The Experts below are selected from a list of 30537 Experts worldwide ranked by ideXlab platform

Isabelle Chrisment - One of the best experts on this subject based on the ideXlab platform.

  • a distributed Monitoring strategy for detecting version number attacks in rpl based networks
    IEEE Transactions on Network and Service Management, 2017
    Co-Authors: Anthea Mayzaud, Remi Badonnel, Isabelle Chrisment
    Abstract:

    The Internet of Things is characterized by the large-scale deployment of low power and lossy networks (LLN), interconnecting pervasive objects. The routing protocol for LLN (RPL) protocol has been standardized by IETF to enable a lightweight and robust routing in these constrained networks. A versioning mechanism is incorporated into RPL in order to maintain an optimized topology. However, an attacker can exploit this mechanism to significantly damage the network and reduce its lifetime. After analyzing and comparing existing work, we propose in this paper a Monitoring strategy with dedicated algorithms for detecting such attacks and identifying the involved malicious Nodes. The performance of this solution is evaluated through extensive experiments, and its scalability is quantified with the support of a Monitoring Node placement optimization method.

  • Detecting Version Number Attacks in RPL-based Networks using a Distributed Monitoring Architecture
    2016
    Co-Authors: Anthea Mayzaud, Remi Badonnel, Isabelle Chrisment
    Abstract:

    The concept of Internet of Things involves the deployment of Low power and Lossy Networks (LLN) allowing communications among pervasive devices such as embedded sensors. The IETF designed the Routing Protocol for Low power and Lossy Networks (RPL) for supporting these constrained networks. Keeping in mind the different requirements of such networks, the protocol supports multiple routing topologies, called DODAGs, built using different objective functions, so as to optimize routing based on several metrics. A DODAG versioning system is incorporated into RPL in order to ensure an optimized topology. However, an attacker can exploit this mechanism to damage the network and reduce its lifetime. In this paper we propose a detection strategy based on a distributed Monitoring architecture with dedicated algorithms that is able to identify malicious Nodes performing such attacks in RPL- based environments. The performance of this solution is evaluated through extensive experiments and its scalability is quantified considering a Monitoring Node placement method.

Radha Poovendran - One of the best experts on this subject based on the ideXlab platform.

  • optimal jamming attack strategies and network defense policies in wireless sensor networks
    IEEE Transactions on Mobile Computing, 2010
    Co-Authors: Iordanis Koutsopoulos, Radha Poovendran
    Abstract:

    We consider a scenario where a sophisticated jammer jams an area in which a single-channel random-access-based wireless sensor network operates. The jammer controls the probability of jamming and the transmission range in order to cause maximal damage to the network in terms of corrupted communication links. The jammer action ceases when it is detected by the network (namely by a Monitoring Node), and a notification message is transferred out of the jammed region. The jammer is detected by employing an optimal detection test based on the percentage of incurred collisions. On the other hand, the network defends itself by computing the channel access probability to minimize the jamming detection plus notification time. The necessary knowledge of the jammer in order to optimize its benefit consists of knowledge about the network channel access probability and the number of neighbors of the monitor Node. Accordingly, the network needs to know the jamming probability of the jammer. We study the idealized case of perfect knowledge by both the jammer and the network about the strategy of each other and the case where the jammer and the network lack this knowledge. The latter is captured by formulating and solving optimization problems where the attacker and the network respond optimally to the worst-case or the average-case strategies of the other party. We also take into account potential energy constraints of the jammer and the network. We extend the problem to the case of multiple observers and adaptable jamming transmission range and propose a meaningful heuristic algorithm for an efficient jamming strategy. Our results provide valuable insights about the structure of the jamming problem and associated defense mechanisms and demonstrate the impact of knowledge as well as adoption of sophisticated strategies on achieving desirable performance.

