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Data-Stream-Based Intrusion Detection System for Advanced Metering Infrastructure in Smart Grid: A Feasibility Study

Category : Embedded


Sub Category : Defense


Project Code : ITEEE02


Project Abstract

Abstract:

With the proliferation of smart grid research, the Advanced Metering Infrastructure (AMI) has become the first ubiquitous and fixed computing platform. However, due to the unique characteristics of AMI, such as complex network structure, resource-constrained smart meter, and privacy-sensitive data, it is an especially challenging issue to make AMI secure. Energy theft is one of the most important concerns related to the smart grid implementation. It is estimated that utility companies lose more than $25 billion every year due to energy theft around the world. To address this challenge, in this paper, we discuss the background of AMI and identify major security requirements that AMI should meet. Specifically, an attack tree based threat model is first presented to illustrate the energy-theft behaviors in AMI. Then, we summarize the current AMI energy-theft detection schemes into three categories, i.e., classification-based, state estimation-based and game theory-based ones, and make extensive comparisons and discussions on them. In order to provide a deep understanding of security vulnerabilities and solutions in AMI and shed light on future research directions, we also explore some open challenges and potential solutions for energy-theft detection.

Existing system

Proposed  system

Ø Meet the demand is not possible in this method.

Ø Cannot find the energy theft in distribution network.

Drawbacks of existing system:

Ø Possible for electricity stealing.

Ø Causes for power crisis.

Ø Load shedding is taken place.

 

Ø Current sensor is used to find the power theft in distributed generation.

Ø GSM is used for intimation purpose.

 

Advantage of proposed system

Ø Can meet the demand requirements.

Ø Prevent the electricity stealing.

 
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