Robust Multivariate Anomaly-Based Intrusion Detection System for Cyber-Physical Systems

2021 ◽  
pp. 86-93
Author(s):  
Aneet Kumar Dutta ◽  
Rohit Negi ◽  
Sandeep Kumar Shukla
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Cyber Physical Systems ◽  
Physical Systems

scholarly journals A Self-Adaptive and Self-Learning Methodology for Wireless Intrusion Detection using Deep Neural Network

2021 ◽  
Vol 12 (6) ◽  
pp. 2084-2094
Author(s):  
R. Sathya Et al.
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Cyber Physical Systems ◽  
Cyber Attacks ◽  
Detection Mechanism ◽  
Vast Number ◽  
Physical Systems ◽  
Computation Process ◽  
Self Learning

Cyber physical systems combine both the physical as well as the computation process. Embedded computers and systems monitor to control the physical forms with feedback loops which have an effect on computations and contrariwise. A vast number of failures and cyber-attacks are present in the cyber physical systems, which leads to a limited growth and accuracy in the intrusion detection system and thus implementing the suitable actions which may be taken to reduce the damage to the system. As Cyber-physical systems square measure but to be made public universally, the applying of the instruction detection mechanism remains open presently. As a result, the inconvenience is made to talk about the way to suitably apply the interruption location component to Cyber physical frameworks amid this paper. By analysing the unmistakable properties of Cyber-physical frameworks, it extraordinary to diagram the exact necessities 1st. At that point, the arranging characterize of the intrusion discovery component in Cyber-physical frameworks is introduced in terms of the layers of framework and particular location procedures. At long last, a few imperative investigation issues unit known for edifying the following considers.

Classification with Clustering and Gaussian Functions in Intrusion Detection System

2014 ◽  
Vol 134 (12) ◽  
pp. 1908-1915 ◽  
Author(s):  
Nannan Lu ◽  
Shingo Mabu ◽  
Yuhong Li ◽  
Kotaro Hirasawa
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Gaussian Functions

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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