A Simple Cyber Attack Detection Scheme for Smart Grid Cyber Security Enhancement

Cybercrime continues to emerge, with new threats surfacing every year. Every business, regardless of its size, is a potential target of cyber-attack. Cybersecurity in today's connected world is a key component of any establishment. Amidst known security threats in a virtualization environment, side-channel attacks (SCA) target most impressionable data and computations. SCA is flattering major security interests that need to be inspected from a new point of view. As a part of cybersecurity aspects, secured implementation of virtualization infrastructure is very much essential to ensure the overall security of the cloud computing environment. We require the most effective tools for threat detection, response, and reporting to safeguard business and customers from cyber-attacks. The objective of this chapter is to explore virtualization aspects of cybersecurity threats and solutions in the cloud computing environment. The authors also discuss the design of their novel ‘Flush+Flush' cache attack detection approach in a virtualized environment.

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Cyber Security Aspects of Virtualization in Cloud Computing Environments

Quantum Cryptography and the Future of Cyber Security - Advances in Information Security, Privacy, and Ethics ◽

10.4018/978-1-7998-2253-0.ch013 ◽

2020 ◽

pp. 283-299 ◽

Cited By ~ 1

Author(s):

Darshan Mansukhbhai Tank ◽

Akshai Aggarwal ◽

Nirbhay Kumar Chaubey

Keyword(s):

Cloud Computing ◽

Cyber Security ◽

Attack Detection ◽

Cyber Attacks ◽

Point Of View ◽

Cyber Attack ◽

Computing Environment ◽

Cloud Computing Environment ◽

Detection Approach ◽

Detection Response

Cybercrime continues to emerge, with new threats surfacing every year. Every business, regardless of its size, is a potential target of cyber-attack. Cybersecurity in today's connected world is a key component of any establishment. Amidst known security threats in a virtualization environment, side-channel attacks (SCA) target most impressionable data and computations. SCA is flattering major security interests that need to be inspected from a new point of view. As a part of cybersecurity aspects, secured implementation of virtualization infrastructure is very much essential to ensure the overall security of the cloud computing environment. We require the most effective tools for threat detection, response, and reporting to safeguard business and customers from cyber-attacks. The objective of this chapter is to explore virtualization aspects of cybersecurity threats and solutions in the cloud computing environment. The authors also discuss the design of their novel ‘Flush+Flush' cache attack detection approach in a virtualized environment.

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Cognitive Dynamic System for AC State Estimation and Cyber-Attack Detection in Smart Grid

10.5772/intechopen.94093 ◽

2020 ◽

Author(s):

Mohammad Irshaad Oozeer ◽

Simon Haykin

Keyword(s):

Smart Grid ◽

Dynamic System ◽

State Estimation ◽

Attack Detection ◽

Cyber Attacks ◽

Data Detection ◽

Cyber Attack ◽

Bad Data Detection ◽

Cycle Basis ◽

Iterative Procedures

The work presented in this chapter is an extension of our previous research of bringing together the Cognitive Dynamic System (CDS) and the Smart Grid (SG) by focusing on AC state estimation and Cyber-Attack detection. Under the AC power flow model, state estimation is complex and computationally expensive as it relies on iterative procedures. On the other hand, the False Data Injection (FDI) attacks are a new category of cyber-attacks targeting the SG that can bypass the current bad data detection techniques in the SG. Due to the complexity of the nonlinear system involved, the amount of published works on AC based FDI attacks have been fewer compared to their DC counterpart. Here, we will demonstrate how the entropic state, which is the objective function of the CDS, can be used as a metric to monitor the grid’s health and detect FDI attacks. The CDS, acting as the supervisor of the system, improves the entropic state on a cycle to cycle basis by dynamically optimizing the state estimation process through the reconfiguration of the weights of the sensors in the network. In order to showcase performance of this new structure, computer simulations are carried out on the IEEE 14-bus system for optimal state estimation and FDI attack detection.

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Malware Detection for Cyber Security Enhancement in Smart Grid

10.29007/fn3p ◽

2018 ◽

Author(s):

Congmiao Li ◽

Dipti Srinivasan ◽

Thomas Reindl

Keyword(s):

Smart Grid ◽

Cyber Security ◽

Detection System ◽

Malware Detection ◽

Cyber Attacks ◽

Grid Security ◽

Embedded Devices ◽

Security Enhancement ◽

Smart Grid Security ◽

Security Problem

Many embedded systems in a Smart Grid have special constraints in terms of timing, cost and power consumption to ensure security. This paper addresses the Smart Grid security problem with a focus on improving the security of crucial components, and reducing the risks from cyber attacks. A hardware architecture to enhance the security of important embedded devices in the smart grid has been proposed and implemented. This hardware based malware detection system runs on a dedicated hardware implemented with FPGA logic, and allows detection in near real-time. The system architecture and results are presented in the paper.

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