The Experts below are selected from a list of 180 Experts worldwide ranked by ideXlab platform
Yan Meng - One of the best experts on this subject based on the ideXlab platform.
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IROS - A decentralized multi-robot system for Intruder detection in security defense
2010 IEEE RSJ International Conference on Intelligent Robots and Systems, 2010Co-Authors: Yuyang Zhang, Yan MengAbstract:In security defense tasks, multiple robots need work cooperatively to detect offensive intrusion to protect some sensitive areas. In this paper, we propose a distributed algorithm for a multi-robot system with some static sensors. The system concept is that static sensors sense intrusions and act as a cueing sensor to an ensemble of robots. These robots in turn engage the Potential Intruder, performing surveillance and/or neutralization of the intrusion. To minimize the Intruder missing rate and average response time, a STAGS (Shame-level Task Allocation and Gap-based Self-deployment) method is proposed, which is a decentralized method without a central control unit. To further improve the system adaptability under dynamic environments, a multi-objective optimization (MOO) method is proposed to adjust the system parameters of STAGS. Extensive simulation results demonstrate the effectiveness and robustness of the proposed algorithm in a dynamic Intruder detection task.
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a decentralized multi robot system for Intruder detection in security defense
Intelligent Robots and Systems, 2010Co-Authors: Yuyang Zhang, Yan MengAbstract:In security defense tasks, multiple robots need work cooperatively to detect offensive intrusion to protect some sensitive areas. In this paper, we propose a distributed algorithm for a multi-robot system with some static sensors. The system concept is that static sensors sense intrusions and act as a cueing sensor to an ensemble of robots. These robots in turn engage the Potential Intruder, performing surveillance and/or neutralization of the intrusion. To minimize the Intruder missing rate and average response time, a STAGS (Shame-level Task Allocation and Gap-based Self-deployment) method is proposed, which is a decentralized method without a central control unit. To further improve the system adaptability under dynamic environments, a multi-objective optimization (MOO) method is proposed to adjust the system parameters of STAGS. Extensive simulation results demonstrate the effectiveness and robustness of the proposed algorithm in a dynamic Intruder detection task.
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Dynamic multi-robot task allocation for Intruder detection
2009 International Conference on Information and Automation, 2009Co-Authors: Yuyang Zhang, Yan MengAbstract:In this paper, we propose an autonomous system consisting of cooperative mobile robots and Fiber Optic Sensors (FSs) for Intruder detection in perimeter defense tasks. The system concept is that FSs will sense perimeter intrusions and act as a cueing sensor to an ensemble of robots. These robots in turn engage the Potential Intruder, performing surveillance and/or neutralization of the intrusion. To minimize the Intruder missing rate and response time, some robots have to perform tracking of the Intruders while others have to deploy themselves dynamically to cover the protected area. Therefore, a shame-level based dynamic task allocation algorithm is proposed for Intruder tracking and allocation, and a gap-based algorithm is proposed for self-deployment of the remaining robots. Both algorithms are developed in a decentralized manner, which means each robot can only communicate with its local neighbors without any global controller unit. Extensive simulation results demonstrate the efficiency and flexibility of the proposed algorithm in a dynamic Intruder detection task.
Stefanos Gritzalis - One of the best experts on this subject based on the ideXlab platform.
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isam an iphone stealth airborne malware
Information Security Conference, 2011Co-Authors: Dimitrios Damopoulos, Georgios Kambourakis, Stefanos GritzalisAbstract:Modern and powerful mobile devices comprise an attractive target for any Potential Intruder or malicious code. The usual goal of an attack is to acquire user’s sensitive data or compromise the device so as to use it as a stepping stone (or bot) to unleash a number of attacks to other targets. In this paper, we focus on the popular iPhone device. We create a new stealth and airborne malware namely iSAM able to wirelessly infect and self-propagate to iPhone devices. iSAM incorporates six different malware mechanisms, and is able to connect back to the iSAM bot master server to update its programming logic or to obey commands and unleash a synchronized attack. Our analysis unveils the internal mechanics of iSAM and discusses the way all iSAM components contribute towards achieving its goals. Although iSAM has been specifically designed for iPhone it can be easily modified to attack any iOS-based device.
