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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Mohajerani, Z. Farzan, F. Jafary, M. Lu, Y. Wei, D. Kalenchits, N. Boyer, B. Muller, M. Skare, P. |
| Copyright Year | 2010 |
| Description | Author affiliation: Automation and Control Department, SIEMENS Corporate Research Inc., Princeton, NJ, USA (Lu, Y.; Wei, D.; Kalenchits, N.) || Mechanical Engineering Department, Rutgers University, Piscataway, NJ, USA (Boyer, B.; Muller, M.) || Industrial Engineering Department, Rutgers University, Piscataway, NJ, USA (Mohajerani, Z.; Farzan, F.; Jafary, M.) || Energy Automation, SIEMENS Energy Inc., Minnetonka, MN, USA (Skare, P.) |
| Abstract | This paper introduces a new way to detect and improve the vulnerability of bulk power systems against the intrusion and malicious acts of cyber hackers. For this aim, detecting the most vulnerable part of the power grid to hacker attack is needed. The method for finding the most vulnerable substation inside the grid (fist pass model) and then finding the most critical asset inside that substation (second pass model) is presented. The suggested method performs Improvement in overall vulnerability of the grid by calculating the risk of each asset and placing a security agent on the most vulnerable positions within the substation to prevent the cyber attacks as most as possible. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 273167 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424465460 |
| e-ISBN | 9781424465484 |
| DOI | 10.1109/TDC.2010.5484417 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-04-19 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Risk management Power grids Substations Computer security Computer hacking Automation Power system modeling Industrial engineering Automatic control Control systems power grids cyber security risk assessments |
| Content Type | Text |
| Resource Type | Article |
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