The Experts below are selected from a list of 1431 Experts worldwide ranked by ideXlab platform
Xiaoming Wang - One of the best experts on this subject based on the ideXlab platform.
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bifurcation analysis of a delay reaction diffusion Malware Propagation model with feedback control
Communications in Nonlinear Science and Numerical Simulation, 2015Co-Authors: Linhe Zhu, Hongyong Zhao, Xiaoming WangAbstract:Abstract With the rapid development of network information technology, information networks security has become a very critical issue in our work and daily life. This paper attempts to develop a delay reaction–diffusion model with a state feedback controller to describe the process of Malware Propagation in mobile wireless sensor networks (MWSNs). By analyzing the stability and Hopf bifurcation, we show that the state feedback method can successfully be used to control unstable steady states or periodic oscillations. Moreover, formulas for determining the properties of the bifurcating periodic oscillations are derived by applying the normal form method and center manifold theorem. Finally, we conduct extensive simulations on large-scale MWSNs to evaluate the proposed model. Numerical evidences show that the linear term of the controller is enough to delay the onset of the Hopf bifurcation and the properties of the bifurcation can be regulated to achieve some desirable behaviors by choosing the appropriate higher terms of the controller. Furthermore, we obtain that the spatial–temporal dynamic characteristics of Malware Propagation are closely related to the rate constant for nodes leaving the infective class for recovered class and the mobile behavior of nodes.
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stability and bifurcation analysis in a delayed reaction diffusion Malware Propagation model
Computers & Mathematics With Applications, 2015Co-Authors: Linhe Zhu, Hongyong Zhao, Xiaoming WangAbstract:Mobile wireless sensor networks (MWSNs) have become an area of intense research activity due to technical advances in sensors, wireless communications and networking, and signal processing. Many applications, including environment monitoring, battlefield surveillance, and urban search and rescue especially in hazardous situations, are envisaged. However, MWSNs may be vulnerable to malicious interference because of the large-scale characteristics. When a contaminated node communications with its neighbors, multiple copies of the Malware are transmitted to its neighbors, which may destroy, block regular communications, or even damage the integrity of regular data packets. Modeling spatial distribution of Malware Propagation over time is the first step to predict the trend of Malware Propagation in MWSNs. We propose a novel wireless Malware Propagation model with the discrete time delay based on reaction-diffusion equations in mobile wireless sensor networks, and study its dynamic behaviors. By analyzing the stability and Hopf bifurcation of the equilibrium of our model, we search for the sufficient conditions, which leads to the Malware Propagation disappears or continues. Furthermore, we demonstrate that oscillations in this model occur through the destabilization of the stationary solution at a Hopf bifurcation point. And formulas for determining the stability of the bifurcating periodic oscillations are derived by applying the normal form method and center manifold theorem. Finally, we conduct extensive simulations on large-scale MWSNs to evaluate the proposed model. Numerical evidence shows that the spatial-temporal dynamic characteristics of Malware Propagation in MWSNs are closely related to the packet transmission rate, the communication rang and the mobile behavior of nodes.
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reaction diffusion modeling of Malware Propagation in mobile wireless sensor networks
Science in China Series F: Information Sciences, 2013Co-Authors: Xiaoming Wang, Zaobo He, Xueqing ZhaoAbstract:Mobile Wireless Sensor Networks (MWSNs) are employed in many fields, such as intelligent transportation, community health monitoring, and animal behavior monitoring. However, MWSNs may be vulnerable to malicious interference because of the large-scale characteristics. One of the threats is to inject Malware into some nodes, especially mobile nodes. When a contaminated node communicates with its neighbors, multiple copies of the Malware are transmitted to its neighbors, which may destroy nodes, block regular communications, or even damage the integrity of regular data packets. This work develops a modeling framework which mathematically characterizes the process of Malware Propagation in MWSNs based on the theory of reaction-diffusion equation. Our proposed model can efficiently predict the temporal dynamic behavior and spatial distribution of Malware Propagation over time, so that targeted immunization measures can be taken on infected nodes, whereas most of the existing models for Malware Propagation can only predict the temporal dynamic behavior rather than the spatial distribution of Malware Propagation over time. We conduct extensive simulations on large-scale MWSNs to evaluate the proposed model. The simulation results indicate that the proposed model and method are efficient, and that the mobile speed, communication range, and packet transmission rate of nodes are the main factors affecting Malware Propagation in MWSNs.
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a spatial temporal model for the Malware Propagation in mwsns based on the reaction diffusion equations
Web-Age Information Management, 2012Co-Authors: Xiaoming WangAbstract:Mobile wireless sensor networks (MWSNs) have important applications in many fields. However, MWSNs are becoming attacked targets due to its large-scale applications. The focus of this work is to develop a modeling framework and mathematical model for characterizing the process of Malware Propagation in MWSNs from two aspects of time and space. It is important to understand Malware’s potential damages, and to develop counter-measures. Firstly, we develop a formal model for describing the process of Malware Propagation in MWSNs based on the reaction-diffusion equations. Then, we derive the threshold for predicting whether a Malware propagates or not in MWSNs as time passes. Finally, we propose the spatial pattern based method to analyze and predict the spatial distribution of nodes infected by Malwares as time passes. Both theoretical analysis and extensive simulation results show that the movement speed of nodes and the communication radius of nodes have a significant effect on the Malware Propagation in MWSNs.
