Visible to the public Biblio

Filters: Author is Govindarasu, M.  [Clear All Filters]
2015-04-30
Junho Hong, Chen-Ching Liu, Govindarasu, M..  2014.  Integrated Anomaly Detection for Cyber Security of the Substations. Smart Grid, IEEE Transactions on. 5:1643-1653.

Cyber intrusions to substations of a power grid are a source of vulnerability since most substations are unmanned and with limited protection of the physical security. In the worst case, simultaneous intrusions into multiple substations can lead to severe cascading events, causing catastrophic power outages. In this paper, an integrated Anomaly Detection System (ADS) is proposed which contains host- and network-based anomaly detection systems for the substations, and simultaneous anomaly detection for multiple substations. Potential scenarios of simultaneous intrusions into the substations have been simulated using a substation automation testbed. The host-based anomaly detection considers temporal anomalies in the substation facilities, e.g., user-interfaces, Intelligent Electronic Devices (IEDs) and circuit breakers. The malicious behaviors of substation automation based on multicast messages, e.g., Generic Object Oriented Substation Event (GOOSE) and Sampled Measured Value (SMV), are incorporated in the proposed network-based anomaly detection. The proposed simultaneous intrusion detection method is able to identify the same type of attacks at multiple substations and their locations. The result is a new integrated tool for detection and mitigation of cyber intrusions at a single substation or multiple substations of a power grid.

Sridhar, S., Govindarasu, M..  2014.  Model-Based Attack Detection and Mitigation for Automatic Generation Control. Smart Grid, IEEE Transactions on. 5:580-591.

Cyber systems play a critical role in improving the efficiency and reliability of power system operation and ensuring the system remains within safe operating margins. An adversary can inflict severe damage to the underlying physical system by compromising the control and monitoring applications facilitated by the cyber layer. Protection of critical assets from electronic threats has traditionally been done through conventional cyber security measures that involve host-based and network-based security technologies. However, it has been recognized that highly skilled attacks can bypass these security mechanisms to disrupt the smooth operation of control systems. There is a growing need for cyber-attack-resilient control techniques that look beyond traditional cyber defense mechanisms to detect highly skilled attacks. In this paper, we make the following contributions. We first demonstrate the impact of data integrity attacks on Automatic Generation Control (AGC) on power system frequency and electricity market operation. We propose a general framework to the application of attack resilient control to power systems as a composition of smart attack detection and mitigation. Finally, we develop a model-based anomaly detection and attack mitigation algorithm for AGC. We evaluate the detection capability of the proposed anomaly detection algorithm through simulation studies. Our results show that the algorithm is capable of detecting scaling and ramp attacks with low false positive and negative rates. The proposed model-based mitigation algorithm is also efficient in maintaining system frequency within acceptable limits during the attack period.

2015-05-06
Junho Hong, Chen-Ching Liu, Govindarasu, M..  2014.  Detection of cyber intrusions using network-based multicast messages for substation automation. Innovative Smart Grid Technologies Conference (ISGT), 2014 IEEE PES. :1-5.

This paper proposes a new network-based cyber intrusion detection system (NIDS) using multicast messages in substation automation systems (SASs). The proposed network-based intrusion detection system monitors anomalies and malicious activities of multicast messages based on IEC 61850, e.g., Generic Object Oriented Substation Event (GOOSE) and Sampled Value (SV). NIDS detects anomalies and intrusions that violate predefined security rules using a specification-based algorithm. The performance test has been conducted for different cyber intrusion scenarios (e.g., packet modification, replay and denial-of-service attacks) using a cyber security testbed. The IEEE 39-bus system model has been used for testing of the proposed intrusion detection method for simultaneous cyber attacks. The false negative ratio (FNR) is the number of misclassified abnormal packets divided by the total number of abnormal packets. The results demonstrate that the proposed NIDS achieves a low fault negative rate.
 

Junho Hong, Chen-Ching Liu, Govindarasu, M..  2014.  Integrated Anomaly Detection for Cyber Security of the Substations. Smart Grid, IEEE Transactions on. 5:1643-1653.

Cyber intrusions to substations of a power grid are a source of vulnerability since most substations are unmanned and with limited protection of the physical security. In the worst case, simultaneous intrusions into multiple substations can lead to severe cascading events, causing catastrophic power outages. In this paper, an integrated Anomaly Detection System (ADS) is proposed which contains host- and network-based anomaly detection systems for the substations, and simultaneous anomaly detection for multiple substations. Potential scenarios of simultaneous intrusions into the substations have been simulated using a substation automation testbed. The host-based anomaly detection considers temporal anomalies in the substation facilities, e.g., user-interfaces, Intelligent Electronic Devices (IEDs) and circuit breakers. The malicious behaviors of substation automation based on multicast messages, e.g., Generic Object Oriented Substation Event (GOOSE) and Sampled Measured Value (SMV), are incorporated in the proposed network-based anomaly detection. The proposed simultaneous intrusion detection method is able to identify the same type of attacks at multiple substations and their locations. The result is a new integrated tool for detection and mitigation of cyber intrusions at a single substation or multiple substations of a power grid.
 

2017-11-27
Ashok, A., Krishnaswamy, S., Govindarasu, M..  2016.  PowerCyber: A remotely accessible testbed for Cyber Physical security of the Smart Grid. 2016 IEEE Power Energy Society Innovative Smart Grid Technologies Conference (ISGT). :1–5.