  • optimal jamming attacks and network defense policies in wireless sensor networks
    IEEE International Conference Computer and Communications, 2007
    Co-Authors: Mingyan Li, Iordanis Koutsopoulos, Radha Poovendran
    Abstract:

    We consider a scenario where a sophisticated jammer jams an area in a single-channel wireless sensor network. The jammer controls the probability of jamming and transmission range to cause maximal damage to the network in terms of corrupted communication links. The jammer action ceases when it is detected by a Monitoring Node in the network, and a notification message is transferred out of the jamming region. The jammer is detected at a monitor Node by employing an optimal detection test based on the percentage of incurred collisions. On the other hand, the network computes channel access probability in an effort to minimize the jamming detection plus notification time. In order for the jammer to optimize its benefit, it needs to know the network channel access probability and number of neighbors of the monitor Node. Accordingly, the network needs to know the jamming probability of the jammer. We study the idealized case of perfect knowledge by both the jammer and the network about the strategy of one another, and the case where the jammer or the network lack this knowledge. The latter is captured by formulating and solving optimization problems, the solutions of which constitute best responses of the attacker or the network to the worst-case strategy of each other. We also take into account potential energy constraints of the jammer and the network. We extend the problem to the case of multiple observers and adaptable jamming transmission range and propose a intuitive heuristic jamming strategy for that case.

Anthea Mayzaud - One of the best experts on this subject based on the ideXlab platform.

  • a distributed Monitoring strategy for detecting version number attacks in rpl based networks
    IEEE Transactions on Network and Service Management, 2017
    Co-Authors: Anthea Mayzaud, Remi Badonnel, Isabelle Chrisment
    Abstract:

    The Internet of Things is characterized by the large-scale deployment of low power and lossy networks (LLN), interconnecting pervasive objects. The routing protocol for LLN (RPL) protocol has been standardized by IETF to enable a lightweight and robust routing in these constrained networks. A versioning mechanism is incorporated into RPL in order to maintain an optimized topology. However, an attacker can exploit this mechanism to significantly damage the network and reduce its lifetime. After analyzing and comparing existing work, we propose in this paper a Monitoring strategy with dedicated algorithms for detecting such attacks and identifying the involved malicious Nodes. The performance of this solution is evaluated through extensive experiments, and its scalability is quantified with the support of a Monitoring Node placement optimization method.

  • Detecting Version Number Attacks in RPL-based Networks using a Distributed Monitoring Architecture
    2016
    Co-Authors: Anthea Mayzaud, Remi Badonnel, Isabelle Chrisment
    Abstract:

    The concept of Internet of Things involves the deployment of Low power and Lossy Networks (LLN) allowing communications among pervasive devices such as embedded sensors. The IETF designed the Routing Protocol for Low power and Lossy Networks (RPL) for supporting these constrained networks. Keeping in mind the different requirements of such networks, the protocol supports multiple routing topologies, called DODAGs, built using different objective functions, so as to optimize routing based on several metrics. A DODAG versioning system is incorporated into RPL in order to ensure an optimized topology. However, an attacker can exploit this mechanism to damage the network and reduce its lifetime. In this paper we propose a detection strategy based on a distributed Monitoring architecture with dedicated algorithms that is able to identify malicious Nodes performing such attacks in RPL- based environments. The performance of this solution is evaluated through extensive experiments and its scalability is quantified considering a Monitoring Node placement method.

Iordanis Koutsopoulos - One of the best experts on this subject based on the ideXlab platform.

  • optimal jamming attack strategies and network defense policies in wireless sensor networks
    IEEE Transactions on Mobile Computing, 2010
    Co-Authors: Iordanis Koutsopoulos, Radha Poovendran
    Abstract:

