Ireland
Martin Fleury, University of Essex, UK
Malika Bendechache, University of Galway, Ireland
Muhammad Babar Imtiaz, Technological University of the Shannon, Ireland
Muhammad Samar Ansari, University of Chester, UK
Rónán Kennedy, University of Galway, Ireland
Saeed Alsamhi, Insight, Data Science Institute, Ireland
Shoaib Ehsan, University of Southampton, UK
Zafar Shahid, Meta, US


The submission guidelines valid for the workshop are the same as for the ARES conference. They can be found at https://www.ares-conference.eu/conference/submission/.