The Experts below are selected from a list of 7773 Experts worldwide ranked by ideXlab platform
Shiyan Hu - One of the best experts on this subject based on the ideXlab platform.
-
Leveraging Strategic Detection Techniques for Smart Home Pricing Cyberattacks
IEEE Transactions on Dependable and Secure Computing, 2016Co-Authors: Shiyan Hu, Tsung-yi HoAbstract:In this work, the vulnerability of the electricity pricing model in the smart home system is assessed. Two closely related pricing Cyberattacks which manipulate the guideline electricity prices received at smart meters are considered and they aim at reducing the expense of the cyberattacker and increasing the peak energy usage in the local community. A single event detection technique which uses support vector regression and impact difference for detecting anomaly pricing is proposed. The detection capability of such a technique is still limited since it does not model the long term impact of pricing Cyberattacks. This motivates us to develop a partially observable Markov decision process based detection algorithm, which has the ingredients such as reward expectation and policy transfer graph to account for the cumulative impact and the potential future impact due to pricing Cyberattacks. Our simulation results demonstrate that the pricing cyberattack can reduce the cyberattacker's bill by 34.3 percent at cost of the increase of others’ bill by 7.9 percent, and increase the peak to average ratio (PAR) by 35.7 percent. Furthermore, the proposed long term detection technique has the detection accuracy of more than 97 percent with significant reduction in PAR and bill compared to repeatedly using the single event detection technique.
-
The Hierarchical Smart Home Cyberattack Detection Considering Power Overloading and Frequency Disturbance
IEEE Transactions on Industrial Informatics, 2016Co-Authors: Shiyan Hu, Albert Y. ZomayaAbstract:The concept of smart home has recently gained significant popularity. Despite that it offers improved convenience and cost reduction, the prevailing smart home infrastructure suffers from vulnerability due to Cyberattacks. It is possible for hackers to launch Cyberattacks at the community level while causing a large area power system blackout through cascading effects. In this paper, the cascading impacts of two Cyberattacks on the predicted dynamic electricity pricing are analyzed. In the first cyberattack, the hacker manipulates the electricity price to form peak energy loads such that some transmission lines are overloaded. Those transmission lines are then tripped and the power system is separated into isolated islands due to the cascading effect. In the second cyberattack, the hacker manipulates the electricity price to increase the fluctuation of the energy load to interfere the frequency of the generators. The generators are then tripped by the protective procedures and cascading outages are induced in the transmission network. The existing technique only tackles overloading cyberattack while still suffering from the severe limitation in scalability. Therefore, based on partially observable Markov decision processes, a hierarchical detection framework exploring community decomposition and global policy optimization is proposed in this work. The simulation results demonstrate that our proposed hierarchical computing technique can effectively and efficiently detect those Cyberattacks, achieving the detection accuracy of above 98%, while improving the scalability.
-
DAC - Impact assessment of net metering on smart home cyberattack detection
Proceedings of the 52nd Annual Design Automation Conference on - DAC '15, 2015Co-Authors: Shiyan Hu, Yu Hu, Jie Wu, Xiaowei LiAbstract:Despite the increasing popularity of the smart home concept, such a technology is vulnerable to various security threats such as pricing Cyberattacks. There are some technical advances in developing detection and defense frameworks against those pricing Cyberattacks. However, none of them considers the impact of net metering, which allows the customers to sell the excessively generated renewable energy back to the grid. At a superficial glance, net metering seems to be irrelevant to the cybersecurity, while this paper demonstrates that its implication is actually profound. In this paper, we propose to analyze the impact of the net metering technology on the smart home pricing cyberattack detection. Net metering changes the grid energy demand, which is considered by the utility when designing the guideline price. Thus, cyberattack detection is compromised if this impact is not considered. It motivates us to develop a new smart home pricing cyberattack detection framework which judiciously integrates the net metering technology with the short/long term detection. The simulation results demonstrate that our new framework can significantly improve the detection accuracy from 65.95% to 95.14% compared to the state-of-art detection technique.