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SEC - iSAM: An iPhone Stealth Airborne Malware
IFIP Advances in Information and Communication Technology, 2011Co-Authors: Dimitrios Damopoulos, Georgios Kambourakis, Stefanos GritzalisAbstract:Modern and powerful mobile devices comprise an attractive target for any Potential Intruder or malicious code. The usual goal of an attack is to acquire user’s sensitive data or compromise the device so as to use it as a stepping stone (or bot) to unleash a number of attacks to other targets. In this paper, we focus on the popular iPhone device. We create a new stealth and airborne malware namely iSAM able to wirelessly infect and self-propagate to iPhone devices. iSAM incorporates six different malware mechanisms, and is able to connect back to the iSAM bot master server to update its programming logic or to obey commands and unleash a synchronized attack. Our analysis unveils the internal mechanics of iSAM and discusses the way all iSAM components contribute towards achieving its goals. Although iSAM has been specifically designed for iPhone it can be easily modified to attack any iOS-based device.
Alison Anderson - One of the best experts on this subject based on the ideXlab platform.
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Machine-independent audit trail analysis - a tool for continuous audit assurance
Intelligent Systems in Accounting Finance & Management, 2004Co-Authors: Peter Best, George M. Mohay, Alison AndersonAbstract:[Summary]: This paper reports the results of a research project which examines the feasibility of developing a machine-independent audit trail analyser (MIATA). MIATA is a knowledge based system which performs intelligent analysis of operating system audit trails. Such a system is proposed as a decision support tool for auditors when assessing the risk of unauthorised user activity in multi-usercomputer systems. It is also relevant to the provision of a continuous assurance service to clients by internal and external auditors. Monitoring user activity in system audit trails manually is impractical because of the vast quantity of events recorded in those audit trails. However, if done manually, an expert security auditor would be needed to look for 2 main types of events - user activity rejected by the system's security settings (failed actions) and user's behaving abnormally (e.g. unexpected changes in activity such as the purchasing clerk attempting to modify payroll data). A knowledge based system is suited to applications that require expertise to perform well-defined, yet complex, monitoring activities (e.g. controlling nuclear reactors and detecting intrusions in computer systems). To permit machine-independent intelligent audit trail analysis, an anomaly-detection approach is adopted. Time series forecasting methods are used to develop and maintain the user profile database (knowledge base) that allows identification of users with rejected behaviour as well as abnormal behaviour. The knowledge based system maintains this knowledge base and permits reporting on the Potential Intruder threats (summarized in Table 1). The intelligence of the MIATA system is its ability to handle audit trails from any system, its knowledge base capturing rejected user activity and detecting anomalous activity, and its reporting capabilities focusing on known methods of intrusion. MIATA also updates user profiles and forecasts of behaviour on a daily basis. As such, it also 'learns' from changes in user behaviour. The feasibility of generating machine-independent audit trail records, and the applicability of the anomaly-detection approach and time series forecasting methods are demonstrated using three case studies. These results support the proposal that developing a machine-independent audit trail analyser is feasible. Such a system will be an invaluable aid to an auditor in detecting Potential computer intrusions and monitoring user activity.
