Reinforcement Learning for Intrusion Detection and Improving Optimal Route by Cuckoo Search in WSN (original) (raw)
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Indonesian Journal of Electrical Engineering and Computer Science, 2022
The cuckoo search (CS) technique is applying to discover the optimal route from source to destination. The main objective of this work is to offer suitable solutions for getting better the optimal routing and communicating the data via reliable sensor nodes. This CS optimization method not capable for managing the diversity of the solutions. To solve this issue, we use the CS technique to hybridize it with the hill climbing (HC) technique to minimize the probability of early convergence. This approach introduces a fusion of CS and HC techniques (CSHC) based optimal forwarder selection and detect the Intrusion in wireless sensor network (WSN). Here, a Bayesian thresholding method is predict the received signal strength and link reliability parameter for identifying intrusion in the network. The hillclimbing technique is able to attain the best solutions in a smaller period than other local search techniques. In CSHC, the optimal forwarderis selection by fitness function. This fitness function is computed based on sensor node lifetime, sensor link reliability, and buffer availability. In this approach, the experimental results suggest that the CSHC for improving 35% throughput and minimizes the 23.52% packet losses compared to the baseline approaches.
2024
Background and Objectives: Wireless sensor networks (WSNs) are ad-hoc technologies that have various applications in different industries such as in healthcare systems, environment and military surveillance, manufacturing, and IoT context in general. Expanding the scope of sensor network applications has led researchers to develop solutions to provide sustainable communications and networks for distributed environments, as well as how to secure these methods with limited resources. Methods: The lack of infrastructure space and the vulnerable nature of these networks make it difficult to design security models and algorithms for them. So, to run the sensor network in safe mode, any type of attack must be detected before any security breach is materialized. According to the importance of the network and also the nature of the sensor networks along with the critical challenge of energy consumption, solutions and defensive lines such as intrusion prevention and intrusion detection systems will be selected. Results: This paper surveys subjectively the intrusion and anomaly detection system in WSNs to determine potentials and challenges for further processing. Therefore, designing an efficient and optimal intrusion detection solution applicable to wireless sensor networks, IoT, and other ad-hoc networks has been a major challenge that will help the researcher to design or choose the best approach for their future research. Conclusion: This research also paves the way of interested researchers to find existing challenges and shortcomings for further processing.
Energy-Efficient Intrusion Detection in Wireless Sensor Network
The use of Wireless Sensor Networks (WSNs) has developed rapidly in the last decade. Deploying tiny sensors with limited battery power in open and unprotected environment and dynamic topology in WSNs raises security issues in this kind of networks. Attacks can occur from any direction and any node in WSNs, so one crucial security challenge is to detect networks’ intrusion. There are several algorithms for building Intrusion Detection Systems (IDS) based on different WSN routing protocol classifications with respect to energy-efficient manner. This paper provides an overview of the research on IDS in WSNs, focusing on routing protocol classification depending on network structure with respect to energy consumption as a crucial parameter in these kinds of networks. In addition, some simulation manners are reviewed.
MACHINE LEARNING BASED WATCHDOG PROTOCOL FOR WORMHOLE ATTACK DETECTION IN WIRELESS SENSOR NETWORKS
The wormhole attack in Wireless sensor networks (WSNs) decreases the network performance by dropping the No. of Packets. Many techniques have been proposed to so far reduce the impact of the wormhole attack by detecting and preventing it. But, related work indicates that no technique is perfect for every kind of circumstances of WSNs. Among the existing techniques, Watchdog technique has better performance in preventing the wormhole attack. It utilizes the local knowledge of the next hop node and eavesdrops it. If it gets that spending time of the Packet is more than the given threshold, then it characterizes that node as wormhole attacker. However, this method has several shortcomings that it does not track the link transmission errors, which may be because of congestion in WSNs and also it not offers high mobility for maximum No. of nodes, which eventually decreases the WSNs performance. In order to handle this issue, a new multipoint relay based Watchdog monitoring and prevention technique is proposed in this paper. The proposed technique utilizes the dynamic threshold value to detect the wormhole attacker node, and then clustering and the Watchdog based optimistic path is selected for communicating the Packets. Thus, it reduces the overall Packet dropping, which improves the performance of the WSNs.
