Heat Loss Quantification (HLQ) is a key step in improving the thermal performance of buildings. A... more Heat Loss Quantification (HLQ) is a key step in improving the thermal performance of buildings. Affordable infrared (IR) cameras mounted on an unmanned aerial vehicle (UAV) make low cost heat loss quantification using IR imaging feasible. This technique also facilitates capturing the heat loss information in hard-to-reach areas using UAVs. In this paper, a series of pre-processing steps such as dominant color isolation (DCI), background elimination and key point identification as part of the heat loss quantification are discussed. The thermal transmittance (or the U-value) of various buildings at the University of North Dakota, in Grand Forks, ND, are estimated from the images captured by aerial thermal cameras mounted on UAVs.
Proceedings of the 2nd International Conference on Networking, Information Systems & Security - NISS19, 2019
Smart grid is an alternative solution of the conventional power grid which harnesses the power of... more Smart grid is an alternative solution of the conventional power grid which harnesses the power of the information technology to save the energy and meet today's' environment requirements. Due to the inherent vulnerabilities in the information technology, the smart grid is exposed to a wide variety of threats that could be translated into cyber-attacks. In this paper, we develop a deep learning-based intrusion detection system to defend against cyber-attacks in the advanced metering infrastructure network. The proposed machine learning approach is trained and tested extensively on an empirical industrial dataset which is composed of several attack' categories including the scanning, buffer overflow, and denial of service attacks. Then, an experimental comparison in terms of detection accuracy is conducted to evaluate the performance of the proposed approach with Naïve Bayes, Support Vector Machine, and Random Forest. The obtained results suggest that the proposed approaches produce optimal results comparing to the other algorithms. Finally, we propose a network architecture to deploy the proposed anomalybased intrusion detection system across the Advanced Metering Infrastructure network. In addition, we propose a network security architecture composed of two types of Intrusion detection system types, Host and Network-based, deployed across the Advanced Metering Infrastructure network to inspect the traffic and detect the malicious one at all the levels.
Smart grid is an emerging and promising technology. It uses the power of information technologies... more Smart grid is an emerging and promising technology. It uses the power of information technologies to deliver intelligently the electrical power to customers, and it allows the integration of green technology to meet the environmental requirements. Unfortunately, information technologies have inherent vulnerabilities and weaknesses that expose the smart grid to a wide variety of security risks. The Intrusion detection system (IDS) plays an important role in securing smart grid networks and detecting malicious activity, yet it suffers from several limitations. Many research papers have been published to address these issues using several algorithms and techniques. Therefore, a detailed comparison between these algorithms is needed. This paper presents an overview of four data mining algorithms used by IDS in Smart Grid. A performance evaluation of these algorithms is conducted based on several metrics including the probability of detection, probability of false alarm, probability of m...
2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC), 2018
Spectrum sensing enables cognitive radio systems to detect unused portions of the radio spectrum ... more Spectrum sensing enables cognitive radio systems to detect unused portions of the radio spectrum and then use them while avoiding interferences to the primary users. Energy detection is one of the most used techniques for spectrum sensing because it does not require any prior information about the characteristics of the primary user signal. However, this technique does not distinguish between the signal and the noise. It has a low performance at low SNR, and the selection of the threshold becomes an issue because the noise is uncertain. The detection performance of this technique can be further improved using a dynamic selection of the sensing threshold. In this work, we investigate a dynamic selection of this threshold by measuring the power of noise present in the received signal using a blind technique. The proposed model was implemented and tested using GNU Radio software and USRP units. Our results show that the dynamic selection of the threshold based on measuring the noise level present in the received signal during the detection process increases the probability of detection and decreases the probability of false alarm compared to the ones of energy detection with a static threshold.
Cognitive radio technology addresses the problem of spectrum scarcity by allowing secondary users... more Cognitive radio technology addresses the problem of spectrum scarcity by allowing secondary users to use the vacant spectrum bands without causing interference to the primary users. However, several attacks could disturb the normal functioning of the cognitive radio network. Primary user emulation attacks are one of the most severe attacks in which a malicious user emulates the primary user signal characteristics to either prevent other legitimate secondary users from accessing the idle channels or causing harmful interference to the primary users. There are several proposed approaches to detect the primary user emulation attackers. However, most of these techniques assume that the primary user location is fixed, which does not make them valid when the primary user is mobile. In this paper, we propose a new approach based on the Kalman filter framework for detecting the primary user emulation attacks with a non-stationary primary user. Several experiments have been conducted and the advantages of the proposed approach are demonstrated through the simulation results.