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Machine-independent audit trail analysis—a tool for continuous audit assurance: Research Articles
International Journal of Intelligent Systems in Accounting Finance & Management, 2004Co-Authors: Peter Best, George M. Mohay, Alison AndersonAbstract:This paper reports the results of a research project which examines the feasibility of developing a machine-independent audit trail analyser (MIATA). MIATA is a knowledge-based system which performs intelligent analysis of operating system audit trails. Such a system is proposed as a decision support tool for auditors when assessing the risk of unauthorized user activity in multi-user computer systems. It is also relevant to the provision of a continuous assurance service to clients by internal and external auditors.Monitoring user activity in system audit trails manually is impractical because of the vast quantity of events recorded in those audit trails. However, if done manually, an expert security auditor would be needed to look for two main types of events—user activity rejected by the system's security settings (failed actions) and users behaving abnormally (e.g. unexpected changes in activity such as the purchasing clerk attempting to modify payroll data). A knowledge-based system is suited to applications that require expertise to perform well-defned, yet complex, monitoring activities (e.g. controlling nuclear reactors and detecting intrusions in computer systems).To permit machine-independent intelligent audit trail analysis, an anomaly-detection approach is adopted. Time series forecasting methods are used to develop and maintain the user profle database (knowledge base) that allows identifcation of users with rejected behaviour as well as abnormal behaviour. The knowledge-based system maintains this knowledge base and permits reporting on the Potential Intruder threats (summarized in Table I).The intelligence of the MIATA system is its ability to handle audit trails from any system, its knowledge base capturing rejected user activity and detecting anomalous activity, and its reporting capabilities focusing on known methods of intrusion. MIATA also updates user profles and forecasts of behaviour on a daily basis. As such, it also ‘learns’ from changes in user behaviour.The feasibility of generating machine-independent audit trail records, and the applicability of the anomaly-detection approach and time series forecasting methods, are demonstrated using three case studies. These results support the proposal that developing a machine-independent audit trail analyser is feasible. Such a system will be an invaluable aid to an auditor in detecting Potential computer intrusions and monitoring user activity. Copyright © 2004 John Wiley & Sons, Ltd.
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Machine-independent audit trail analysis – a decision support tool for continuous audit assurance
2004Co-Authors: Peter Best, George M. Mohay, Alison AndersonAbstract:This paper reports the results of a research project which examines the feasibility of developing a machine-independent audit trail analyser (MIATA). MIATA is a knowledge based system which performs intelligent analysis of operating system audit trails. Such a system is proposed as a decision support tool for auditors when assessing the risk of unauthorised user activity in multi-user computer systems. It is also relevant to the provision of a continuous assurance service to clients by internal and external auditors. Monitoring user activity in system audit trails manually is impractical because of the vast quantity of events recorded in those audit trails. However, if done manually, an expert security auditor would be needed to look for 2 main types of events - user activity rejected by the system's security settings (failed actions) and user's behaving abnormally (e.g. unexpected changes in activity such as the purchasing clerk attempting to modify payroll data). A knowledge based system is suited to applications that require expertise to perform well-defined, yet complex, monitoring activities (e.g. controlling nuclear reactors and detecting intrusions in computer systems). To permit machine-independent intelligent audit trail analysis, an anomaly-detection approach is adopted. Time series forecasting methods are used to develop and maintain the user profile database (knowledge base) that allows identification of users with rejected behaviour as well as abnormal behaviour. The knowledge based system maintains this knowledge base and permits reporting on the Potential Intruder threats (summarized in Table 1). The intelligence of the MIATA system is its ability to handle audit trails from any system, its knowledge base capturing rejected user activity and detecting anomalous activity, and its reporting capabilities focusing on known methods of intrusion. MIATA also updates user profiles and forecasts of behaviour on a daily basis. As such, it also 'learns' from changes in user behaviour. The feasibility of generating machine-independent audit trail records, and the applicability of the anomaly-detection approach and time series forecasting methods are demonstrated using three case studies. These results support the proposal that developing a machine-independent audit trail analyser is feasible. Such a system will be an invaluable aid to an auditor in detecting Potential computer intrusions and monitoring user activity.
Bo Feng - One of the best experts on this subject based on the ideXlab platform.