Intrusion Detection for Routing Attacks in Sensor Networks
International Journal of Distributed Sensor Networks, 2006
Security is a critical challenge for creating robust and reliable sensor networks. For example, routing attacks have the ability to disconnect a sensor network from its central base station. In this paper, we present a method for intrusion detection in wireless sensor networks. Our intrusion detection scheme uses a clustering algorithm to build a model of normal traffic behavior, and then uses this model of normal traffic to detect abnormal traffic patterns. A key advantage of our approach is that it is able to detect attacks that have not previously been seen. Moreover, our detection scheme is based on a set of traffic features that can potentially be applied to a wide range of routing attacks. In order to evaluate our intrusion detection scheme, we have extended a sensor network simulator to generate routing attacks in wireless sensor networks. We demonstrate that our intrusion detection scheme is able to achieve high detection accuracy with a low false positive rate for a variety of simulated routing attacks.
Perceive the Packet Drops in Wireless Sensor Networks using New Secure Cuckoo Filter
Bloom Filters are used for high speed set membership tests in large scale sensor networking systems. It allows a small part of false positive answers with very good space effectiveness. However, it does not permit deletion of items from the set, and before attempts to make bigger " standard " Bloom filters to support deletion all degrade of both space or performance. A malicious adversary may initiate further nodes in the network or confrontation previous ones. Therefore, assuring high data responsibility is crucial for correct decision-making. Data provenance represents a key factor in evaluating the responsibility of sensor data. Provenance management for sensor networks introduces more than a few challenging requirements, such as low energy and bandwidth consumption, efficient storage and secure transmission. For the reason propose a novel lightweight scheme to securely transmit provenance for sensor data. And introduce resourceful mechanisms for provenance verification and reconstruction at the base station. In addition, it extends the secure provenance scheme with functionality to detect packet drop attacks staged by malicious data forwarding nodes, propose a new data structure called the cuckoo filter that can replace Bloom filters for approximate set membership tests. Cuckoo filters support adding and removing items dynamically while achieving even higher performance than Bloom filters.
2021
Wireless networks are gaining popularity to its peak today, as the users want wireless connectivity irrespective of their geographic position. There is an increasing threat of attacks on the wireless sensor network (WSN). Wormhole attack is one of the security threat in which the traffic is redirected this type of node that honestly does no longer exist inside the network. This paper is proposed neural network (NN) for optimization and multicast routing protocol approach for attack detection and prevention. The measurements were taken in terms of throughput, end-toend delay and network load.
DIFFERENT} {INTRUSION} {AND} {ITS} {DETECTION} {OF} {WIRELESS} {SENSOR} {NETWORK}: A {REVIEW}~
Wireless Sensor Network (WSN) has become an emerging technology of wireless communication and computing. Wireless Sensor Network is a self-configured, infrastructure-less wireless network which comprises of a few to large number of spatially distributed autonomous sensor nodes and a base station. The function of the base station is to interface user and network. A sensor node combines hardware and software. The main deployment of sensor network is sensing, data processing and transmitting data. WSN has different application in enemy intrusion detection in the battlefield in the military application, medical field, atmospheric disaster, agricultural and industrial applications. In Wireless sensor network each node is a battery-operated low power device and operated in ad-hoc principle, which indicates network power is mainly dependent on rate of energy consumption. Ad-hoc networking nature of WSN allows the attacker for different types of attacks from passive eavesdropping to active attacks. As WSN requires hop by hop routing to transport the packets to the destination, any intermediate node acting maliciously can drop, modify or misguide the traffic traversing through it. Confidentiality, authenticity, integrity, data freshness and quality of service (QoS) are the most important issues for wireless sensor nodes. An attacker may collect and destroy sensitive information if the transmission is not properly encrypted. However, avoiding collision and providing cooperation among the nodes during the transmission are done by using medium access control protocols. This paper focuses on the security threats on the resource restricted design and deployment characteristics along with the requirements to design a secured WSN system. In this paper wormhole attacks, black hole attacks, Sybil attacks, hello flood attack, denial of service attacks and private attacks are investigated. In this paper different link layer attacks are also discussed. Not only does this document about the popular attacks in different layers of WSN, but also provides some remedies against these attacks.