Message authentication and wormhole detection mechanism in wireless sensor network

How to determine the source-visiting sequence among the target sensor nodes and manage the mobile agent (MA) effectively is the crucial problem in Mobile-Agent-based computing model for wireless sensor networks (WSNs). In this paper, we propose a novel improved Directed Diffusion-based MA mechanism (IDDMA) for WSNs. IDDMA uses an improved gradient generation algorithm to set up multiple optimal gradients among sensor nodes. The source nodes will subsequently send two distinct types of the exploratory data packet to implement the discovery of the sources and build the routing tables for the MA routing, respectively. Then, the MA in target region could choose its next-hop node dynamically according to the established routing table for MA in each source node and achieve the data fusion; finally it will return to the Sink. Simulation results show that the mechanism outperforms two existing routing protocols in end-to-end packet delay and average energy consumption.

The inherent characteristics of Mobile Ad hoc network (MANET) such as dynamic topology, limited bandwidth, limited power supply, infrastructure less network make themselves attractive for a wide spectrum of applications and vulnerable to security attacks. Sinkhole attack is the most disruptive routing layer attack. Sinkhole nodes attract all the traffic towards them to setup further active attacks such as Black hole, Gray hole and wormhole attacks. Sinkhole nodes need to be isolated from the MANET as early as possible. In this paper, an effective mechanism is proposed to prevent and detect sinkhole and wormhole attacks in MANET. The proposed work detects and punishes the attacker nodes using different techniques such as node collusion technique, which classifies a node as an attacker node only with the agreement with the neighboring nodes. When the node suspects the existence of attacker or sinkhole node in the path, it joins together with neighboring nodes to determine the sinkhole node. In the prevention of routing attacks, the proposed system introduces a route reserve method; new routes learnt are updated in the routing table of the node only after ensuring that the route does not contain the attacker nodes. The proposed system effectively modifies Ad hoc on demand Distance Vector (AODV) with the ability to detect and prevent the sinkhole and wormhole attack, so the modified protocol is named as Attack Aware Alert (A3AODV). The experiments are carried out in NS2 simulator, and the result shows the efficiency in terms of packet delivery ratio and routing overhead.

Wireless sensor network allows nodes to communicate with another using wireless channels so that it is necessary for packet delivery to the nodes. Black hole attack occurs when a malicious node receives and misleads a set of nodes in the wireless network to drop the data they received. Wormhole attack occurs when malicious nodes create data delivery latency between two nodes in the wireless network. In this paper, we propose a Machine Learning based Naive Bayes Classifier to detect and Enhanced Code-based Round Trip Time based method prevent those two vital attacks. The black hole attack can be analyzed using this technique with the help of authorize code. Similarly, the wormhole attack and fake destination attack can be prevented by trip time to find the data delay time to reach the destination. In the case of black hole attack, a node which does not have authorized code will be considered as malicious node and discarded. If the packet does not arrive at the destination within the specific time, it will automatically detect the occurrence of wormhole in the wireless network. The proposed method is experimentally validated on network simulator (NS2). The main advantage of the proposed method is to reduce the communication overhead.

MANET is the mobile ad-hoc network. Security is very important especially when transmitting the data packets from one node to another. MANET is constructed by grouping mobile wireless nodes with no fixed infrastructure. In order to forward the packets, all the nodes in the network must cooperate with each other, so that the nodes beyond the radio ranges can communicate. Each node acts as a router and MANET is infrastructure-less networks. Hence, MANET is open to more security attacks such as Gray-hole attack, Black-hole attack and worm-hole attack. Due to the dynamism in network topology, MANETS are highly vulnerable and are prone to malicious attack. Security issue is highly challenging in MANET. Understanding the different form of possible attacks and providing good security solutions is important for secure data transmission between nodes. The most dangerous attack among these attacks is Gray-hole attack. In this paper, it proposed a method for reducing the Gray-hole attack. Our proposed algorithm MAODV identifies the malicious node before the data transmission process and it greatly reduces the dropping of data packets.

MANET is vulnerable to most of the security threats and we proposed a combined approach which is used to detect both the black hole and worm hole attack. We also carried out black hole and worm hole attack on MANET using Ad hoc On Demand Distance Vector (AODV) routing protocol and analyzed the performance parameters like Throughput, Packet Delivery Ratio(PDR) and Normalized Routing Load (NRL). After implementation of proposed technique, we found that the parameters for Quality of Services (QoS) in MANET improved significantly as compare to conventional techniques.

