Wireless sensor networks (WSNs) consist of a large number of sensor nodes that monitor the environment and a few base stations that collect the sensor readings. Individual sensor nodes are subject to compromised secur...Wireless sensor networks (WSNs) consist of a large number of sensor nodes that monitor the environment and a few base stations that collect the sensor readings. Individual sensor nodes are subject to compromised security because they may be deployed in hostile environments and each sensor node communicates wirelessly. An adversary can inject false reports into the networks via compromised nodes. Furthermore, an adversary can create a wormhole by directly linking two compromised nodes or using out-of-band channels. If these two kinds of attacks occur simultaneously in a network, existing methods cannot defend against them adequately. We thus propose a secure routing method for detecting false report injections and wormhole attacks in wireless sensor networks. The proposed method uses ACK messages for detecting wormholes and is based on a statistical en-route filtering (SEF) scheme for detecting false reports. Simulation results show that the proposed method reduces energy consumption by up to 20% and provide greater network security.展开更多
Sensor nodes are easily compromised to malicious attackers due to an open environment. A false injected attack which takes place on application layer is elected by the compromised node. If the false report arrives in ...Sensor nodes are easily compromised to malicious attackers due to an open environment. A false injected attack which takes place on application layer is elected by the compromised node. If the false report arrives in a base station, a false alarm is occurred, and the energy of the nodes is consumed. To detect the false report, statistical en-route filtering method is proposed. In this paper, we proposed the secure path cycle selection method using fuzzy rule-based system to consume effective energy. The method makes balanced energy consumption of each node. Moreover, the lifetime of the whole network will be increased. The base station determines the path cycle using the fuzzy rule-based system. The performance of the proposed method is demonstrated using simulation studies with the three methods.展开更多
Wireless sensor networks (WSNs) are networked systems that are able to sense various events and report the events to a user to enable appropriate responses. One of security threats to a WSN is false data injection att...Wireless sensor networks (WSNs) are networked systems that are able to sense various events and report the events to a user to enable appropriate responses. One of security threats to a WSN is false data injection attacks in which an attacker steals some sensor nodes in the network and injects forged event messages into the network through the captured nodes. As a result, the intermediate nodes on the forwarding paths of the false event messages waste their limited energy. Additionally, the network cannot provide the user with correct information. There have been many studies on en-route detection of false event messages for WSNs. Yang et al. proposed the commutative cipher-based en-route filtering scheme (CCEF) which establishes a secure session between a sink node and a cluster head (CH) based on the commutative cipher. In CCEF, each intermediate node on the path between the sink node and the CH receives an event message and verifies the authenticity of the session based on a probability. Due to the probabilistic approach, it is hard to adapt to the change of false traffic ratio in the network and energy inefficiency may occur. We propose a filtering scheme which applies a deterministic approach to assign filtering nodes to a given session. The proposed method consumes less energy than that of CCEF without sacrificing security.展开更多
Sensor networks include numerous sensor nodes that are vulnerable to physical attacks from the outside because they operate in open environments. The sensor nodes are compromised by an attacker. The compromised nodes ...Sensor networks include numerous sensor nodes that are vulnerable to physical attacks from the outside because they operate in open environments. The sensor nodes are compromised by an attacker. The compromised nodes generate false reports and inject the reports into sensor networks. The false report injection attacks deplete energy of the sensor nodes. Ye et al. proposed Statistical En-Route Filtering (SEF) to defend sensor nodes against the false report injection attacks. In SEF, sensor nodes verify the event reports based on a fixed probability. Thus, the verification energy of a node is the same whether the report is false or valid. But when there are few false reports, energy for verifying legitimate reports may be wasted. In this paper, we propose a method in which each node controls a probability of attempts at verification of an event report to reduce the wasted energy. The probability is determined through consideration of the number of neighboring nodes, the number of hops from the node to the sink node, and the rate of false reports among the 10 most recent event reports forwarded to a node. We simulated our proposed method to prove its energy efficiency. After the simulation, we confirmed that the proposed method is more efficient than SEF for saving sensor node’s energy.展开更多
Sensor networks are vulnerable to many attacks because the sensor networks operate in open environments. It is easy to incur one or more attacks such as a selective forwarding attack, a false report injection attack. ...Sensor networks are vulnerable to many attacks because the sensor networks operate in open environments. It is easy to incur one or more attacks such as a selective forwarding attack, a false report injection attack. It is hard to defend the sensor network from the multiple attacks through existing security methods. Thus, we suggest an energy-efficient security method in order to detect the multiple attacks. This paper presents a security method to detect the false report injection attack and the selective forwarding attack in the sensor network using a new message type. The message type is a filtering message. The filtering message prevents from generating and forwarding false alert messages. We evaluated performance of our proposed method through a simulation in comparison with an application of SEF (statistical enroute filtering scheme) and CHEMAS (Check point-based Multi-hop Acknowledgement Scheme). The simulation results represent that the proposed method is 10% more energy-efficient than the application when the number of false reports is great while retaining the detection performance.展开更多
文摘Wireless sensor networks (WSNs) consist of a large number of sensor nodes that monitor the environment and a few base stations that collect the sensor readings. Individual sensor nodes are subject to compromised security because they may be deployed in hostile environments and each sensor node communicates wirelessly. An adversary can inject false reports into the networks via compromised nodes. Furthermore, an adversary can create a wormhole by directly linking two compromised nodes or using out-of-band channels. If these two kinds of attacks occur simultaneously in a network, existing methods cannot defend against them adequately. We thus propose a secure routing method for detecting false report injections and wormhole attacks in wireless sensor networks. The proposed method uses ACK messages for detecting wormholes and is based on a statistical en-route filtering (SEF) scheme for detecting false reports. Simulation results show that the proposed method reduces energy consumption by up to 20% and provide greater network security.
