Detecting selective forwarding attacks in wireless sensor networks

Wireless sensor networks (WSNs) are novel large-scale wireless networks that consist of distributed, self organizing, low-power, low-cost, tiny sensor devices to cooperatively collect information through infrastructure less wireless networks. These networks are envisioned to play a crucial role in variety of applications like critical military surveillance applications, forest fire monitoring, commercial applications such as building security monitoring, traffic surveillance, habitat monitoring and smart homes and many more scenarios. Node capture attack is one of the most dreadful security attack exist in wireless sensor networks. An adversary steals cryptographic key or other confidential information like node’s id etc from a captured node to compromise entire network. So, Security of wireless sensor network is an important issue for maintaining confidentiality and integrity of wireless links. Now-a-days, researchers are paying attention towards developing security schemes against Node capture attack. Our survey provides deep insights of existing techniques that enhance the attacking efficiency of the node capture attack in wireless sensor network. It also analyzes various detection and key predistribution schemes for inventing a new scheme to improve resilience against node capture attack.

Wireless sensor networks have been widely applied in many areas due to their unique characteristics. These have exposed them to different types of active and passive attacks. In the literature, several solutions have been proposed to mitigate these attacks. Most of the proposed solutions are too complex to be implemented in wireless sensor networks considering the resource-constraint of sensor nodes. In this work, we proposed a hierarchical trust mechanism based on clustering approach to detect and prevent denial of service attacks in wireless sensor networks. The approach was validated through simulation using Network Simulator (NS2). The following metrics were used to evaluation the proposed scheme: packet delivery ratio, network lifetime, routing delay, overhead, and number of nodes. The proposed approach is capable of detecting compromised sensor nodes vulnerable to a denial of service attacks. Moreover, it is able to detect all sensed data that have been compromised during transmission to the base station. The results show that our method can effectively detect and defend against denial of service attacks in sensor wireless sensor networks.

Wireless Sensor Networks (WSNs) are a new technology foreseen to be used increasingly in the near future due to their data acquisition and data processing abilities. Security for WSNs is an area that needs to be considered in order to protect the functionality of these networks, the data they convey and the location of their members. The security models and protocols used in wired and other networks are not suited to WSNs because of their severe resource constraints, especially concerning energy. In this article, we propose a centralized intrusion detection scheme based on Support Vector Machines (SVMs) and sliding windows. We find that our system can detect black hole attacks and selective forwarding attacks with high accuracy without depleting the nodes of their energy.

Routing protocols in wireless sensor network are vulnerable to various malicious security attacks that can degrade network performance and lifetime. This becomes more important in cluster routing protocols that is composed of multiple node and cluster head, such as low energy adaptive clustering hierarchy (LEACH) protocol. Namely, if an attack succeeds in failing the cluster head, then the entire set of nodes fail. Therefore, it is necessary to develop robust recovery schemes to overcome security attacks and recover packets at short times. Hence this paper proposes a detection and recovery scheme for selective forwarding attacks in wireless sensor networks using LEACH protocol. The proposed solution features near-instantaneous recovery times, without the requirement for feedback or retransmissions once an attack occurs.

The article comprises issues of analytical modeling of attacks in wireless sensor networks. A proposed attack model specifies possible types of unauthorized influences at the network level aimed at compromising network nodes, data transmitted over the network, and information services provided by the wireless sensor network. A developed graph-based analytical model of a wireless sensor network aims at detecting network layer attacks by processing actual events received from network nodes and deciding whether the network is running under an attack. The correctness of the models is confirmed by their testing by using an example of a scenario for detecting a wormhole attack aimed at disrupting routing processes in a wireless sensor network.

Detecting Sybil attacks in wireless sensor networks using UWB ranging-based information

One of the most common attacks against Wireless Sensor Networks is the wormhole attack. In this attack, the enemy deploys two malicious nodes in two different areas of the network and establishes a high-speed dedicated channel between these two. This will cause the normal nodes in two different areas wrongly think that they are two-hop neighbors. Therefore, this attack will greatly affect the routing algorithms. In this paper, a new distributed algorithm is provided to deal with the wormhole attack. The main idea of the proposed algorithm is to discover separate routes between pairs of two-hop neighboring nodes. The proposed algorithm was implemented and evaluated in terms of true and false detection rate by performing a series of experiments and the results were compared with the base algorithm. The test results showed that the proposed algorithm has desirable efficacy.

A Wireless Sensor network (WSN) consists of large number of low cost low power sensor nodes. The nature of wireless sensor networks makes them very attractive to attackers. One of the most popular and serious attacks in wireless sensor networks is sink hole attack and most existing protocols to defend against this attack used cryptographic methods with keys. In sink hole attack a sensor node will have a lot of false neighbors. Wireless Sensor Network has a dynamic topology, intermittent connectivity, and resource constrained device nodes. Researchers over the past years have encouraged the use of mobile agent to overcome these challenges. The proposed scheme is to defend against sink hole attacks using mobile agents. Mobile agent is a program segment which is self controlling. They navigate from node to node not only transmitting data but also doing computation. They are an effective paradigm for distributed applications, and especially attractive in a dynamic network environment. A routing algorithm with multiple constraints is proposed based on mobile agents. It uses mobile agents to collect information of all mobile sensor nodes to make every node aware of the entire network so that a valid node will not listen the cheating information from malicious or compromised node which leads to sink hole attack. The significant feature of the proposed mechanism is that it does not need any encryption or decryption mechanism to detect the sink hole attack. This mechanism does not require more energy than normal routing protocols like AODV. Here we implement a simulation-based model of our solution to recover from a Sinkhole attack in a Wireless Sensor Network. The mobile agents were developed using the Aglet.

