This paper presents a novel approach for detecting denial of service attacks. In particular, the concern is on the sleeping deprivation attacks such as the malicious nodes that use flooding technique. Our approach is based on wireless sensor network (WSN) clustering. It consists in recursively clustering sensors until a required granularity (chosen by the expert) is achieved. We apply our approach with two different clustering algorithms. Indeed, we use the common clustering WSN algorithm Low Energy Algorithm Adaptive Clustering Hierarchy and the general clustering method Fast and Flexible Unsupervised Clustering Algorithm (FFUCA) based on ultrametric properties. We discuss the behavior of the approach with the two algorithms. Also, we present numerical results that show the efficiency of recursive clustering using the FFUCA algorithm. 310 S. FOUCHAL ET AL.to DoS attacks such as jamming or greedy attacks. The radio signal may be jammed or interfered with and then induces a communication breakdown or a message loss. Many attack strategies, which a jammer can perform, exist, such as the following [11]:Constant: random bits of data are sent continuously over channel. Deceptive: valid packets are sent continuously over the channel. Random: the jammer alternates between sleeping and jamming the channel. Reactive: the jammer attacks only when another radio attempts to use the channel.Several solutions to cope with these attacks have been proposed in the literature [12]. All of them are mainly based on ad hoc networks that have more energy and processing capacities, like routing algorithms [13]. Thus, to overcome these problems, WSNs need specific protection mechanism that detect and reacts to make attacks more complicated [14]. In this context, many approaches are suitable of specific topology organization, especially a hierarchical one [15].Hierarchical topology of WSNs is based on clusters [16]. In fact, sensors are gathered into clusters. Each cluster is represented by a cluster head (CH). The CHs collect information that is locally processed and send it to the BS. This CHs are chosen among sensors that have sufficient resources (i.e., residual energy, memory, and computing capacity) [17]. The common algorithms that are used to cluster WSNs are Low Energy Algorithm Adaptive Clustering Hierarchy (LEACH) [18,19] and a Hybrid, Energy Efficient, Distributed (HEED) clustering approach for ad hoc sensor networks [20].Alrajeh et al. proposed in [4] a secure routing protocol for WSNs that uses a cluster-based security mechanism. They have considered cross-layer design and energy-harvesting system. The cross-layer information exchange allows a network usage and resources optimization by communicating different layers. This induces a multiple parameters exchange and so increases network performance and its efficiency. The energy-harvesting mechanism is applied to enlarge sensors availability and thus the network lifetime. This proposal offers a consistent energy management and efficient solution of secure path from source to ...

WIth the facility of deployment, Wireless Sensor Networks becomes very popular but have special characteristics such as limited battery, limited processing power, and limited storage that makes the energy consumption saving a real challenge. Add to this and due to their distributed deployment, these networks are exposed to denial of service attacks such as jamming and greedy attacks. In all cases these attacks tackle the energy consumption in order to degrade the overall Quality of Service (QoS). In this paper, we propose an energy-preserving solution to detect compromised nodes in WSNs. The proposed method is based on hierarchical clustering technique which elect Controlled nodes (Cnode) that analyze the traffic inside a cluster and to send warnings to the cluster-head (CH) whenever an abnormal behavior is detected. The proposed method is dynamic as the Cnodes are periodically elected among ordinary nodes on each atomic cluster. Such a solution results in a better energy balance while maintaining good detection coverage as it is based on the distance between nodes, the output throughput and delay between packets transmission.

Sensor networks are tiny independent devices which are characterized by limiting battery, processing power and storage memory, that makes saving consumption energy as real challenge power. Morever, there are many techniques used used to conserve energy in Wireless Sensor Networks (WSNs) the clustering technique is one of them. In terms of security, WSNs are more vulnerable to attacks than wired networks. However, radio frequencies used in WSNs are open, making the eavesdropping fairly easy. By considering energy consumption and in order to prevent from Denial of Service (DoS) attacks, present study introducing a preventing DoS attacks approach, which is based on using clustering techniques.

International audienceClustering algorithms have been widely used in many domains so as to partition a set of elements into several subsets, each subset (or ”cluster”) grouping elements which share some similarities. These algorithms are particularly useful in wireless sensor networks (WSNs), where they allow data aggregation and energy cuts. By forming clusters and electing cluster heads responsible for forwarding their packets, the small devices that compose WSNs have not to reach directly the base station (BS) of the network. They spare energy and they can lead further in time their measuring task, so as to detect forest fires or water pollution for example. In this paper, we will apply a new and general clustering algorithm, based on classificability and ultrametric properties, to a WSN. Our goal is to get clusters with a low computational complexity, but with an optimal structure regarding energy consumption

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Summary In recent years, wireless sensor networks (WSNs) have attracted an increasing attention in several fields. However, WSNs must be treated with significant challenges in their design due to their special characteristics such as limited energy, processing power, and data storage that make the energy consumption saving a real challenge. Also, regarding their distributed deployment in open radio frequency and lack of physical security, these networks are vulnerable and exposed to several attacks: passive eavesdropping, active attacks, and identity theft. In this paper, we propose a new method called accordion method to detect and apprehend denial of service attacks in WSNs. This approach is a dynamic and an adaptive method based on using clustering method which allows electing control nodes that analyze the traffic inside a cluster and send warnings to the cluster head whenever an abnormal behavior is suspected or detected. The proposed method relies on the analysis of the evolution of the threshold messages (alerts) sent in the cluster. The proposed method has been evaluated, and the obtained numerical results show its benefit compared with other detection methods.

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