文摘Sensor nodes are easily compromised to malicious attackers due to an open environment. A false injected attack which takes place on application layer is elected by the compromised node. If the false report arrives in a base station, a false alarm is occurred, and the energy of the nodes is consumed. To detect the false report, statistical en-route filtering method is proposed. In this paper, we proposed the secure path cycle selection method using fuzzy rule-based system to consume effective energy. The method makes balanced energy consumption of each node. Moreover, the lifetime of the whole network will be increased. The base station determines the path cycle using the fuzzy rule-based system. The performance of the proposed method is demonstrated using simulation studies with the three methods.
文摘Wireless sensor networks (WSNs) are networked systems that are able to sense various events and report the events to a user to enable appropriate responses. One of security threats to a WSN is false data injection attacks in which an attacker steals some sensor nodes in the network and injects forged event messages into the network through the captured nodes. As a result, the intermediate nodes on the forwarding paths of the false event messages waste their limited energy. Additionally, the network cannot provide the user with correct information. There have been many studies on en-route detection of false event messages for WSNs. Yang et al. proposed the commutative cipher-based en-route filtering scheme (CCEF) which establishes a secure session between a sink node and a cluster head (CH) based on the commutative cipher. In CCEF, each intermediate node on the path between the sink node and the CH receives an event message and verifies the authenticity of the session based on a probability. Due to the probabilistic approach, it is hard to adapt to the change of false traffic ratio in the network and energy inefficiency may occur. We propose a filtering scheme which applies a deterministic approach to assign filtering nodes to a given session. The proposed method consumes less energy than that of CCEF without sacrificing security.
文摘Sensor networks include numerous sensor nodes that are vulnerable to physical attacks from the outside because they operate in open environments. The sensor nodes are compromised by an attacker. The compromised nodes generate false reports and inject the reports into sensor networks. The false report injection attacks deplete energy of the sensor nodes. Ye et al. proposed Statistical En-Route Filtering (SEF) to defend sensor nodes against the false report injection attacks. In SEF, sensor nodes verify the event reports based on a fixed probability. Thus, the verification energy of a node is the same whether the report is false or valid. But when there are few false reports, energy for verifying legitimate reports may be wasted. In this paper, we propose a method in which each node controls a probability of attempts at verification of an event report to reduce the wasted energy. The probability is determined through consideration of the number of neighboring nodes, the number of hops from the node to the sink node, and the rate of false reports among the 10 most recent event reports forwarded to a node. We simulated our proposed method to prove its energy efficiency. After the simulation, we confirmed that the proposed method is more efficient than SEF for saving sensor node’s energy.
文摘Sensor networks are vulnerable to many attacks because the sensor networks operate in open environments. It is easy to incur one or more attacks such as a selective forwarding attack, a false report injection attack. It is hard to defend the sensor network from the multiple attacks through existing security methods. Thus, we suggest an energy-efficient security method in order to detect the multiple attacks. This paper presents a security method to detect the false report injection attack and the selective forwarding attack in the sensor network using a new message type. The message type is a filtering message. The filtering message prevents from generating and forwarding false alert messages. We evaluated performance of our proposed method through a simulation in comparison with an application of SEF (statistical enroute filtering scheme) and CHEMAS (Check point-based Multi-hop Acknowledgement Scheme). The simulation results represent that the proposed method is 10% more energy-efficient than the application when the number of false reports is great while retaining the detection performance.
