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

Category : Electrical


Sub Category : Defense


Project Code : ITEEE02


Project Abstract

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

Existing system

Proposed  system

 Meet the demand is not possible in this method.

 Cannot find the energy theft in distribution network.

Drawbacks of existing system:

Possible for electricity stealing.

 Causes for power crisis.

 Load shedding is taken place.

 

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

 GSM is used for intimation purpose.

 

Advantage of proposed system

 Can meet the demand requirements.

 Prevent the electricity stealing.





 
 
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