    We consider a scenario where a sophisticated jammer jams an area in which a single-channel random-access-based wireless sensor network operates. The jammer controls the probability of jamming and the transmission range in order to cause maximal damage to the network in terms of corrupted communication links. The jammer action ceases when it is detected by the network (namely by a Monitoring Node), and a notification message is transferred out of the jammed region. The jammer is detected by employing an optimal detection test based on the percentage of incurred collisions. On the other hand, the network defends itself by computing the channel access probability to minimize the jamming detection plus notification time. The necessary knowledge of the jammer in order to optimize its benefit consists of knowledge about the network channel access probability and the number of neighbors of the monitor Node. Accordingly, the network needs to know the jamming probability of the jammer. We study the idealized case of perfect knowledge by both the jammer and the network about the strategy of each other and the case where the jammer and the network lack this knowledge. The latter is captured by formulating and solving optimization problems where the attacker and the network respond optimally to the worst-case or the average-case strategies of the other party. We also take into account potential energy constraints of the jammer and the network. We extend the problem to the case of multiple observers and adaptable jamming transmission range and propose a meaningful heuristic algorithm for an efficient jamming strategy. Our results provide valuable insights about the structure of the jamming problem and associated defense mechanisms and demonstrate the impact of knowledge as well as adoption of sophisticated strategies on achieving desirable performance.

  • optimal jamming attacks and network defense policies in wireless sensor networks
    IEEE International Conference Computer and Communications, 2007
    Co-Authors: Mingyan Li, Iordanis Koutsopoulos, Radha Poovendran
    Abstract:

    We consider a scenario where a sophisticated jammer jams an area in a single-channel wireless sensor network. The jammer controls the probability of jamming and transmission range to cause maximal damage to the network in terms of corrupted communication links. The jammer action ceases when it is detected by a Monitoring Node in the network, and a notification message is transferred out of the jamming region. The jammer is detected at a monitor Node by employing an optimal detection test based on the percentage of incurred collisions. On the other hand, the network computes channel access probability in an effort to minimize the jamming detection plus notification time. In order for the jammer to optimize its benefit, it needs to know the network channel access probability and number of neighbors of the monitor Node. Accordingly, the network needs to know the jamming probability of the jammer. We study the idealized case of perfect knowledge by both the jammer and the network about the strategy of one another, and the case where the jammer or the network lack this knowledge. The latter is captured by formulating and solving optimization problems, the solutions of which constitute best responses of the attacker or the network to the worst-case strategy of each other. We also take into account potential energy constraints of the jammer and the network. We extend the problem to the case of multiple observers and adaptable jamming transmission range and propose a intuitive heuristic jamming strategy for that case.

Remi Badonnel - One of the best experts on this subject based on the ideXlab platform.

  • a distributed Monitoring strategy for detecting version number attacks in rpl based networks
    IEEE Transactions on Network and Service Management, 2017
    Co-Authors: Anthea Mayzaud, Remi Badonnel, Isabelle Chrisment
    Abstract:

    The Internet of Things is characterized by the large-scale deployment of low power and lossy networks (LLN), interconnecting pervasive objects. The routing protocol for LLN (RPL) protocol has been standardized by IETF to enable a lightweight and robust routing in these constrained networks. A versioning mechanism is incorporated into RPL in order to maintain an optimized topology. However, an attacker can exploit this mechanism to significantly damage the network and reduce its lifetime. After analyzing and comparing existing work, we propose in this paper a Monitoring strategy with dedicated algorithms for detecting such attacks and identifying the involved malicious Nodes. The performance of this solution is evaluated through extensive experiments, and its scalability is quantified with the support of a Monitoring Node placement optimization method.

  • Detecting Version Number Attacks in RPL-based Networks using a Distributed Monitoring Architecture
    2016
    Co-Authors: Anthea Mayzaud, Remi Badonnel, Isabelle Chrisment
    Abstract:

    The concept of Internet of Things involves the deployment of Low power and Lossy Networks (LLN) allowing communications among pervasive devices such as embedded sensors. The IETF designed the Routing Protocol for Low power and Lossy Networks (RPL) for supporting these constrained networks. Keeping in mind the different requirements of such networks, the protocol supports multiple routing topologies, called DODAGs, built using different objective functions, so as to optimize routing based on several metrics. A DODAG versioning system is incorporated into RPL in order to ensure an optimized topology. However, an attacker can exploit this mechanism to damage the network and reduce its lifetime. In this paper we propose a detection strategy based on a distributed Monitoring architecture with dedicated algorithms that is able to identify malicious Nodes performing such attacks in RPL- based environments. The performance of this solution is evaluated through extensive experiments and its scalability is quantified considering a Monitoring Node placement method.