Advances in Artificial Intelligence (AI), mobile and Internet technologies have been progressively reshaping our lives over the past few years. The applications of IoT and cyber-physical systems touch today almost all aspects of our daily lives including healthcare (e.g., remote patient monitoring environments), leisure (e.g., smart entertainment spaces), and work (e.g., smart manufacturing, asset management). For many of us, social media has become the rule rather than the exception as the way to interact, socialize and exchange information. AI powered systems have become a reality and started to affect our lives in important ways. These systems and services collect huge amounts of data about us and exploit it for various purposes that could affect positively and negatively our lives. Even though most of these systems employ data and privacy protection mechanisms, data misuse incidents keep making the headlines (e.g., the case of Facebook-Cambridge Analytica).

In this new digital world, privacy of end users is becoming a fundamental aspect to consider when the system / service / software is designed, implemented and operationalized. The user should be supported to understand how their data is collected, processed, analyzed, stored, accessed and kept safe. They should also be able to exert their fundamental rights (as specified in applicable data protection lows e.g., GDPR, CCPA) such as controlling what is collected about them, when and where, for what purposes collected data can be exploited and the right to be forgotten. The users should also be provided with a transparent view into the system to verify, at any point of time, how their data is processed and exploited. 

The goal of this workshop is to collect recent advances, innovations and practices in data and knowledge engineering for building security and privacy protection systems, techniques and solutions that provide effective data and privacy protection for users and contribute to increase their trust in the cyberspace. The topics of interest include, but are not limited to:

• Privacy in data analytics;
• Data and knowledge driven privacy protection;
• Privacy in Big Data frameworks and architectures;
• Privacy and data protection in cyber-physical-social systems;
• Privacy and data protection in IoT;
• Decision support for informed data sharing;
• Automated recognition of novel privacy threats
• Data mining and machine learning for data security and privacy;
• Data mining and machine learning for cybersecurity;
• Privacy aware recommendation systems;
• Privacy preserving data integration;
• Models and techniques for involving the user in controlling her data;
• User privacy and security requirements;
• Privacy and security threats introduced by the human behavior;
• Privacy by design for the cyberspace;
• Privacy risks assessment and visualization;
• Tunable and adaptive data obfuscation;
• Natural language for expressing data access/usage policy;
• Innovative models to acquire the user consent;
• Assistive technology to promote more secure behavior and awareness of users;
• Bringing transparency into the cyberspace;
• Models and techniques for engendering trust and transparency;

Deadline: August 24, 2020

Inclusion in Journal Special Issues: 

A selection of high quality papers will be invited to submit an extended version to special issues in Service Oriented Computing and Applications (SOCA), ACM Transactions on Data and Quality Information, and possibly Knowledge and Information Systems (KAIS).

Submission site

 

 

General Chairs

• Mahmoud Barhamgi, Claude Bernard Lyon 1 University ;
• Xiangliang Zhang, KAUST University, Saudi Arabia;
• Charith Perera, Cardiff University,United Kingdom;
• Chia-Mu Yu, National Chiao Tung University, Taiwan.

Programme Chairs

To be defined

• Prof Jin LI, Guangzhou University, China

To be defined

Participants

ICDM 2020：20th IEEE International Conference on Data Mining November 17-20, 2020, Sorrento, Italy