A topology processor that tracks network modifications

Prais, M.; Bose, Anjan

doi:10.1109/59.14552

Cited by 90 publications

(24 citation statements)

References 4 publications

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“…An attacker can obtain data on power usage and breakers' status, and based on this information, estimate system state and determine network topology [5] [6]. Then he/she can use contingency analysis methods to decide on the attack strategy (e.g., which transmission lines to open) to cause maximum damage with minimum effort.…”

Section: Attack Preparationmentioning

confidence: 99%

“…As most proprietary SCADA protocols lack security properties (e.g., authentication and integrity), we assume that an attacker can install a malicious software on the SCADA system to either directly observe real-time measurements arriving from substations [4], or access data historians. Based on the measurements, it is also possible for an attacker to estimate network topology and system states [5] [6].  We trust measurements of power usage, current, and voltage directly obtained from sensing devices (or sensors) in substations.…”

Section: Attack Modelmentioning

confidence: 99%

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Semantic security analysis of SCADA networks to detect malicious control commands in power grids

Lin¹,

Slagell

Kalbarczyk³

et al. 2013

Proceedings of the First ACM Workshop on Smart Energy Grid Security

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In the current generation of SCADA (Supervisory Control And Data Acquisition) systems used in power grids, a sophisticated attacker can exploit system vulnerabilities and use a legitimate maliciously crafted command to cause a wide range of system changes that traditional contingency analysis does not consider and remedial action schemes cannot handle. To detect such malicious commands, we propose a semantic analysis framework based on a distributed network of intrusion detection systems (IDSes). The framework combines system knowledge of both cyber and physical infrastructure in power grid to help IDS to estimate execution consequences of control commands, thus to reveal attacker's malicious intentions. We evaluated the approach on the IEEE 30-bus system. Our experiments demonstrate that: (i) by opening 3 transmission lines, an attacker can avoid detection by the traditional contingency analysis and instantly put the tested 30-bus system into an insecure state and (ii) the semantic analysis provides reliable detection of malicious commands with a small amount of analysis time.

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Section: Attack Preparationmentioning

confidence: 99%

Section: Attack Modelmentioning

confidence: 99%

Semantic security analysis of SCADA networks to detect malicious control commands in power grids

Lin¹,

Slagell

Kalbarczyk³

et al. 2013

Proceedings of the First ACM Workshop on Smart Energy Grid Security

View full text Add to dashboard Cite

show abstract

“…(1) The outage area is identified to obtain the suspected fault sections using a real-time network topology determination method [21]. (2) An objective function, which reflect the discrepancy between the actual and the expected states of protective relays and circuit breakers, is formulated based on the logic relationship among the section faults, the actions of protective relays and the tripping of circuit breakers.…”

Section: Frameworkmentioning

confidence: 99%

A new analytic approach for power system fault diagnosis employing the temporal information of alarm messages

Guo

Wen

Ledwich

et al. 2012

International Journal of Electrical Power & Energy Systems

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“…First, the status information is read from the SCADA system. Second, outage areas are identified to obtain the suspected fault sections using network topology analysis method [10], [31]. Third, a fault diagnosis model for each section in each candidate outage area is built.…”

mentioning

confidence: 99%

Fault Diagnosis of Electric Power Systems Based on Fuzzy Reasoning Spiking Neural P Systems

Wang

Zhang

Zhao

et al. 2015

IEEE Trans. Power Syst.

213

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This paper proposes a graphic modeling approach, fault diagnosis method based on fuzzy reasoning spiking neural P systems (FDSNP), for power transmission networks. In FDSNP, fuzzy reasoning spiking neural P systems (FRSN P systems) with trapezoidal fuzzy numbers are used to model candidate faulty sections and an algebraic fuzzy reasoning algorithm is introduced to obtain confidence levels of candidate faulty sections, so as to identify faulty sections. FDSNP offers an intuitive illustration based on a strictly mathematical expression, a good fault-tolerant capacity due to its handling of incomplete and uncertain messages in a parallel manner, a good description for the relationships between protective devices and faults, and an understandable diagnosis model-building process. To test the validity and feasibility of FDSNP, seven cases of a local subsystem in an electrical power system are used. The results of case studies show that FDSNP is effective in diagnosing faults in power transmission networks for single and multiple fault situations with/without incomplete and uncertain SCADA data, and is superior to four methods, reported in the literature, in terms of the correctness of diagnosis results.Index Terms-Electric power system, fault diagnosis, fuzzy production rules, fuzzy reasoning, fuzzy reasoning spiking neural P system, linguistic term, trapezoidal fuzzy number.

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A topology processor that tracks network modifications

Cited by 90 publications

References 4 publications

Semantic security analysis of SCADA networks to detect malicious control commands in power grids

Semantic security analysis of SCADA networks to detect malicious control commands in power grids

A new analytic approach for power system fault diagnosis employing the temporal information of alarm messages

Fault Diagnosis of Electric Power Systems Based on Fuzzy Reasoning Spiking Neural P Systems

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