Building a Frame-Based Cyber Security Learning Game

2018 ◽  
pp. 32-41
Author(s):  
Yuh-Jye Wang ◽  
Shian-Shyong Tseng ◽  
Tsung-Yu Yang ◽  
Jui-Feng Weng
Keyword(s):  
Cyber Security ◽  
Learning Game

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

Influential individuals: Approach to modeling

2018 ◽  
pp. 114-131
Author(s):  
O. Yu. Bondarenko
Keyword(s):  
Social Interactions ◽  
Social Status ◽  
Experimental Approach ◽  
Expert Knowledge ◽  
Formal Models ◽  
Leader Influence ◽  
Learning Game ◽  
Game Theoretic ◽  
Asymmetric Interactions ◽  
Influential Individuals

his article explores theoretical and experimental approach to modeling social interactions. Communication and exchange of information with other people affect individual’s behavior in numerous areas. Generally, such influence is exerted by leaders, outstanding individuals who have a higher social status or expert knowledge. Social interactions are analyzed in the models of social learning, game theoretic models, conformity models, etc. However, there is a lack of formal models of asymmetric interactions. Such models could help elicit certain qualities characterizing higher social status and perception of status by other individuals, find the presence of leader influence and analyze its mechanism.

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

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.

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