The current research work in wireless sensor networks has mostly focused on the resolving issues related to power consumption and computational resource constraints in the wireless sensor networks .To achieve the same various specific routing schemes ,MAC and cross layered protocols and techniques have been proposed and designed .But with recent advances the privacy issues related to the data collected and transmitted by the wireless sensor networks had taken the center stage .Privacy preservation in wireless sensor networks has become more challenging because of the wireless nature of communication in WSN as well as its self organizing architecture. The present paper provides a comparative review of various privacy preserving mechanisms proposed and implemented in wireless sensor networks with respect to the privacy notions of k- anonymity and L-diversity. Along with the discussion and analysis the present work is an effort for the pavement of a way towards the future research in the field of privacy preservation in WSN.

Wireless sensor networks (WSNs) are wireless ad hoc networks of tiny sensor nodes increasingly deployed for multiple civilian and military applications, including patient monitoring, wildlife monitoring, battlefield surveillance, enemy tracking, etc. Like other computer networks, WSNs must be provided of security services such as key management, confidentiality, integrity and authentication. However, the nature of WSNs and their operational requirements introduce new exciting challenges on security design. Key management is a fundamental security service and a hot topic of research in security for WSNs. In this paper, we will review the state of the art on key management for WSNs and provide a glimpse on current and future developments in this area.

With increasing of load in wireless sensor network, congestion will make network performance worse quickly. Network performance will be improved by introducing based on single-hop flow control mechanism for wireless sensor network, in which the former hop nodes of congestion nodes adjust flow to control flow rate coming into congestion nodes. In addition, this mechanism can keep the balance of rate between inflow and outflow in congestion nodes.

<p>Wireless sensor networks (WSNs) are susceptible to a variety of attacks, such as data tampering attacks, blackhole attacks, and grayhole attacks, that can affect the reliability of communication. We proposed a reputationenhanced two-way hybrid algorithm (RCHA) that uses cryptographic hash functions and reputation-based trust management to detect and de-escalate attacks accurately. The RCHA algorithm implements two hash functions RACE integrity primitives’ evaluation message digest (RIPEMD) and secure hash algorithm (SHA-3), to initiate the integrity check for the entire packet sent across the network. Every node in the WSN tracks a reputation score for each neighbor the node is connected to, and this score is dynamically updated based on the behavior of each neighbor. If a neighboring node’s reputation drops below a threshold, the node is sent a maliciousness designation. At that time, the node will broadcast an alert message to its neighboring nodes and begin to reroute its data through one of its trusted neighbors to ensure the reliability of the communication. The simulation results reported that the RCHA algorithm improved the accuracy of the attack detection rate and the number of packets delivered compared to traditional attack detection methods. The RCHA algorithm was able to maintain low computational and energy overhead for the WSN, making it an attractive option for a resource-constrained application in a WSN. Given the trends towards more collaborative networks, the reputation mechanism in the RCHA algorithm improves the overall reliability and capabilities of the WSN, regardless of adversaries.</p>

With the explosion of big data, the implementation of distributed machine learning mechanisms in wireless sensor networks (WSNs) is becoming required for reducing the number of data traveling throughout the network and for identifying anomalies promptly and reliably. In WSNs, the above need has to be considered along with the limited energy and processing resources available at the nodes. In this paper, we tackle the resulting complex problem by designing a multi-criteria protocol CINE that stands for “Clustered distributed learnIng exploiting Node centrality and residual Energy” for distributed learning in WSNs. More specifically, considering the energy and processing capabilities of nodes, we design a scheme that assumes that nodes are partitioned in clusters and selects a central node in each cluster, called cluster head (CH), that executes the training of the machine learning (ML) model for all the other nodes in the cluster, called cluster members (CMs). In fact, CMs are responsible for executing the inference only. Since the CH role requires the consumption of more resources, the proposed scheme rotates the CH role among all nodes in the cluster. The protocol has been simulated and tested using real environmental data sets.

