scholarly journals A Situation-Aware Scheme for Efficient Device Authentication in Smart Grid-Enabled Home Area Networks

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 989 ◽  
Author(s):  
Anhao Xiang ◽  
Jun Zheng
Keyword(s):  
Smart Grid ◽  
Smart Grids ◽  
Communication Complexity ◽  
Situational Awareness ◽  
Security Analysis ◽  
Risk Level ◽  
Security Risk ◽  
Risk Levels ◽  
Home Area ◽  
Home Area Networks

Home area networks (HANs) are the most vulnerable part of smart grids since they are not directly controlled by utilities. Device authentication is one of most important mechanisms to protect the security of smart grid-enabled HANs (SG-HANs). In this paper, we propose a situation-aware scheme for efficient device authentication in SG-HANs. The proposed scheme utilizes the security risk information assessed by the smart home system with a situational awareness feature. A suitable authentication protocol with adequate security protection and computational and communication complexity is then selected based on the assessed security risk level. A protocol design of the proposed scheme considering two security risk levels is presented in the paper. The security of the design is verified by using both formal verification and informal security analysis. Our performance analysis demonstrates that the proposed scheme is efficient in terms of computational and communication costs.

scholarly journals Combination of D-AHP and Grey Theory for the Assessment of the Information Security Risks of Smart Grids

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Hua Dong ◽  
Jun Zhao ◽  
Xiaoyu Yang ◽  
Kun Yang
Keyword(s):  
Information Security ◽  
Smart Grid ◽  
Embedded System ◽  
Smart Grids ◽  
Comprehensive Assessment ◽  
Qualitative Assessment ◽  
Risk Level ◽  
Grey Theory ◽  
Security Risk ◽  
Ahp Method

As a modern power infrastructure, smart grids have great advantages over traditional power grids, but their effective operation is largely restricted by information security. Hence, a smart grid information security risk assessment (ISRA) method is proposed. This method combines D numbers to improve the classical analytic hierarchy process (D-AHP) independent of experts’ subjective qualitative assessment and then integrated with grey theory which does not require complete and unambiguous information. First, we establish a smart grid ISRA system according to the characteristics and development reality of smart grid technology. The proposed system includes 5 first-level indexes as an intelligent terminal, a wireless communication channel, password security, application code and embedded system, and corresponding 13 secondary indexes. Second, a D-AHP method aimed at the uncertainty of human subjective judgment and fuzziness of language assessment is used to obtain the weight of each index. The D-AHP method is then combined with the grey assessment matrix solved by grey theory, to obtain the comprehensive assessment value and corresponding risk grade. With a smart grid demonstration project in Suzhou, China, as an example, an empirical study is carried out using expert scoring. The comprehensive assessment risk value is 3.8199, and the corresponding risk level is moderate. The results of this work could serve as a reference for the information security protection of smart grids.

scholarly journals A Risk Assessment Framework to Reduce Risk Level and Optimize Software Quality

2015 ◽  
Vol 1 (1) ◽  
Author(s):  
Sanjeev Puri
Keyword(s):  
Risk Assessment ◽  
Risk Analysis ◽  
Security Policy ◽  
Management Control ◽  
Risk Level ◽  
Assessment Framework ◽  
Security Risk ◽  
Software Projects ◽  
Risk Levels ◽  
Reduce Risk

Risk management for software projects is intended to minimize the chances of unexpected events, or more specifically to keep all possible outcomes under tight management control with making judgments about how risk events are to be treated, valued, compared and combined. It is necessary to have some well-founded infrastructure for the identification of software security risks as well as the application of appropriate controls to manage risks. To be truly beneficial, the risk analysis framework must be granular and practical enough to produce a customizable roadmap of which problems exist, and to rank them in order of severity. The paper a risk assessment framework for a precise, unambiguous and efficient risk analysis with qualitative risk analysis methodologies and tree based techniques by exploiting the synthesis of risk analysis methods with object-oriented modeling, semi-formal methods and tools, in order to improve the security risk analysis of software and security policy implementation of security-cri tical systems to reduce risk levels and optimizequality instructions.

scholarly journals Home Area Networks and the Smart Grid

2011 ◽  
Author(s):  
Samuel L. Clements ◽  
Thomas E. Carroll ◽  
Mark D. Hadley
Keyword(s):  
Smart Grid ◽  
Home Area ◽  
Home Area Networks

Efficient Electricity Forecasting in Multiple Residential Buildings considering Demand-Side Management

2021 ◽  
pp. 49-63
Author(s):  
Piyush Kumar Shukla ◽  
◽  
Prashant Kumar Shukla ◽  
Keyword(s):  
Deep Learning ◽  
Smart Grid ◽  
Smart Grids ◽  
Residential Buildings ◽  
Load Forecasting ◽  
Time Interval ◽  
Short Time Interval ◽  
Area Network ◽  
Load Prediction ◽  
Home Area

Gateway based Home Area Network (HAN ) to Neighbourhood Area Network (NAN); NAN to HAN improved the communication in the Smart grid. The gateway reduces the Load dispatch centre (LDC) work in varying power consumption in a short time interval. The proposed work explains the working of gateway, reducing the work of LDC using the load scheduling procedure. Deep learning methods incorporated gateway will aid in achieving the requirement. It reduces black start operation and it may be prevented by indulging consumers in the supply automation of the grid. It will produce the grid to maintain the operating frequency, avoiding the substations' disciplinary charges. A variety of types of abrupt load variation and load kinds has been taken in this function. The analysis shows that the gateway achieves a decrease in complexity in the proposed work. This method provides the detail of employment of deep learning for predicting the load forecasting performances in smart grids that can be made better through a gateway between SMs-DCU. The Proposed work compares with systems that employ the predictable profound estimating methods for load forecasting, which has provided better performance. Load Prediction, Deep Learning, Gateway, Smart Grid, Estimation

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