Heat Loss Quantification (HLQ) is a key step in improving the thermal performance of buildings. A... more Heat Loss Quantification (HLQ) is a key step in improving the thermal performance of buildings. Affordable infrared (IR) cameras mounted on an unmanned aerial vehicle (UAV) make low cost heat loss quantification using IR imaging feasible. This technique also facilitates capturing the heat loss information in hard-to-reach areas using UAVs. In this paper, a series of pre-processing steps such as dominant color isolation (DCI), background elimination and key point identification as part of the heat loss quantification are discussed. The thermal transmittance (or the U-value) of various buildings at the University of North Dakota, in Grand Forks, ND, are estimated from the images captured by aerial thermal cameras mounted on UAVs.
Proceedings of the 2nd International Conference on Networking, Information Systems & Security - NISS19, 2019
Smart grid is an alternative solution of the conventional power grid which harnesses the power of... more Smart grid is an alternative solution of the conventional power grid which harnesses the power of the information technology to save the energy and meet today's' environment requirements. Due to the inherent vulnerabilities in the information technology, the smart grid is exposed to a wide variety of threats that could be translated into cyber-attacks. In this paper, we develop a deep learning-based intrusion detection system to defend against cyber-attacks in the advanced metering infrastructure network. The proposed machine learning approach is trained and tested extensively on an empirical industrial dataset which is composed of several attack' categories including the scanning, buffer overflow, and denial of service attacks. Then, an experimental comparison in terms of detection accuracy is conducted to evaluate the performance of the proposed approach with Naïve Bayes, Support Vector Machine, and Random Forest. The obtained results suggest that the proposed approaches produce optimal results comparing to the other algorithms. Finally, we propose a network architecture to deploy the proposed anomalybased intrusion detection system across the Advanced Metering Infrastructure network. In addition, we propose a network security architecture composed of two types of Intrusion detection system types, Host and Network-based, deployed across the Advanced Metering Infrastructure network to inspect the traffic and detect the malicious one at all the levels.
Smart grid is an emerging and promising technology. It uses the power of information technologies... more Smart grid is an emerging and promising technology. It uses the power of information technologies to deliver intelligently the electrical power to customers, and it allows the integration of green technology to meet the environmental requirements. Unfortunately, information technologies have inherent vulnerabilities and weaknesses that expose the smart grid to a wide variety of security risks. The Intrusion detection system (IDS) plays an important role in securing smart grid networks and detecting malicious activity, yet it suffers from several limitations. Many research papers have been published to address these issues using several algorithms and techniques. Therefore, a detailed comparison between these algorithms is needed. This paper presents an overview of four data mining algorithms used by IDS in Smart Grid. A performance evaluation of these algorithms is conducted based on several metrics including the probability of detection, probability of false alarm, probability of m...
2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC), 2018
Spectrum sensing enables cognitive radio systems to detect unused portions of the radio spectrum ... more Spectrum sensing enables cognitive radio systems to detect unused portions of the radio spectrum and then use them while avoiding interferences to the primary users. Energy detection is one of the most used techniques for spectrum sensing because it does not require any prior information about the characteristics of the primary user signal. However, this technique does not distinguish between the signal and the noise. It has a low performance at low SNR, and the selection of the threshold becomes an issue because the noise is uncertain. The detection performance of this technique can be further improved using a dynamic selection of the sensing threshold. In this work, we investigate a dynamic selection of this threshold by measuring the power of noise present in the received signal using a blind technique. The proposed model was implemented and tested using GNU Radio software and USRP units. Our results show that the dynamic selection of the threshold based on measuring the noise level present in the received signal during the detection process increases the probability of detection and decreases the probability of false alarm compared to the ones of energy detection with a static threshold.
Cognitive radio technology addresses the problem of spectrum scarcity by allowing secondary users... more Cognitive radio technology addresses the problem of spectrum scarcity by allowing secondary users to use the vacant spectrum bands without causing interference to the primary users. However, several attacks could disturb the normal functioning of the cognitive radio network. Primary user emulation attacks are one of the most severe attacks in which a malicious user emulates the primary user signal characteristics to either prevent other legitimate secondary users from accessing the idle channels or causing harmful interference to the primary users. There are several proposed approaches to detect the primary user emulation attackers. However, most of these techniques assume that the primary user location is fixed, which does not make them valid when the primary user is mobile. In this paper, we propose a new approach based on the Kalman filter framework for detecting the primary user emulation attacks with a non-stationary primary user. Several experiments have been conducted and the advantages of the proposed approach are demonstrated through the simulation results.
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Papers by Zakaria Mrabet