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iBotGuard: an Internet-based Intelligent Robot security system using Invariant Face Recognition against Intruder
IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews), 2005Co-Authors: Meng Wang, Bo FengAbstract:One crucial application of intelligent robotic systems is remote surveillance using a security robot. A fundamental need in security is the ability to automatically verify an Intruder into a secure or restricted area, to alert remote security personnel, and then to enable them to track the Intruder. In this article, we propose an Internet-based security robot system. The face recognition approach possesses "invariant" recognition characteristics, including face recognition where facial expressions, viewing perspectives, three-dimensional poses, individual appearance, and lighting vary and occluding structures are present. The experiment uses a 33.6-kb/s modem Internet connection to successfully remotely control a mobile robot, proving that the streaming technology-based approach greatly improves the "sensibility" of robot teleoperation. This improvement ensures that security personnel can effectively and at low cost use the Internet to remotely control a mobile robot to track and identify a Potential Intruder.
Yuyang Zhang - One of the best experts on this subject based on the ideXlab platform.
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IROS - A decentralized multi-robot system for Intruder detection in security defense
2010 IEEE RSJ International Conference on Intelligent Robots and Systems, 2010Co-Authors: Yuyang Zhang, Yan MengAbstract:In security defense tasks, multiple robots need work cooperatively to detect offensive intrusion to protect some sensitive areas. In this paper, we propose a distributed algorithm for a multi-robot system with some static sensors. The system concept is that static sensors sense intrusions and act as a cueing sensor to an ensemble of robots. These robots in turn engage the Potential Intruder, performing surveillance and/or neutralization of the intrusion. To minimize the Intruder missing rate and average response time, a STAGS (Shame-level Task Allocation and Gap-based Self-deployment) method is proposed, which is a decentralized method without a central control unit. To further improve the system adaptability under dynamic environments, a multi-objective optimization (MOO) method is proposed to adjust the system parameters of STAGS. Extensive simulation results demonstrate the effectiveness and robustness of the proposed algorithm in a dynamic Intruder detection task.
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a decentralized multi robot system for Intruder detection in security defense
Intelligent Robots and Systems, 2010Co-Authors: Yuyang Zhang, Yan MengAbstract:In security defense tasks, multiple robots need work cooperatively to detect offensive intrusion to protect some sensitive areas. In this paper, we propose a distributed algorithm for a multi-robot system with some static sensors. The system concept is that static sensors sense intrusions and act as a cueing sensor to an ensemble of robots. These robots in turn engage the Potential Intruder, performing surveillance and/or neutralization of the intrusion. To minimize the Intruder missing rate and average response time, a STAGS (Shame-level Task Allocation and Gap-based Self-deployment) method is proposed, which is a decentralized method without a central control unit. To further improve the system adaptability under dynamic environments, a multi-objective optimization (MOO) method is proposed to adjust the system parameters of STAGS. Extensive simulation results demonstrate the effectiveness and robustness of the proposed algorithm in a dynamic Intruder detection task.
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Dynamic multi-robot task allocation for Intruder detection
2009 International Conference on Information and Automation, 2009Co-Authors: Yuyang Zhang, Yan MengAbstract:In this paper, we propose an autonomous system consisting of cooperative mobile robots and Fiber Optic Sensors (FSs) for Intruder detection in perimeter defense tasks. The system concept is that FSs will sense perimeter intrusions and act as a cueing sensor to an ensemble of robots. These robots in turn engage the Potential Intruder, performing surveillance and/or neutralization of the intrusion. To minimize the Intruder missing rate and response time, some robots have to perform tracking of the Intruders while others have to deploy themselves dynamically to cover the protected area. Therefore, a shame-level based dynamic task allocation algorithm is proposed for Intruder tracking and allocation, and a gap-based algorithm is proposed for self-deployment of the remaining robots. Both algorithms are developed in a decentralized manner, which means each robot can only communicate with its local neighbors without any global controller unit. Extensive simulation results demonstrate the efficiency and flexibility of the proposed algorithm in a dynamic Intruder detection task.