-
Vulnerability assessment and defense technology for smart home cybersecurity considering pricing Cyberattacks
IEEE ACM International Conference on Computer-Aided Design Digest of Technical Papers ICCAD, 2015Co-Authors: Shiyan Hu, Tsung-yi HoAbstract:Smart home, which controls the end use of the power grid, has become a critical component in the smart grid infrastructure. In a smart home system, the advanced metering infrastructure (AMI) is used to connect smart meters with the power system and the communication system of a smart grid. The electricity pricing information is transmitted from the utility to the local community, and then broadcast through wired or wireless networks to each smart meter within AMI. In this work, the vulnerability of the above process is assessed. Two closely related pricing Cyberattacks which manipulate the guideline electricity prices received at smart meters are considered and they aim at reducing the expense of the cyberattacker and increasing the peak energy usage in the local community. A countermeasure technique which uses support vector regression and impact difference for detecting anomaly pricing is then proposed. These pricing Cyberattacks explore the interdependance between the transmitted electricity pricing in the communication system and the energy load in the power system, which are the first such cyber-attacks in the smart home context. Our simulation results demonstrate that the pricing cyberattack can reduce the attacker's bill by 34.3% at the cost of the increase of others' bill by 7.9% on average. In addition, the pricing cyberattack can unbalance the energy load of the local power system as it increases the peak to average ratio by 35.7%. Furthermore, our simulation results show that the proposed countermeasure technique can effectively detect the electricity pricing manipulation.
Tsung-yi Ho - One of the best experts on this subject based on the ideXlab platform.
-
Leveraging Strategic Detection Techniques for Smart Home Pricing Cyberattacks
IEEE Transactions on Dependable and Secure Computing, 2016Co-Authors: Shiyan Hu, Tsung-yi HoAbstract:In this work, the vulnerability of the electricity pricing model in the smart home system is assessed. Two closely related pricing Cyberattacks which manipulate the guideline electricity prices received at smart meters are considered and they aim at reducing the expense of the cyberattacker and increasing the peak energy usage in the local community. A single event detection technique which uses support vector regression and impact difference for detecting anomaly pricing is proposed. The detection capability of such a technique is still limited since it does not model the long term impact of pricing Cyberattacks. This motivates us to develop a partially observable Markov decision process based detection algorithm, which has the ingredients such as reward expectation and policy transfer graph to account for the cumulative impact and the potential future impact due to pricing Cyberattacks. Our simulation results demonstrate that the pricing cyberattack can reduce the cyberattacker's bill by 34.3 percent at cost of the increase of others’ bill by 7.9 percent, and increase the peak to average ratio (PAR) by 35.7 percent. Furthermore, the proposed long term detection technique has the detection accuracy of more than 97 percent with significant reduction in PAR and bill compared to repeatedly using the single event detection technique.
-
Vulnerability assessment and defense technology for smart home cybersecurity considering pricing Cyberattacks
IEEE ACM International Conference on Computer-Aided Design Digest of Technical Papers ICCAD, 2015Co-Authors: Shiyan Hu, Tsung-yi HoAbstract:Smart home, which controls the end use of the power grid, has become a critical component in the smart grid infrastructure. In a smart home system, the advanced metering infrastructure (AMI) is used to connect smart meters with the power system and the communication system of a smart grid. The electricity pricing information is transmitted from the utility to the local community, and then broadcast through wired or wireless networks to each smart meter within AMI. In this work, the vulnerability of the above process is assessed. Two closely related pricing Cyberattacks which manipulate the guideline electricity prices received at smart meters are considered and they aim at reducing the expense of the cyberattacker and increasing the peak energy usage in the local community. A countermeasure technique which uses support vector regression and impact difference for detecting anomaly pricing is then proposed. These pricing Cyberattacks explore the interdependance between the transmitted electricity pricing in the communication system and the energy load in the power system, which are the first such cyber-attacks in the smart home context. Our simulation results demonstrate that the pricing cyberattack can reduce the attacker's bill by 34.3% at the cost of the increase of others' bill by 7.9% on average. In addition, the pricing cyberattack can unbalance the energy load of the local power system as it increases the peak to average ratio by 35.7%. Furthermore, our simulation results show that the proposed countermeasure technique can effectively detect the electricity pricing manipulation.
Albert Y. Zomaya - One of the best experts on this subject based on the ideXlab platform.
