In-Network Outlier Detection in Wireless Sensor Networks

To address the problem of unsupervised outlier detection in wireless sensor networks, we develop an approach that (1) is flexible with respect to the outlier definition, (2) computes the result in-network to reduce both bandwidth and energy usage,(3) only uses single hop communication thus permitting very simple node failure detection and message reliability assurance mechanisms (e.g., carrier-sense), and (4) seamlessly accommodates dynamic updates to data. We examine performance using simulation with real sensor data streams. Our results demonstrate that our approach is accurate and imposes a reasonable communication load and level of power consumption.Comment: Extended version of a paper appearing in the Int'l Conference on Distributed Computing Systems 200

Maximizing Network Lifetime using Fuzzy Based Secure Data Aggregation Protocol (FSDAP) in a Wireless Sensor Networks

Secure Data Aggregation in Wireless Senor Networks (WSNs) is a challenging issue. The various protocols has been suggested in the recent past such as EDIT[13], ADA[8], TSDA[9], SEDAN[10]. These protocols effectively meet the constraints of WSNs. In this paper, we have proposed a Fuzzy Based Secure Data Aggregation protocol (FSDAP) which is an efficient localized protocol. The FSDAP protocol is designed with three phases. The first phase selects Aggregator Node using ANS algorithm. An ANS algorithm involves two steps to elect an Aggregator Node in the clustered network. In first step, the cluster head is selected based on the Euclidean distance and in second step, the cluster head is selected based on the fuzzy product and fuzzy value (α). Then, in second phase, a selected AN eliminates data redundancy sensed by all sensor nodes within the cluster. Finally, in third phase, the FSDAP protocol effectively detects malicious node and provides secure data transmission path. Thus, the proposed protocol, FSDAP utilizes the node’s resource parameter uniformly, which in turn improves Network Lifetime, maximizes Throughput Rate, maximizes Packet Delivery Ratio and minimizes End-to-End Delay. The FSDAP is simulated using the NS2 simulator and compared with centroid algorithms Fuzzy C-Means and K-Means algorithm and a secure aggregation protocol implemented using SAR (Secure Aware Ad hoc Routing). The time complexity of FSDAP protocol is O(m2n)

Security of the Internet of Things: Vulnerabilities, Attacks and Countermeasures

Wireless Sensor Networks (WSNs) constitute one of the most promising third-millennium technologies and have wide range of applications in our surrounding environment. The reason behind the vast adoption of WSNs in various applications is that they have tremendously appealing features, e.g., low production cost, low installation cost, unattended network operation, autonomous and longtime operation. WSNs have started to merge with the Internet of Things (IoT) through the introduction of Internet access capability in sensor nodes and sensing ability in Internet-connected devices. Thereby, the IoT is providing access to huge amount of data, collected by the WSNs, over the Internet. Hence, the security of IoT should start with foremost securing WSNs ahead of the other components. However, owing to the absence of a physical line-of-defense, i.e., there is no dedicated infrastructure such as gateways to watch and observe the flowing information in the network, security of WSNs along with IoT is of a big concern to the scientific community. More specifically, for the application areas in which CIA (confidentiality, integrity, availability) has prime importance, WSNs and emerging IoT technology might constitute an open avenue for the attackers. Besides, recent integration and collaboration of WSNs with IoT will open new challenges and problems in terms of security. Hence, this would be a nightmare for the individuals using these systems as well as the security administrators who are managing those networks. Therefore, a detailed review of security attacks towards WSNs and IoT, along with the techniques for prevention, detection, and mitigation of those attacks are provided in this paper. In this text, attacks are categorized and treated into mainly two parts, most or all types of attacks towards WSNs and IoT are investigated under that umbrella: “Passive Attacks” and “Active Attacks”. Understanding these attacks and their associated defense mechanisms will help paving a secure path towards the proliferation and public acceptance of IoT technology

AIDPS:Adaptive Intrusion Detection and Prevention System for Underwater Acoustic Sensor Networks

Underwater Acoustic Sensor Networks (UW-ASNs) are predominantly used for underwater environments and find applications in many areas. However, a lack of security considerations, the unstable and challenging nature of the underwater environment, and the resource-constrained nature of the sensor nodes used for UW-ASNs (which makes them incapable of adopting security primitives) make the UW-ASN prone to vulnerabilities. This paper proposes an Adaptive decentralised Intrusion Detection and Prevention System called AIDPS for UW-ASNs. The proposed AIDPS can improve the security of the UW-ASNs so that they can efficiently detect underwater-related attacks (e.g., blackhole, grayhole and flooding attacks). To determine the most effective configuration of the proposed construction, we conduct a number of experiments using several state-of-the-art machine learning algorithms (e.g., Adaptive Random Forest (ARF), light gradient-boosting machine, and K-nearest neighbours) and concept drift detection algorithms (e.g., ADWIN, kdqTree, and Page-Hinkley). Our experimental results show that incremental ARF using ADWIN provides optimal performance when implemented with One-class support vector machine (SVM) anomaly-based detectors. Furthermore, our extensive evaluation results also show that the proposed scheme outperforms state-of-the-art bench-marking methods while providing a wider range of desirable features such as scalability and complexity

