13th International Symposium on Intelligent Distributed Computing
IDC 2019
7-9 October 2019, Saint-Petersburg, Russia

 

Security for Intelligent Distributed Computing (IDC) - Machine Learning (ML) vs. Chains of Trust (CoT) – (SIDCMLCoT)

 

 

Topics of interest:

 

  • Мachine learning for IDC
  • Tustworthy platforms and gateways for IDC
  • Application of ML and CoT for safety and security in IoT and CPS
  • Application of ML and CoT for safety and security in the Internet of Vehicles
  • Bio/Nature-inspired self-protecting IDC
  • Evolutionary safety and security in IDC
  • Formal methods to measure and prove security in IDC
  • Interdisciplinary (e.g. legal) challenges for security in IDC
  • Network security in IDC

 


Call for papers:

Modern IT systems depend increasingly on the results of dynamically distributed computing tasks in IDC. Each involved device plays a crucial role for the security and safety of the overall system.

Not only may these devices be widely distributed and belong to different stakeholders, but they may be in the hands of a potential adversary. In order to address these arising challenges, it is necessary to reliably assess the identity and integrity of each involved entity and to provide strong means for data secrecy and privacy. The possible solutions range from hardware-based trust anchors such as Trusted Platform Modules (TPM) and Device Identity Composition Engines (DICE) through to system isolation mechanisms and the design and integration of trustworthy applications and protocols. Additionally, novel autonomous IDC systems have to learn by themselves and adapt their behavior to new situations and new insights during the operational phase. Security systems for detecting and mitigating the effects of attacks also need to learn and adapt. In the long-term, IT security has to cope with high/full automation. For example, fully autonomous driving also requires fully automated countermeasures in the event of attacks. It is expected that autonomous driving will be based on AI technologies such as image recognition of the environment and surrounding traffic. Machine Learning (ML) methods such as OCSVM, SVM, Neural Networks, LSTM or Process Mining can also be applied to IDC for the purpose of security measuring and decision on countermeasures. Such AI systems must be designed robustly against attackers and transparent for users. Thus, "Security by Design" for AI needs new guidelines, resulting in interdisciplinary challenges. This Special Session on "Security for Intelligent Distributed Computing" aims to bring together researchers and practitioners handling techniques, algorithms, protocols and interdisciplinary aspects for use of Machine Learning for IDC Security as well as platforms and Chains of Trust (CoT) for IDC. Let us exchange ideas and results of the latest developments in these important fields.

 

Submissions and reviews will be handled via EasyChair system: https://easychair.org/conferences/?conf=idc2019

 

 

Important dates:

 

Full paper submission: A̶p̶r̶i̶l̶ ̶9̶t̶h,  ̶A̶p̶r̶i̶l̶ ̶2̶3̶r̶d̶, May 6th 2019 (final extension!)

Notification of acceptance: ̶M̶a̶y̶ ̶3̶1̶s̶t̶, ̶J̶u̶n̶e̶ ̶7̶t̶h̶, June 11, 2019

Final (camera ready) paper submission: ̶J̶u̶n̶e̶ ̶4̶t̶h̶, ̶J̶u̶n̶e̶ ̶1̶7̶t̶h̶, June 19, 2019

Registration for authors: June 20, 2019

Special session date: October 7th/8th/9th, 2019

 

 

Program chairs:

 

 

 

Technical Program Committee (to be confirmed):

 

 

Laboratory of Computer Security Problems

St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS)

Saint Petersburg National Research University of Information Technologies, Mechanics and Optics  (ITMO University)

Monomax PCO

Prof. Igor Kotenko

Russia, 199178, St. Petersburg., No. 39, 14-th Linia, VI

Phone / Fax:   +7-812-328-71-81 / +7-812-328-44-50

E-mail: idc2019@comsec.spb.ru