-
The Hierarchical Smart Home Cyberattack Detection Considering Power Overloading and Frequency Disturbance
IEEE Transactions on Industrial Informatics, 2016Co-Authors: Shiyan Hu, Albert Y. ZomayaAbstract:The concept of smart home has recently gained significant popularity. Despite that it offers improved convenience and cost reduction, the prevailing smart home infrastructure suffers from vulnerability due to Cyberattacks. It is possible for hackers to launch Cyberattacks at the community level while causing a large area power system blackout through cascading effects. In this paper, the cascading impacts of two Cyberattacks on the predicted dynamic electricity pricing are analyzed. In the first cyberattack, the hacker manipulates the electricity price to form peak energy loads such that some transmission lines are overloaded. Those transmission lines are then tripped and the power system is separated into isolated islands due to the cascading effect. In the second cyberattack, the hacker manipulates the electricity price to increase the fluctuation of the energy load to interfere the frequency of the generators. The generators are then tripped by the protective procedures and cascading outages are induced in the transmission network. The existing technique only tackles overloading cyberattack while still suffering from the severe limitation in scalability. Therefore, based on partially observable Markov decision processes, a hierarchical detection framework exploring community decomposition and global policy optimization is proposed in this work. The simulation results demonstrate that our proposed hierarchical computing technique can effectively and efficiently detect those Cyberattacks, achieving the detection accuracy of above 98%, while improving the scalability.
Kenneth Rohde - One of the best experts on this subject based on the ideXlab platform.
-
Protecting smart grid automation systems against Cyberattacks
IEEE Transactions on Smart Grid, 2011Co-Authors: Dong Wei, Paul M. Skare, Mohsen Jafari, Yan Lu, Kenneth RohdeAbstract:The smart grid moves new power grid automation systems from being proprietary and closed to the current state of information technology (IT) which is highly interconnected and open. But open and interconnected automation platforms bring about major security challenges. The power grid automation network has inherent security risks due to the fact that the systems and applications for the power grid were originally designed without much consideration of cybersecurity. This paper first introduces scope and functionalities of power grid, its automation and control system, and communications. Potential Cyberattacks and their adverse impacts on power grid operation are discussed, a general SCADA cyberattack process is presented. This paper discusses the major challenges and strategies to protect smart grid against Cyberattacks and finally proposes a conceptual layered framework for protecting power grid automation systems against Cyberattacks without compromising timely availability of control and signal data. The proposed “bump-in-the-wire” approach also provides security protection for legacy systems which do not have enough computational power or memory space to perform security functionalities. The on-site system test of the developed prototype security system is briefly presented as well.
Michael D Fontaine - One of the best experts on this subject based on the ideXlab platform.
-
impact of Cyberattacks on safety and stability of connected and automated vehicle platoons under lane changes
Accident Analysis & Prevention, 2021Co-Authors: Zulqarnain H Khattak, Brian L Smith, Michael D FontaineAbstract:Connected and automated vehicles (CAVs) offer a huge potential to improve the operations and safety of transportation systems. However, the use of smart devices and communications in CAVs introduce new risks. CAVs would leverage vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication, thus providing additional system access points compared to traditional systems. Automation makes these systems more vulnerable and increases the consequences of Cyberattacks. This study utilizes an infrastructure-based communication platform consisting of cooperative adaptive cruise control and lane control advisories developed by the authors to perform cyber risk assessment of CAVs. The study emulates three types of Cyberattacks (message falsification, dedicated denial of service, and spoofing attacks) in a representative traffic environment consisting of multiple CAV platoons and lane change events to analyze the safety and stability impacts of the Cyberattacks. Simulation experiments using VISSIM reveals that traffic stream and CAV string is unstable under all three types of Cyberattacks. The worst case is represented by the message falsification attack. Increases in volatility are observed over a no attack case, with variations increasing by an average of 43%-51% along with an increase of over 3000 crash conflicts. Similarly, lane change crash conflicts are observed to be more severe compared to rear end crash conflicts, showing a higher probability of severe injuries. Further, the case of slight cyberattack on a single CAV also creates significant disruption in the traffic stream. Analysis of variance (ANOVA) reveals the statistical significance of the results. These results pave the way for future design of secure systems from a monitoring perspective.