Survey on RPL enhancements: a focus on topology, security and mobility

International audienceA few years ago, the IPv6 Routing Protocol for Low-power and Lossy Networks (RPL) was proposed by IETF as the routing standard designed for classes of networks in which both nodes and their interconnects are constrained. Since then, great attention has been paid by the scientific and industrial communities for the protocol evaluation and improvement. Indeed, depending on applications scenarios, constraints related to the target environments or other requirements, many adaptations and improvements can be made. So, since the initial release of the standard, several implementations were proposed, some targeting specific optimization goals whereas others would optimize several criteria while building the routing topology. They include, but are not limited to, extending the network lifetime, maximizing throughput at the sink node, avoiding the less secured nodes, considering nodes or sink mobility. Sometimes, to consider the Quality of Service (QoS), it is necessary to consider several of those criteria at the same time. This paper reviews recent works on RPL and highlights major contributions to its improvement, especially those related to topology optimization, security and mobility. We aim to provide an insight into relevant efforts around the protocol, draw some lessons and give useful guidelines for future developments

FEATURE SELECTION FOR INTRUSION DETECTION SYSTEM IN A CLUSTER-BASED HETEROGENEOUS WIRELESS SENSOR NETWORK

Wireless sensor network (WSN) has become one of the most promising networking solutions with exciting new applications for the near future. Notwithstanding the resource constrain of WSNs, it has continued to enjoy widespread deployment.  Security in WSN, however, remains an ongoing research trend as the deployed sensor nodes (SNs) are susceptible to various security challenges due to its architecture, hostile deployment environment and insecure routing protocols. In this work, we propose a feature selection method by combining three filter methods; Gain ratio, Chi-squared and ReliefF (triple-filter) in a cluster-based heterogeneous WSN prior to classification. This will increase the classification accuracy and reduce system complexity by extracting 14 important features from the 41 original features in the dataset. An intrusion detection benchmark dataset, NSL-KDD, is used for performance evaluation by considering detection rate, accuracy and the false alarm rate. Results obtained show that our proposed method can effectively reduce the number of features with a high classification accuracy and detection rate in comparison with other filter methods. In addition, this proposed feature selection method tends to reduce the total energy consumed by SNs during intrusion detection as compared with other filter selection methods, thereby extending the network lifetime and functionality for a reasonable period

Implementación de protocolo de enrutamiento multicamino basado en topología de árbol para aplicaciones de recolección de información en redes inalámbricas de sensores

Una red inalámbrica de sensores (WSN) generalmente sigue un patrón de comunicación de muchos a uno, es decir, todos los nodos de la red envían información a un nodo llamado raíz. Sin embargo, las WSN suelen operar en entornos hostiles y pueden agotar su energía rápidamente, de manera que deben ser resilientes, donde la resiliencia es la capacidad de la red para mantener un nivel aceptable en la calidad del servicio al enfrentarse a fallos y desafíos. Esta tesis se concentra en la implementación de un protocolo de enrutamiento multicamino basado en topología de árbol cuya finalidad es favorecer la conectividad de los nodos y la confiabilidad en la transmisión de los paquetes a medida que van muriendo nodos en una WSN. El protocolo implementado es llamado Árbol doble, y ofrece la siguiente garantía: si un nodo falla, todos los nodos restantes continúan teniendo al menos una ruta hasta la raíz, sin importar qué nodo ha fallado. Los resultados obtenidos demuestran que Árbol doble favorece la conectividad y ofrece más garantías de resiliencia con respecto al algoritmo Shortest path tree (SPT), incrementando el retardo en los paquetes enviados por los nodos en menos del 1%. Árbol doble requiere que los nodos conozcan información local de la red, no información global, lo cual representa una ventaja importante con relación a los protocolos H-SPREAD y DACA. La implementación de Árbol doble se realizó en el simulador OMNET++

Algorithms for Energy Efficiency in Wireless Sensor Networks

The recent advances in microsensor and semiconductor technology have opened a new field within computer science: the networking of small-sized sensors which are capable of sensing, processing, and communicating. Such wireless sensor networks offer new applications in the areas of habitat and environment monitoring, disaster control and operation, military and intelligence control, object tracking, video surveillance, traffic control, as well as in health care and home automation. It is likely that the deployed sensors will be battery-powered, which will limit the energy capacity significantly. Thus, energy efficiency becomes one of the main challenges that need to be taken into account, and the design of energy-efficient algorithms is a major contribution of this thesis. As the wireless communication in the network is one of the main energy consumers, we first consider in detail the characteristics of wireless communication. By using the embedded sensor board (ESB) platform recently developed by the Free University of Berlin, we analyze the means of forward error correction and propose an appropriate resync mechanism, which improves the communication between two ESB nodes substantially. Afterwards, we focus on the forwarding of data packets through the network. We present the algorithms energy-efficient forwarding (EEF), lifetime-efficient forwarding (LEF), and energy-efficient aggregation forwarding (EEAF). While EEF is designed to maximize the number of data bytes delivered per energy unit, LEF additionally takes into account the residual energy of forwarding nodes. In so doing, LEF further prolongs the lifetime of the network. Energy savings due to data aggregation and in-network processing are exploited by EEAF. Besides single-link forwarding, in which data packets are sent to only one forwarding node, we also study the impact of multi-link forwarding, which exploits the broadcast characteristics of the wireless medium by sending packets to several (potential) forwarding nodes. By actively selecting a forwarder among all nodes that received a packet successfully, retransmissions can often be avoided. In the majority of cases, multi-link forwarding is thus more efficient and able to save energy. In the last part of this thesis, we present a topology and energy control algorithm (TECA) to turn off the nodes' radio transceivers completely in order to avoid idle listening. By means of TECA, a connected backbone of active nodes is established, while all other nodes may sleep and save energy by turning off their radios. All algorithms presented in this thesis have been fully analyzed, simulated, and implemented on the ESB platform. They are suitable for several applications scenarios and can easily be adapted even to other wireless sensor platforms