%0 Journal Article %1 Rubavathy_2015 %A A, Ruth Rubavathy %A Krishnan, Mr. M. Navaneetha %D 2015 %I Auricle Technologies, Pvt., Ltd. %J International Journal on Recent and Innovation Trends in Computing and Communication %K Anomaly GOOSE Ranking SMV and anomaly cyber detection security substations %N 3 %P 923--926 %R 10.17762/ijritcc2321-8169.150305 %T A New Ranking Approach to Efficiently Detect Anomalies in Cyber Security of Substation %U http://dx.doi.org/10.17762/ijritcc2321-8169.150305 %V 3 %X Smart Grid advancements present an undetermined level of risk to electric grid reliability. The coupling of the power infrastructure with complex computer networks substantially expand current cyber-attack surface area and will require significant advances in cyber security capabilities. New capabilities for smart grid system and networks, such as broadband and distributed intelligence capabilities can greatly enhance efficiency and reliability, but they may also create much new vulnerability if not deployed with the appropriate security controls. Providing security for a large system may seem an unfathomable task, and can leave utilities open to cyber-attacks. The problem is to provide an efficient security mechanism to the power grids. Already many mechanisms are proposed for network and host based cyber security these methods does not provide efficient security mechanism. A new mechanism is proposed based on ranking the network and host based anomalies using Gaussian approximation algorithm. This method will monitor the anomalies occurs in the substation and rank the continuous network level security by implementing additional features such as Traffic Analyzing System, Address Blocks System and Packet Filtering System.

@article{Rubavathy_2015, abstract = {Smart Grid advancements present an undetermined level of risk to electric grid reliability. The coupling of the power infrastructure with complex computer networks substantially expand current cyber-attack surface area and will require significant advances in cyber security capabilities. New capabilities for smart grid system and networks, such as broadband and distributed intelligence capabilities can greatly enhance efficiency and reliability, but they may also create much new vulnerability if not deployed with the appropriate security controls. Providing security for a large system may seem an unfathomable task, and can leave utilities open to cyber-attacks. The problem is to provide an efficient security mechanism to the power grids. Already many mechanisms are proposed for network and host based cyber security these methods does not provide efficient security mechanism. A new mechanism is proposed based on ranking the network and host based anomalies using Gaussian approximation algorithm. This method will monitor the anomalies occurs in the substation and rank the continuous network level security by implementing additional features such as Traffic Analyzing System, Address Blocks System and Packet Filtering System.}, added-at = {2015-08-06T07:05:38.000+0200}, author = {A, Ruth Rubavathy and Krishnan, Mr. M. Navaneetha}, biburl = {https://www.bibsonomy.org/bibtex/237fd86094c04302c32e9011e8774e2e6/ijritcc}, doi = {10.17762/ijritcc2321-8169.150305}, interhash = {18725015967bf8dbad5637707e41d472}, intrahash = {37fd86094c04302c32e9011e8774e2e6}, journal = {International Journal on Recent and Innovation Trends in Computing and Communication}, keywords = {Anomaly GOOSE Ranking SMV and anomaly cyber detection security substations}, month = {march}, number = 3, pages = {923--926}, publisher = {Auricle Technologies, Pvt., Ltd.}, timestamp = {2015-08-06T07:05:38.000+0200}, title = {A New Ranking Approach to Efficiently Detect Anomalies in Cyber Security of Substation}, url = {http://dx.doi.org/10.17762/ijritcc2321-8169.150305}, volume = 3, year = 2015 }