Sajal K Das - One of the best experts on this subject based on the ideXlab platform.
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an epidemic theoretic framework for vulnerability analysis of broadcast protocols in wireless sensor networks
IEEE Transactions on Mobile Computing, 2009Co-Authors: Yonghe Liu, Sajal K DasAbstract:While multi-hop broadcast protocols, such as Trickle, Deluge and MNP, have gained tremendous popularity as a means for fast and convenient Propagation of data/code in large scale wireless sensor networks, they can, unfortunately, serve as potential platforms for virus spreading if the security is breached. To understand the vulnerability of such protocols and design defense mechanisms against piggy-backed virus attacks, it is critical to investigate the Propagation process of these protocols in terms of their speed and reachability. In this paper, we propose a general framework based on the principles of epidemic theory, for vulnerability analysis of current broadcast protocols in wireless sensor networks. In particular, we develop a common mathematical model for the Propagation that incorporates important parameters derived from the communication patterns of the protocol under test. Based on this model, we analyze the Propagation rate and the extent of spread of a Malware over typical broadcast protocols proposed in the literature. The overall result is an approximate but convenient tool to characterize a broadcast protocol in terms of its vulnerability to Malware Propagation. We have also performed extensive simulations which have validated our model.
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an epidemic theoretic framework for evaluating broadcast protocols in wireless sensor networks
Mobile Adhoc and Sensor Systems, 2007Co-Authors: Yonghe Liu, Sajal K DasAbstract:While multi-hop broadcast protocols, such as Trickle, Deluge and MNP, have gained tremendous popularity as a means for fast and convenient Propagation of data/code in large scale wireless sensor networks, they can, unfortunately, serve as potential platforms for virus Propagation if the security is breached. To understand the vulnerability of such protocols and design defense mechanisms against piggy-backed virus attacks, it is critical to investigate the Propagation process of these protocols in terms of their speed and reachability. In this paper, we propose a general framework based on the principles of epidemic theory, for vulnerability analysis of current broadcast protocols in wireless sensor networks. In particular, we develop a common mathematical model for the Propagation that incorporates important parameters derived from the communication patterns of the protocol under test. Based on this model, we analyze the Propagation rate and the extent of spread of a Malware over typical broadcast protocols proposed in the literature. The overall result is an approximate but convenient tool to characterize a broadcast protocol in terms of its vulnerability to Malware Propagation. We have also performed extensive simulations which have validated our model.
Nan Li - One of the best experts on this subject based on the ideXlab platform.
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Malware Propagation in Online Social Networks: Nature, Dynamics, and Defense Implications
ACM Symposium on Information Computer and Communications Security, 2011Co-Authors: Guanhua Yan, Guanling Chen, Stephan Eidenbenz, Nan LiAbstract:Online social networks, which have been expanding at a blistering speed recently, have emerged as a popular communication infrastructure for Internet users. Meanwhile, Malware that specifically target these online social networks are also on the rise. In this work, we aim to investigate the characteristics of Malware Propagation in online social networks. Our study is based on a dataset collected from a real-world location-based online social network, which includes not only the social graph formed by its users but also the users' activity events. We analyze the social structure and user activity patterns of this network, and confirm that it is a typical online social network, suggesting that conclusions drawn from this specific network can be translated to other online social networks. We use extensive trace-driven simulation to study the impact of initial infection, user click probability, social structure, and activity patterns on Malware Propagation in online social networks. We also investigate the performance of a few user-oriented and server-oriented defense schemes against Malware spreading in online social networks and identify key factors that affect their effectiveness. We believe that this comprehensive study has deepened our understanding of the nature of online social network Malware and also shed light on how to defend against them effectively. Copyright 2011 ACM.
Guanhua Yan - One of the best experts on this subject based on the ideXlab platform.
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Malware Propagation in Online Social Networks: Nature, Dynamics, and Defense Implications
ACM Symposium on Information Computer and Communications Security, 2011Co-Authors: Guanhua Yan, Guanling Chen, Stephan Eidenbenz, Nan LiAbstract:Online social networks, which have been expanding at a blistering speed recently, have emerged as a popular communication infrastructure for Internet users. Meanwhile, Malware that specifically target these online social networks are also on the rise. In this work, we aim to investigate the characteristics of Malware Propagation in online social networks. Our study is based on a dataset collected from a real-world location-based online social network, which includes not only the social graph formed by its users but also the users' activity events. We analyze the social structure and user activity patterns of this network, and confirm that it is a typical online social network, suggesting that conclusions drawn from this specific network can be translated to other online social networks. We use extensive trace-driven simulation to study the impact of initial infection, user click probability, social structure, and activity patterns on Malware Propagation in online social networks. We also investigate the performance of a few user-oriented and server-oriented defense schemes against Malware spreading in online social networks and identify key factors that affect their effectiveness. We believe that this comprehensive study has deepened our understanding of the nature of online social network Malware and also shed light on how to defend against them effectively. Copyright 2011 ACM.
