Study on Cyber-Security for IoT Edge Utilizing Pattern Match Accelerator

2020 ◽  
Vol 140 (1) ◽  
pp. 15-28
Author(s):  
Masamori Kashiyama ◽  
Reo Kashiyama ◽  
Hiroto Seki ◽  
Hiroyuki Hosono
Keyword(s):  
Cyber Security ◽  
Pattern Match

Study on cyber‐security for IoT edge utilizing pattern match accelerator

2021 ◽  
Vol 214 (2) ◽  
Author(s):  
Masamori Kashiyama ◽  
Reo Kashiyama ◽  
Hiroto Seki ◽  
Hiroyuki Hosono
Keyword(s):  
Cyber Security ◽  
Pattern Match

Perspectives on the role of cognition in cyber security

2012 ◽  
Author(s):  
Michael McNeese ◽  
Nancy J. Cooke ◽  
Anita D'Amico ◽  
Mica R. Endsley ◽  
Cleotilde Gonzalez ◽  
...  
Keyword(s):  
Cyber Security

Towards Comprehensive Threat Modeling for Intelligent Vehicle Cyber Security

CICTP 2017 ◽  
2018 ◽  
Author(s):  
Haojie Ji ◽  
Guizhen Yu ◽  
Yunpeng Wang ◽  
Zhao Zhang ◽  
Hongmao Qin
Keyword(s):  
Cyber Security ◽  
Intelligent Vehicle ◽  
Threat Modeling

Security of Cyber-Physical Systems: A Generalized Algorithm for Intrusion Detection and Determining Security Robustness of Cyber Physical Systems using Logical Truth Tables

2013 ◽  
Vol 9 ◽  
Author(s):  
Curtis G. Northcutt
Keyword(s):  
Intrusion Detection ◽  
Cyber Security ◽  
Logical Truth ◽  
Cyber Physical Systems ◽  
Security Model ◽  
Security Measures ◽  
Physical Systems ◽  
Multiple Signal ◽  
Security Attack ◽  
Truth Tables

The recent proliferation of embedded cyber components in modern physical systems [1] has generated a variety of new security risks which threaten not only cyberspace, but our physical environment as well. Whereas earlier security threats resided primarily in cyberspace, the increasing marriage of digital technology with mechanical systems in cyber-physical systems (CPS), suggests the need for more advanced generalized CPS security measures. To address this problem, in this paper we consider the first step toward an improved security model: detecting the security attack. Using logical truth tables, we have developed a generalized algorithm for intrusion detection in CPS for systems which can be defined over discrete set of valued states. Additionally, a robustness algorithm is given which determines the level of security of a discrete-valued CPS against varying combinations of multiple signal alterations. These algorithms, when coupled with encryption keys which disallow multiple signal alteration, provide for a generalized security methodology for both cyber-security and cyber-physical systems.

Reports of the Workshops Held at the 2019 AAAI Conference on Artificial Intelligence

AI Magazine ◽  
2019 ◽  
Vol 40 (3) ◽  
pp. 67-78
Author(s):  
Guy Barash ◽  
Mauricio Castillo-Effen ◽  
Niyati Chhaya ◽  
Peter Clark ◽  
Huáscar Espinoza ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Cyber Security ◽  
Question Answering ◽  
Intent Recognition ◽  
Affective Content ◽  
Learning Plan ◽  
Dialog System ◽  
Affective Content Analysis ◽  
Games And Simulations

The workshop program of the Association for the Advancement of Artificial Intelligence’s 33rd Conference on Artificial Intelligence (AAAI-19) was held in Honolulu, Hawaii, on Sunday and Monday, January 27–28, 2019. There were fifteen workshops in the program: Affective Content Analysis: Modeling Affect-in-Action, Agile Robotics for Industrial Automation Competition, Artificial Intelligence for Cyber Security, Artificial Intelligence Safety, Dialog System Technology Challenge, Engineering Dependable and Secure Machine Learning Systems, Games and Simulations for Artificial Intelligence, Health Intelligence, Knowledge Extraction from Games, Network Interpretability for Deep Learning, Plan, Activity, and Intent Recognition, Reasoning and Learning for Human-Machine Dialogues, Reasoning for Complex Question Answering, Recommender Systems Meet Natural Language Processing, Reinforcement Learning in Games, and Reproducible AI. This report contains brief summaries of the all the workshops that were held.

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