Severe energy constraints and hence the low power communication requirements amplify the significance of the energy efficient and preferably cross-layer error control mechanisms in wireless sensor networks (WSN). In this paper, a cross-layer methodology for the analysis of error control schemes in WSNs is presented such that the effects of multi-hop routing and the broadcast nature of the wireless channel are investigated. More specifically, the cross-layer effects of routing, medium access and physical layers are considered. This analysis enables a comprehensive comparison of forward error correction (FEC) and automatic repeat request (ARQ) in WSNs. FEC schemes improve the error resiliency compared to ARQ. In a multi-hop network, this improvement can be exploited by reducing the transmit power (transmit power control) or by constructing longer hops (hop length extension), which can be achieved through channel-aware routing protocols. The results of our analysis reveal that for certain FEC codes, the hop length extension decreases both the energy consumption and the end-to-end latency subject to a target PER compared to ARQ. Thus, FEC codes can be regarded as an important candidate for delay sensitive traffic in WSNs. On the other hand, transmit power control results in significant savings in energy consumption at the cost of increased latency. Moreover, the cases where ARQ outperforms FEC codes are indicated for various end-to-end distance and target PER values

Objective: Wormhole attack is a serious threat to Wireless Sensor Networks (WSN) due to its wireless broadcast nature of communication, multi hop nature and resource constraints. Hence, to enhance the security and energy efficiency of a WSN, energy efficient Intrusion Detection System (IDS) is needed to detect and mitigate the attacks. In this paper, an Energy Efficient Intrusion Detection System (EE-IDS) has been proposed for IEEE 802.15.4 based WSN to detect and mitigate the effect of wormhole attacks. Methods/Statistical Analysis: The wormhole attack is detected by using the optimized watchdog system. The optimized watchdog mechanism is a trust based method which is used to evaluate the validity of all the nodes of the network. In proposed approach, the optimization has been done in the selection of watchdog nodes, in order to consume less energy compared to that of the existing approaches. The detection of wormhole attack is also completely relies on the three main factors like trustworthiness, packet delivery ratio and end-to-end delay. Findings: The proposed EE-IDS is examined through extensive simulations by considering static and mobility model, and then it is compared with the existing IDS for detecting wormhole attacks. The performance of zigbee WSN is analyzed in terms of metrics such as packet delivery ratio, average end-to-end delay and energy consumption for static model. In mobility model, the Proposed EE-IDS is evaluated in terms of detection rate, false positive rate and detection time. Application/ Improvements: The proposed EE-IDS is used to detect the wormhole attack and improve the energy efficiency in zigbee based wireless sensor networks, which can be used for military, environmental, health and commercial applications.

Node failures are inevitable in wireless sensor networks (WSNs) because sensor nodes in WSNs are miniature and equipped with small and often irreplaceable batteries. Due to battery drainage, sensor nodes can fail at any instance. Moreover, WSNs operate in hostile environments and environmental factors may also contribute to nodes failure. Failure of nodes leads to disruption of inter-node connectivity and might also lead to network partitioning. Failure to communicate with each other and with the base station can compromise the basic operation of the sensor network. For restoration of connectivity, a robust recovery mechanism is required. The existing connectivity restoration mechanisms suffer from shortcomings because they do not focus on energy-efficient operation and coverage-aware mechanisms while performing connectivity restoration. As a result, most of these mechanisms lead to the excessive mobility of nodes, which itself causes the utilization of excessive battery. In this work, we propose a novel technique called smart node relocation (SNR). SNR is capable of detecting and restoring the connectivity caused by either single or multiple node failures. For achieving energy efficiency, SNR relies on transmitting a lesser number of control packets. For achieving the goal of being coverage-aware, it tries to relocate only essential nodes while trying to restore connectivity. By performing extensive simulations, we prove that SNR outperforms the existing approaches concerning multiple performance metrics including but not limited to the total number of packets transmitted, total distance moved for connectivity restoration, the percentage reduction in field coverage.

Wireless sensor network (WSN), has been a much attracted area for researchers for quite a while. Even with the extensive research activity over the last few years, WSNs still has a lot of ground to cover. Sensor Networks are basically data- centric wireless self-organizing network which is created by the many individual sensor nodes. They are battery driven devices, and as any battery powered devices it too has a limited lifespan. WSNs are widely used for tracking wild animals and border surveillance, enemy tracking, etc. Hence it may not be possible to recharge batteries frequently so the main objective will be to reduce energy consumption. It can be reduced in many ways like effective node placement, clustering, data aggregation, synchronized transmission etc. In this paper we are analyzing some of the available protocols for our further research.

Wireless sensor networks are emerging as broadband communication networks, because of their bandwidth, low cost and easy installation. In large sensor networks, data aggregation significantly reduces the amount of communication and energy consumption in the network. In this paper two different routing protocols namely Ad hoc On-demand Distance Vector (AODV) routing protocol and Secure-aware Ad hoc Routing Protocol (SAR) are proposed. By using these protocols the network performances are evaluated in the presence of three types of attacks namely black hole attack, warm hole attack and grey hole attack respectively. The performance of the network is analyzed using the Network Simulator.