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Cybersim: Geographic, temporal, and organizational dynamics of Malware Propagation
Proceedings - Winter Simulation Conference, 2010Co-Authors: Nandakishore Santhi, Guanhua Yan, Stephan EidenbenzAbstract:Cyber-infractions into a nation's strategic security envelope pose a constant and daunting challenge. We present the modular CyberSim tool which has been developed in response to the need to realistically simulate at a national level, software vulnerabilities and resulting Malware Propagation in online social networks. CyberSim suite (a) can generate realistic scale-free networks from a database of geocoordinated computers to closely model social networks arising from personal and business email contacts and online communities; (b) maintains for each host a list of installed software, along with the latest published vulnerabilities; (c) allows to designate initial nodes where Malware gets introduced; (d) simulates using distributed discrete event-driven technology, the spread of Malware exploiting a specific vulnerability, with packet delay and user online behavior models; (e) provides a graphical visualization of spread of infection, its severity, businesses affected etc to the analyst. We present sample simulations on a national level network with millions of computers.
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blue watchdog detecting bluetooth worm Propagation in public areas
Dependable Systems and Networks, 2009Co-Authors: Guanhua Yan, Stephan Eidenbenz, Leticia Cuellar, Nicolas W HengartnerAbstract:The rising popularity of mobile devices, such as cellular phones and PDAs, has made them a lucrative playground for mobile Malware Propagation. One common infection vector exploited by these mobile Malware is Bluetooth. In this paper, we propose an architecture called Blue-Watchdog that detects Bluetooth worm Propagation in public areas based on statistical methods. To achieve fast and accurate Bluetooth worm detection, Blue-Watchdog monitors abrupt changes of average paging rate per Bluetooth device from both temporal and temporal-spatial perspectives. The temporal scheme relies on the CUSUM (Cumulative Sum) sequential test together with the generalized likelihood ratio (GLR), and the temporal-spatial scheme aims to identify spatial regions with abnormally frequent paging attempts. Experimental results show that Blue-Watchdog not only has low false alarm rates, but also effectively detects Bluetooth worms that spread quickly in areas where Bluetooth devices are greatly mixed due to high mobility and also those that propagate relatively slowly in a spatially constrained fashion.
Yonghe Liu - One of the best experts on this subject based on the ideXlab platform.
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an epidemic theoretic framework for vulnerability analysis of broadcast protocols in wireless sensor networks
IEEE Transactions on Mobile Computing, 2009Co-Authors: Yonghe Liu, Sajal K DasAbstract:While multi-hop broadcast protocols, such as Trickle, Deluge and MNP, have gained tremendous popularity as a means for fast and convenient Propagation of data/code in large scale wireless sensor networks, they can, unfortunately, serve as potential platforms for virus spreading if the security is breached. To understand the vulnerability of such protocols and design defense mechanisms against piggy-backed virus attacks, it is critical to investigate the Propagation process of these protocols in terms of their speed and reachability. In this paper, we propose a general framework based on the principles of epidemic theory, for vulnerability analysis of current broadcast protocols in wireless sensor networks. In particular, we develop a common mathematical model for the Propagation that incorporates important parameters derived from the communication patterns of the protocol under test. Based on this model, we analyze the Propagation rate and the extent of spread of a Malware over typical broadcast protocols proposed in the literature. The overall result is an approximate but convenient tool to characterize a broadcast protocol in terms of its vulnerability to Malware Propagation. We have also performed extensive simulations which have validated our model.
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an epidemic theoretic framework for evaluating broadcast protocols in wireless sensor networks
Mobile Adhoc and Sensor Systems, 2007Co-Authors: Yonghe Liu, Sajal K DasAbstract:While multi-hop broadcast protocols, such as Trickle, Deluge and MNP, have gained tremendous popularity as a means for fast and convenient Propagation of data/code in large scale wireless sensor networks, they can, unfortunately, serve as potential platforms for virus Propagation if the security is breached. To understand the vulnerability of such protocols and design defense mechanisms against piggy-backed virus attacks, it is critical to investigate the Propagation process of these protocols in terms of their speed and reachability. In this paper, we propose a general framework based on the principles of epidemic theory, for vulnerability analysis of current broadcast protocols in wireless sensor networks. In particular, we develop a common mathematical model for the Propagation that incorporates important parameters derived from the communication patterns of the protocol under test. Based on this model, we analyze the Propagation rate and the extent of spread of a Malware over typical broadcast protocols proposed in the literature. The overall result is an approximate but convenient tool to characterize a broadcast protocol in terms of its vulnerability to Malware Propagation. We have also performed extensive simulations which have validated our model.