This paper presents an anomaly-based methodology for reliable detection of integrity attacks in cyber-physical critical infrastructures. Such malicious events compromise the smooth operation of the infrastructure while the attacker is able to exploit the respective resources according to his/her purposes. Even though the operator may not understand the attack, since the overall system appears to remain in a steady state, the consequences may be of catastrophic nature with a huge negative impact. Here, we apply a computational intelligent technique which incorporates the merits of two of the heterogeneous modeling approaches (linear time-invariant and neural networks), while considering both temporal and functional dependencies existing among the elements of an infrastructure. The experimental platform includes a power grid simulator of the IEEE 30 bus model and a cyber network emulator. Subsequently, we implemented a wide range of integrity attacks (replay, ramp, pulse, scaling, and random) with different intensity levels. A thorough evaluation procedure is carried out while the results demonstrate the ability of the proposed method to produce a desired result in terms of false positive rate, false negative rate, and detection delay.

Detection of integrity attacks in cyber-physical critical infrastructures using ensemble modeling / S. Ntalampiras. - In: IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS. - ISSN 1551-3203. - 11:1(2015 Feb), pp. 6948272.104-6948272.111. [10.1109/TII.2014.2367322]

Detection of integrity attacks in cyber-physical critical infrastructures using ensemble modeling

S. Ntalampiras
2015-02

Abstract

This paper presents an anomaly-based methodology for reliable detection of integrity attacks in cyber-physical critical infrastructures. Such malicious events compromise the smooth operation of the infrastructure while the attacker is able to exploit the respective resources according to his/her purposes. Even though the operator may not understand the attack, since the overall system appears to remain in a steady state, the consequences may be of catastrophic nature with a huge negative impact. Here, we apply a computational intelligent technique which incorporates the merits of two of the heterogeneous modeling approaches (linear time-invariant and neural networks), while considering both temporal and functional dependencies existing among the elements of an infrastructure. The experimental platform includes a power grid simulator of the IEEE 30 bus model and a cyber network emulator. Subsequently, we implemented a wide range of integrity attacks (replay, ramp, pulse, scaling, and random) with different intensity levels. A thorough evaluation procedure is carried out while the results demonstrate the ability of the proposed method to produce a desired result in terms of false positive rate, false negative rate, and detection delay.
cyberphysical critical infrastructures; Ensemble modeling; fault diagnosis; Control and Systems Engineering; Information Systems; Computer Science Applications1707 Computer Vision and Pattern Recognition; Electrical and Electronic Engineering
Settore INF/01 - Informatica
5-nov-2014
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/615207
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