1st international workshop on Artificial Intelligence and Industrial Internet-of-Things Security (AIoTS)
2019-06-05 ~ 2019-06-07
In recent years, Artificial Intelligence (AI) has got a lot of attention, especially, for the success of deep learning to address problems that were considered hard before. Big players such as Google, Amazon and Baidu are exploring the application of AI in different markets like healthcare, FinTech and autonomous vehicles. Along with AI, other technologies such Internet-of-Things (IoT) have boosted other areas like the case of Industry 4.0, where through the adoption of Industrial-IoT into the production chain companies want to have a smarter manufacture that can be adapted to their customers’ needs.
The accelerating adoption of new technologies brings new challenges especially associated with the cybersecurity of the applications, where confidentiality, integrity and availability of data are important but also safety properties since applications interact physically with people or other assets. The intersection of AI and cybersecurity can be seen as a two-fold relationship. In one side AI techniques can be adopted to improve the state-of-the-art of security solutions, while on the other side, cybersecurity can contribute to improving the study of the security of AI algorithms through the exploration of adversarial machine learning.
This workshop aims to open a space where new research ideas from different areas converge into the intersection of AI, IoT, Cyber-Physical Systems (CPS) and cybersecurity. We encourage researchers in the fields of AI, embedded systems, CPS and cybersecurity to take the opportunity to use this workshop for sharing their work and open the discussion of new ideas in this always-evolving topic.
Topics of Interest
Adversarial Machine Learning
AI applications in Detection, Prevention and Response of Cyber Attacks
Cyber-Physical Systems Security
Applications of Formal Methods to IoT Security
Applications of Blockchain to IoT
Critical Infrastructure Security
Intrusion Detection Powered by AI
Privacy-Preserving Machine Learning
Security of Industrial IoT
Instructions for authors:
Submissions must not substantially duplicate work that any of the authors has published elsewhere or has submitted in parallel to any other venue with formally published proceedings. Information about submissions may be shared with program chairs of other conferences for that purpose. Submissions must be anonymous, with no author names, affiliations, acknowledgement or obvious references. Each submission must begin with a title, short abstract, and a list of keywords. The introduction should summarise the contributions of the paper at a level appropriate for a non-specialist reader. All submissions must follow the original LNCS format (see http://www.springeronline.com/lncs) with a page limit of 18 pages (incl. references) for the main part (reviewers are not required to read beyond this limit) and 30 pages in total. Authors of accepted papers must guarantee that their paper will be presented at the conference and must make a full version of their paper available online. Any paper co-authored by at least one full-time student who will present the paper at the conference is eligible for the best student paper award (the eligibility will be clarified with authors of accepted papers following the notification) . Submissions not meeting the submission guidelines risk rejection without consideration of their merits. It is strongly encouraged that submissions be processed in LaTeX.
The accepted papers will have post-proceedings published by Springer.
Robert Deng, Singapore Management University
Sandra Rueda, Universidad de los Andes