Recent Advances in Attacks, Technical Challenges, Vulnerabilities and Their Countermeasures in Wireless Sensor Networks

Bhushan, Bharat; Sahoo, G.

doi:10.1007/s11277-017-4962-0

Cited by 151 publications

(64 citation statements)

References 115 publications

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“…Then, the potential security threats are detected in the paper at various protocol layers. Here, different security attacks are recognized along with their countermeasures assessed by various investigators recently [15].…”

Section: Related Workmentioning

confidence: 99%

A novel countermeasure technique to protect WSN against denial-of-sleep attacks using firefly and Hopfield neural network (HNN) algorithms

Fotohi

Bari

2020

J Supercomput

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Wireless Sensor Networks (WSN) contain numerous nodes that their main goals are to monitor and control environments. Also, sensor nodes distribute based on network usage. One of the most significant issues in this type of network is the energy consumption of sensor nodes. In fixed-sink networks, nodes which are near the sink act as an interface to transfer data of other nodes to sink. This causes the energy consumption of sensors reduces rapidly. Therefore, the lifetime of the network declines. Sensor nodes owing to their weaknesses are susceptible to several threats, one of which is Denial of Sleep Attack (DoSA) threating WSN. Hence, the DoSA attack refers to the energy loss in these nodes by maintaining the nodes from entering energy-saving and sleep mode. In this paper, a hybrid approach is proposed based on mobile sink, firefly algorithm based on leach, and Hopefield Neural Network (WSN-FAHN). Thus, mobile sink is applied to both improve energy consumption and increase network lifetime. Firefly algorithm is proposed to cluster nodes and authenticate in two levels to prevent from DoSA. In addition, Hopefield Neural Network detects the direction route of the sink movement to send data of CH. Furthermore, here WSN-FAHN technique is assessed through wide simulations performed in the NS-2 environment. The WSN-FAHN procedure superiority is demonstrated by simulation outcomes in comparison with contemporary schemes based on performance metrics like Packet Delivery Ratio (PDR), average throughput, detection ratio, and network lifetime while decreasing the average residual energy.

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Section: Related Workmentioning

confidence: 99%

A novel countermeasure technique to protect WSN against denial-of-sleep attacks using firefly and Hopfield neural network (HNN) algorithms

Fotohi

Bari

2020

J Supercomput

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“…In WSNs, the most severe threat is wormhole attacks [10] [11]. Generally, this type of attack is launched by two or more malicious nodes having a private channel, called a tunnel, between them.…”

Section: A Wormhole Attacksmentioning

confidence: 99%

“…With the advantages of low cost, large scale, densely distributed deployment and self-configuration [6], WSNs are widely used for industrial control, logistics management, environmental monitoring, military defense, and civilian life [7], [8], most of which support range of time and data sensitive applications and have high requirements for safety. However, as a consequence of distinctive open nature, limited resource availability, infrastructure less and self-governing nature, WSNs are very delicate to many attacks [9], [10].…”

Section: Introductionmentioning

confidence: 99%

CREDND: A Novel Secure Neighbor Discovery Algorithm for Wormhole Attack

Luo

Chen

et al. 2019

IEEE Access

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As nodes' characteristics that they are self-governed and resource-limited, wireless sensor networks (WSNs) face potential threats due to various attacks, among which the most threatening attack is wormhole attack. Wormhole attack severely imperils WSNs and is difficult to be detected, for it causes incorrect routing by private tunnels and damages to WSNs in terms of data leakage, data dropping, and delayed delivery. However, the existing solutions are based on additional hardware, incur high communication overhead, or fail to give consideration to all types of wormholes. In this paper, we propose CREDND, a protocol for creating a Credible Neighbor Discovery against wormholes in WSN, which can detect not only external wormholes through the hop difference between the own exclusive neighbors but also internal wormholes through enabling the common neighbor nodes as witnesses to monitor whether the authentication packets are forwarded by malicious nodes. CREDND is a simple, localized protocol and needs no special hardware, localization, or synchronization, but it improves the ability of wormhole defense. The simulation results are provided, showing that CREDND outperforms in wormhole detection than other same types of solutions. INDEX TERMS Secure neighborhood, neighbor discovery, network security, wireless sensor networks, wormhole attack.

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“…• Fabrication These attacks are manifested by the injection of erroneous data into the WSN. Attacker aims to threaten message authenticity and network availability through the depletion of the energy resources of the network especially with wireless communications which are very energy intensive [32].…”

Section: • Modificationmentioning

confidence: 99%

Attacks classification and security mechanisms in Wireless Sensor Networks

Kardi¹,

Zagrouba²

2019

Adv. sci. technol. eng. syst. j.

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This paper proposes a new classification model distinguishing four classes of attacks in Wireless Sensor Networks (WSNs) namely: attacks based on the protocol stack, on the capability of the attacker, on the attack impacts and on the attack target. Then, it presents and classifies the most known attacks in WSNs based the proposed model. Simulations implemented under the NS3 simulator prove that the network lifetime can decrease by more than 45% in the presence of attacks. Afterwards, it discusses the main security methods and protocols of management and distribution of encryption keys used to ward off different types of attacks. Obtained results confirm that these security methods must be adapted to the specific characteristics of WSNs to achieve the intended objectives.

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Recent Advances in Attacks, Technical Challenges, Vulnerabilities and Their Countermeasures in Wireless Sensor Networks

Cited by 151 publications

References 115 publications

A novel countermeasure technique to protect WSN against denial-of-sleep attacks using firefly and Hopfield neural network (HNN) algorithms

A novel countermeasure technique to protect WSN against denial-of-sleep attacks using firefly and Hopfield neural network (HNN) algorithms

CREDND: A Novel Secure Neighbor Discovery Algorithm for Wormhole Attack

Attacks classification and security mechanisms in Wireless Sensor Networks

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