Wireless sensor networks are being used more and more. Sensor nodes can be distributed in hazardous environments to collect data. As these environments are usually unsecured, provide security in wireless sensor networks is vital. Detecting attacks in sensor networks is inevitable to provide security. Various attacks threaten sensor networks one of which is Sybil attack, which can be a big threat for geographical routing protocols and multi-path routing. In this paper, a distributed method has been presented using mobile agents and local information of each sensor to detect Sybil attack. The results of simulation show the efficacy of this method in comparison with previous methods.

Objectives: The main aim of this paper is security by applying Intelligent Intrusion detection System to detect one of the critical attack know as sinkhole attack in Wireless Sensor network. Methods/Analysis: The major problem occurs while transmitting the data is security. The malicious node attracts the packets from the other normal sensor nodes and drops the sensitive packets which may leads to selective forwarding attack and black hole attack. Findings: In the existing system, Leader based intrusion detection system is used to monitor the surrounding node. Here the leader can monitor the nodes only region wise and does not have any clustering technique. By using the clustering technique we can monitor the surrounding nodes in efficient manner and better solution. In the proposed system, an Intelligent Intrusion Detection System (IIDS) mechanism to detect the intruder in the network, which uses a Hybrid Approach to detect and prevent sinkhole attack, with two approaches such as Zone-Based Leader Election Method and Leader Based Monitoring. In Zone-Based Leader Election method, a set of nodes is located in different regions and a Cluster Based Zone Leader (CBZL) is allocated to every region in the network. In the Leader Based Monitoring Approach, when a node gets detected as a compromised node, it communicates the status of that node to the other leader within the WSN. Application/Improvement: This technique can identify the intruder node and improve the efficiency of the network. As a simulation results, we are implementing in Network Simulator. In environment monitoring and military applications the proposed approach can be deployed.

Information attacks and security in wireless sensor networks of industrial SCADA systems

In this paper, we propose an Intrusion Detection System (IDS) against Sinkhole attack in wireless sensor networks with mobile sink. In the detection model, the network area is divided into a flat grid of cells, and we use the signature-based technique, which is represented by the detection rate of a cell, to distinguish between real and fake sink nodes. The proposed IDS considers two types of sink mobility: periodic and random. In addition, as the cell leaders do not activate their IDS agent simultaneously, the additional energy consumption incurred by the IDS is low. Simulation results show the efficiency of the proposed IDS in terms of detection rate, efficiency, and energy consumption.

Wormhole attack is a harmful attack that disrupts the normal functioning of the network by manipulating routing protocols and exhausting network resources. The paper presents a technique that detects the presence of wormhole attack in wireless sensor network (WSN) using artificial neural network (ANN). The proposed technique uses connectivity information between any two sensor nodes as the detection feature. The proposed technique has been implemented considering the deployment of sensor nodes in the wireless sensor network area under uniform, Poisson, Gaussian, exponential, gamma & beta probability distributions. The proposed technique does not require any additional hardware resources and gives a comparatively high percentage of detection accuracy. KeywordsWireless sensor networkProbability distributionWormhole attackANN

Wireless sensor networks (WSNs) are being increasingly deployed for various applications such as object tracking and monitoring, precision agriculture, controlling nuclear reactors, detecting seismic activities, security and surveillance, navigational activities, industrial automation, and so on. In selective forwarding attack, malicious nodes may refuse to forward certain messages and simply drop them, ensuring that they are not propagated any more. In this paper we have proposed a defensive technique. Our approach is divided into mainly three phases: In first phase the node discover a path and its neighbor nodes, in second phase when the event is generated and data is propagated in multipath and is checked whether the data reached is correct or not, and in the final phase if any error is detected then a MONITOR packet is generated and the malicious node is removed.

Wireless sensor networks (WSNs), including Software-Defined Wireless Sensors, are particularly vulnerable to Denial-of-Service (DoS) attacks. Trust models are widely acknowledged as an effective strategy to mitigate the threat of successful DoS attacks in WSNs. However, existing trust models commonly rely on threshold configurations that are based on the network administrator’s experience and leave the challenging task of weight allocation for various trust metrics to network users. This limits the widespread application of trust models as a WSN defence mechanism. To address that issue, this study proposes and theoretically analyses an Adaptive, Threshold-Free, and Automatically Weighted Trust Model (ATAW-TM) for SDWSNs. The model architecture is aligned with the layered centralized management architecture of SDWSNs, which makes it flexible and enhances its responsiveness. The proposed model does not require manual threshold configuration and weight allocation and allows for rapid trust system recovery. It has significant advantages compared to existing trust models and is potentially more feasible to implement on a large scale.