scholarly journals Modeling Data Flows with Network Calculus in Cyber-Physical Systems: Enabling Feature Analysis for Anomaly Detection Applications

Information ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 255
Author(s):  
Nicholas Jacobs ◽  
Shamina Hossain-McKenzie ◽  
Adam Summers
Keyword(s):  
Intrusion Detection ◽  
Anomaly Detection ◽  
Communication Networks ◽  
Physical System ◽  
Situational Awareness ◽  
Cyber Physical Systems ◽  
Network Calculus ◽  
Support Functions ◽  
Physical Systems ◽  
Data Flows

The electric grid is becoming increasingly cyber-physical with the addition of smart technologies, new communication interfaces, and automated grid-support functions. Because of this, it is no longer sufficient to only study the physical system dynamics, but the cyber system must also be monitored as well to examine cyber-physical interactions and effects on the overall system. To address this gap for both operational and security needs, cyber-physical situational awareness is needed to monitor the system to detect any faults or malicious activity. Techniques and models to understand the physical system (the power system operation) exist, but methods to study the cyber system are needed, which can assist in understanding how the network traffic and changes to network conditions affect applications such as data analysis, intrusion detection systems (IDS), and anomaly detection. In this paper, we examine and develop models of data flows in communication networks of cyber-physical systems (CPSs) and explore how network calculus can be utilized to develop those models for CPSs, with a focus on anomaly and intrusion detection. This provides a foundation for methods to examine how changes to behavior in the CPS can be modeled and for investigating cyber effects in CPSs in anomaly detection applications.

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.

scholarly journals Many-Objective Optimization for Anomaly Detection on Multi-Layer Complex Interaction Networks

2021 ◽  
Vol 11 (9) ◽  
pp. 4005
Author(s):  
Asep Maulana ◽  
Martin Atzmueller
Keyword(s):  
Anomaly Detection ◽  
Complex Networks ◽  
Pareto Front ◽  
Scoring Function ◽  
Cyber Physical Systems ◽  
Complex Interaction ◽  
Interaction Networks ◽  
Physical Systems ◽  
Human Interactions ◽  
Different Levels

Anomaly detection in complex networks is an important and challenging task in many application domains. Examples include analysis and sensemaking in human interactions, e.g., in (social) interaction networks, as well as the analysis of the behavior of complex technical and cyber-physical systems such as suspicious transactions/behavior in financial or routing networks; here, behavior and/or interactions typically also occur on different levels and layers. In this paper, we focus on detecting anomalies in such complex networks. In particular, we focus on multi-layer complex networks, where we consider the problem of finding sets of anomalous nodes for group anomaly detection. Our presented method is based on centrality-based many-objective optimization on multi-layer networks. Starting from the Pareto Front obtained via many-objective optimization, we rank anomaly candidates using the centrality information on all layers. This ranking is formalized via a scoring function, which estimates relative deviations of the node centralities, considering the density of the network and its respective layers. In a human-centered approach, anomalous sets of nodes can then be identified. A key feature of this approach is its interpretability and explainability, since we can directly assess anomalous nodes in the context of the network topology. We evaluate the proposed method using different datasets, including both synthetic as well as real-world network data. Our results demonstrate the efficacy of the presented approach.

scholarly journals OPEN-SCIENCE SPACE ISSUE: CALIBRATION OF MEASURING CHANNELS OF NON-DISMANTLING CYBER-PHYSICAL SYSTEMS

2021 ◽  
Vol 82 (3) ◽  
pp. 12-17
Author(s):  
Bohdan Stadnyk ◽  
◽  
Vasyl Yatsuk ◽  
Mykola Mykyjchuk ◽  
Svyatoslav Yatsyshyn ◽  
...  
Keyword(s):  
Physical System ◽  
Open Science ◽  
Cyber Physical Systems ◽  
Metrological Characteristics ◽  
Cyber Physical System ◽  
Cyberphysical Systems ◽  
Time Code ◽  
Efficient Operation ◽  
Physical Systems ◽  
Physical Quantities

The analysis of the concept of Open-Science Space is carried out. The existence of ways to achieve reproducibility and traceability of research results performed by a group of worldwide situated Cyber-physical system operators/supervisors is shown. Ways to ensure the efficient operation of Cyber-physical systems as complex technological nondemountable objects with high requirements for metrological characteristics have been studied. To develop the scattered cyberphysical systems, the portable stable-in-time code-controlled measures of physical quantities have been studied. They have to be metrologically confirmed in the laboratory before the delivery to the site of the measuring subsystem for its calibration.

Detecting Intrusions in Cyber-Physical Systems of Smart Cities

2019 ◽  
pp. 74-102 ◽  
Author(s):  
Ismail Butun ◽  
Patrik Österberg
Keyword(s):  
Anomaly Detection ◽  
Smart Cities ◽  
Cyber Physical Systems ◽  
Security And Privacy ◽  
Security Vulnerabilities ◽  
Physical Systems ◽  
Detection Systems ◽  
Comprehensive Survey ◽  
Privacy Violation ◽  
Detection Schemes

Interfacing the smart cities with cyber-physical systems (CPSs) improves cyber infrastructures while introducing security vulnerabilities that may lead to severe problems such as system failure, privacy violation, and/or issues related to data integrity if security and privacy are not addressed properly. In order for the CPSs of smart cities to be designed with proactive intelligence against such vulnerabilities, anomaly detection approaches need to be employed. This chapter will provide a brief overview of the security vulnerabilities in CPSs of smart cities. Following a thorough discussion on the applicability of conventional anomaly detection schemes in CPSs of smart cities, possible adoption of distributed anomaly detection systems by CPSs of smart cities will be discussed along with a comprehensive survey of the state of the art. The chapter will discuss challenges in tailoring appropriate anomaly detection schemes for CPSs of smart cities and provide insights into future directions for the researchers working in this field.

Bayesian Model for Evaluating Real-World Adaptation Progress of a Cyber-Physical System

2021 ◽  
pp. 324-343
Author(s):  
Arif Sari ◽  
Joshua Chibuike Sopuru
Keyword(s):  
Work Environment ◽  
Real World ◽  
Environmental Conditions ◽  
Physical System ◽  
Bayesian Model ◽  
Cyber Physical Systems ◽  
Cyber Physical System ◽  
Industrial Activities ◽  
Physical Systems

Cyber-physical systems, also known as CPS, have come to stay. There is no doubt, CPS would one day outnumber humans in industries. How do we evaluate the adaptation progress of these systems considering changing environmental conditions? A failed implementation of a CPS can result to a loss. Since CPSs are designed to automate industrial activities, which are centred on the use of several technologies, collaboration with humans may sometimes be inevitable. CPSs are needed to automate several processes and thus help firms compete favourably within an industry. This chapter focuses on the adaptation of CPS in diverse work environment. Considering the ecosystem of the CPS, the authors present a Bayesian model evaluating the progress of adaptation of a CPS given some known conditions.

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