Detecting Sybil attacks in Wireless Sensor Networks using neighboring information

Ssu, Kuo‐Feng; Wang, Wei-Tong; Chang, Win−Jin

doi:10.1016/j.comnet.2009.07.013

Cited by 105 publications

(84 citation statements)

References 14 publications

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“…Figure 5 indicates the experiment results for time periods 25 to 200 during the test phase. The experiment results prove that network nodes number (n) has no significant effect on detection rate of the proposed algorithm because, unlike other algorithms, such the one developed in [9], the proposed algorithm is not based on network density but on confrontation of malicious and legitimate nodes, the identities of which is captured by the enemy, in the vicinity of sink nodes. Therefore, increase or decrease of the number of nodes in the network leaves no effect on detection rate of the proposed algorithm.…”

Section: Detection Rate (%)mentioning

confidence: 82%

“…the amount of Sybil nodes detected by a security algorithm. What is more, the proposed algorithm performance is compared with those given in [8][9][10]13,14,16], in terms of average detection rate and average rate of error.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…It is enough to identify the target nodes because all Sybil nodes are located in a same area. The method which is developed in [9] for detecting Sybil nodes needs no hardware or information about signal strength yet it solely uses data regarding the number of neighbors to identify malicious node and fake (Sybil) identities. The algorithm functions in a distributed manner based on no central point such as base stations or specific nodes (location-aware).…”

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

A Lightweight Algorithm for Detecting Sybil Attack in Mobile Wireless Sensor Networks using Sink Nodes

Andalib¹,

Jamshidi²,

Andalib³

et al. 2016

IJCATR

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Considering the application of wireless sensor networks in critical area, such as battlefields, establishing security in these networks is of utmost importance. One of the most serious and dangerous attack against these networks is Sybil attack. In this attack, a malicious hostile node creates multiple fake identities simultaneously. This misleads legitimate nodes and, by mistake, they assume each of these identifiers as real separate nodes. In this attack, malicious hostile node attracts so heavy traffic that can dramatically disrupt routing protocols which has devastating effects on the network functions such as data integration, voting, and resource allocation. The current research proposes a new lightweight algorithm for detecting Sybil attack in Mobile Wireless Sensor Networks using sink nodes. The proposed algorithm is implemented to be assessed in terms of detection and error rates efficiency in a series of experiments. Comparison of the experiment results with the results of other available algorithms revealed optimal performance of the proposed algorithm.

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Section: Detection Rate (%)mentioning

confidence: 82%

Section: Simulation Resultsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

A Lightweight Algorithm for Detecting Sybil Attack in Mobile Wireless Sensor Networks using Sink Nodes

Andalib¹,

Jamshidi²,

Andalib³

et al. 2016

IJCATR

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show abstract

“…One of the techniques under non-location-based category, as far as we could identify, is the Radio resource testing [6]. The techniques under the upper-layers-based category are further divided to neighborhood-based [7,8], code attestation-based [9][10][11], authentication-based (puzzle solving technique [12] for peer-to-peer networks, Identity certificate technique [13]), and identity registration-based [14]. Figure 1 illustrates the Sybil attack detection techniques categorization.…”

Section: Introductionmentioning

confidence: 99%

A New Lightweight Watchdog-Based Algorithm for Detecting Sybil Nodes in Mobile WSNs

et al. 2017

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Abstract:Wide-spread deployment of Wireless Sensor Networks (WSN) necessitates special attention to security issues, amongst which Sybil attacks are the most important ones. As a core to Sybil attacks, malicious nodes try to disrupt network operations by creating several fabricated IDs. Due to energy consumption concerns in WSNs, devising detection algorithms which release the sensor nodes from high computational and communicational loads are of great importance. In this paper, a new computationally lightweight watchdog-based algorithm is proposed for detecting Sybil IDs in mobile WSNs. The proposed algorithm employs watchdog nodes for collecting detection information and a designated watchdog node for detection information processing and the final Sybil list generation. Benefiting from a newly devised co-presence state diagram and adequate detection rules, the new algorithm features low extra communication overhead, as well as a satisfactory compromise between two otherwise contradictory detection measures of performance, True Detection Rate (TDR) and False Detection Rate (FDR). Extensive simulation results illustrate the merits of the new algorithm compared to a couple of recent watchdog-based Sybil detection algorithms.

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“…Ssu et al [23] proposed a scheme based on the assumption that probability of two nodes having exactly the same set of neighbours was extremely low provided that a network had a high node density. They argued that forged identities typically had the same set of neighbours because they were all associated with the same physical device.…”

Section: Related Workmentioning

confidence: 99%

A Sybil attack detection scheme for a forest wildfire monitoring application

Jan

Nanda

et al. 2018

Future Generation Computer Systems

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Wireless Sensor Networks (WSNs) have experienced phenomenal growth over the past decade. They are typically deployed in human-inaccessible terrains to monitor and collect time-critical and delay-sensitive events. There have been several studies on the use of WSN in different applications. All such studies have mainly focused on Quality of Service (QoS) parameters such as delay, loss, jitter etc. of the sensed data. Security provisioning is also an important and challenging task lacking in all previous studies. In this paper, we propose a Sybil attack detection scheme for a cluster-based hierarchical network mainly deployed to monitor forest wildfire. We propose a two-tier detection scheme. Initially, Sybil nodes and their forged identities are detected by high-energy nodes. However, if one or more identities of a Sybil node sneak through the detection process, they are ultimately detected by the two base stations. After Sybil attack detection, an optimal percentage of cluster heads are elected and each one is informed using nomination packets. Each nomination packet contains the identity of an elected cluster head and an end user's specific query for data collection within a cluster. These queries are user-centric, on-demand and adaptive to an end user requirement. The undetected identities of Sybil nodes reside in one or more clusters. Their goal is to transmit high false-negative alerts to an end user for diverting attention to those geographical regions which are less vulnerable to * Corresponding author Email addresses: Priyadarsi.Nanda@uts.edu.au (Priyadarsi Nanda), Xiangjian.He@uts.edu.au (Xiangjian He) Preprint submitted to ElsevierMay 24, 2016 a wildfire. Our proposed approach has better network lifetime due to efficient sleep-awake scheduling, higher detection rate and low false-negative rate.

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Detecting Sybil attacks in Wireless Sensor Networks using neighboring information

Cited by 105 publications

References 14 publications

A Lightweight Algorithm for Detecting Sybil Attack in Mobile Wireless Sensor Networks using Sink Nodes

A Lightweight Algorithm for Detecting Sybil Attack in Mobile Wireless Sensor Networks using Sink Nodes

A New Lightweight Watchdog-Based Algorithm for Detecting Sybil Nodes in Mobile WSNs

A Sybil attack detection scheme for a forest wildfire monitoring application

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