Cyber Physical Systems (CPS) security testbeds serve as a platform for evaluating and validating novel CPS security tools and technologies, accelerating the transition of state-of-the-art research to industrial practice. The engineering of CPS security testbeds requires significant investments in money, time and modeling efforts to provide a scalable, high-fidelity, real-time attack-defense platform. Therefore, there is a strong need in academia and industry to create remotely accessible testbeds that support a range of use-cases pertaining to CPS security of the grid, including vulnerability assessments, impact analysis, product testing, attack-defense exercises, and operator training. This paper describes the implementation architecture, and capabilities of a remote access and experimental orchestration framework developed for the PowerCyber CPS security testbed at Iowa State University (ISU). The paper then describes several engineering challenges in the development of such remotely accessible testbeds for Smart Grid CPS security experimentation. Finally, the paper provides a brief case study with some screenshots showing a particular use case scenario on the remote access framework.

2018-01-16
Ulrich, J., Drahos, J., Govindarasu, M..  2017.  A symmetric address translation approach for a network layer moving target defense to secure power grid networks. 2017 Resilience Week (RWS). :163–169.

This paper will suggest a robust method for a network layer Moving Target Defense (MTD) using symmetric packet scheduling rules. The MTD is implemented and tested on a Supervisory Control and Data Acquisition (SCADA) network testbed. This method is shown to be efficient while providing security benefits to the issues faced by the static nature of SCADA networks. The proposed method is an automated tool that may provide defense in depth when be used in conjunction with other MTDs and traditional security devices.

Pappa, A. C., Ashok, A., Govindarasu, M..  2017.  Moving target defense for securing smart grid communications: Architecture, implementation evaluation. 2017 IEEE Power Energy Society Innovative Smart Grid Technologies Conference (ISGT). :1–5.

Supervisory Control and Data Acquisition(SCADA) communications are often subjected to various sophisticated cyber-attacks mostly because of their static system characteristics, enabling an attacker for easier profiling of the target system(s) and thereby impacting the Critical Infrastructures(CI). In this Paper, a novel approach to mitigate such static vulnerabilities is proposed by implementing a Moving Target Defense (MTD) strategy in a power grid SCADA environment, leveraging the existing communication network with an end-to-end IP-Hopping technique among trusted peers. The main contribution involves the design and implementation of MTD Architecture on Iowa State's PowerCyber testbed for targeted cyber-attacks, without compromising the availability of a SCADA system and studying the delay and throughput characteristics for different hopping rates in a realistic environment. Finally, we study two cases and provide mitigations for potential weaknesses of the proposed mechanism. Also, we propose to incorporate port mutation to further increase attack complexity as part of future work.

2018-02-02
Ashok, A., Sridhar, S., McKinnon, A. D., Wang, P., Govindarasu, M..  2016.  Testbed-based performance evaluation of Attack Resilient Control for AGC. 2016 Resilience Week (RWS). :125–129.

The modern electric power grid is a complex cyber-physical system whose reliable operation is enabled by a wide-area monitoring and control infrastructure. Recent events have shown that vulnerabilities in this infrastructure may be exploited to manipulate the data being exchanged. Such a scenario could cause the associated control applications to mis-operate, potentially causing system-wide instabilities. There is a growing emphasis on looking beyond traditional cybersecurity solutions to mitigate such threats. In this paper we perform a testbed-based validation of one such solution - Attack Resilient Control (ARC) - on Iowa State University's PowerCyber testbed. ARC is a cyber-physical security solution that combines domain-specific anomaly detection and model-based mitigation to detect stealthy attacks on Automatic Generation Control (AGC). In this paper, we first describe the implementation architecture of the experiment on the testbed. Next, we demonstrate the capability of stealthy attack templates to cause forced under-frequency load shedding in a 3-area test system. We then validate the performance of ARC by measuring its ability to detect and mitigate these attacks. Our results reveal that ARC is efficient in detecting stealthy attacks and enables AGC to maintain system operating frequency close to its nominal value during an attack. Our studies also highlight the importance of testbed-based experimentation for evaluating the performance of cyber-physical security and control applications.

2021-04-09
Ravikumar, G., Singh, A., Babu, J. R., A, A. Moataz, Govindarasu, M..  2020.  D-IDS for Cyber-Physical DER Modbus System - Architecture, Modeling, Testbed-based Evaluation. 2020 Resilience Week (RWS). :153—159.
Increasing penetration of distributed energy resources (DERs) in distribution networks expands the cyberattack surface. Moreover, the widely used standard protocols for communicating DER inverters such as Modbus is more vulnerable to data-integrity attacks and denial of service (DoS) attacks because of its native clear-text packet format. This paper proposes a distributed intrusion detection system (D-IDS) architecture and algorithms for detecting anomalies on the DER Modbus communication. We devised a model-based approach to define physics-based threshold bands for analog data points and transaction-based threshold bands for both the analog and discrete data points. The proposed IDS algorithm uses the model- based approach to develop Modbus-specific IDS rule sets, which can enhance the detection accuracy of the anomalies either by data-integrity attacks or maloperation on cyber-physical DER Modbus devices. Further, the IDS algorithm autogenerates the Modbus-specific IDS rulesets in compliance with various open- source IDS rule syntax formats, such as Snort and Suricata, for seamless integration and mitigation of semantic/syntax errors in the development and production environment. We considered the IEEE 13-bus distribution grid, including DERs, as a case study. We conducted various DoS type attacks and data-integrity attacks on the hardware-in-the-loop (HIL) CPS DER testbed at ISU to evaluate the proposed D-IDS. Consequently, we computed the performance metrics such as IDS detection accuracy, IDS detection rate, and end-to-end latency. The results demonstrated that 100% detection accuracy, 100% detection rate for 60k DoS packets, 99.96% detection rate for 80k DoS packets, and 0.25 ms end-to-end latency between DERs to Control Center.