A Survey on Various Attacks and Countermeasures in Wireless Sensor Networks

Santhi, G.; Sowmiya, R.

doi:10.5120/ijca2017912972

Cited by 11 publications

(6 citation statements)

References 9 publications

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“…The neighbor nodes are faked by the adversary. The sinkhole attack able to drop the data packets or forward them to another attack, or tamper it with aggregated data [13], [14].…”

Section: B Sinkhole Attacksmentioning

confidence: 99%

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Secure and Energy-Efficient Data Aggregation Method Based on an Access Control Model

et al. 2019

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Wireless sensor networks (WSNs) consist of a large number of sensor nodes that are distributed to capture the information about an area of interest. In WSN, many of the secure data aggregation works are conducted without addressing the authentication process. It is challenging to implement authentication while preserving the energy consumption in the network. The previous research that focus on these issues have several limitations, such as sharing the security key and the key length with a base station node, and not much attention is given to enhance the authentication of the Medium Access Control (MAC) server. This makes the data aggregation network are exposed to malicious activities. This paper presents a new protocol to address the security and energy issue in Wireless Sensor Network (WSN). This newly developed protocol is named Secure and Energy-Efficient Data Aggregation (SEEDA), which is the extension of SDAACA protocol. The proposed protocol aims to enhance authentication by generating a random value and random timestamp with a secret key. The base station node will verify the fake aggregated data when the packets are received using the generated key earlier. Furthermore, the attacks are detected and prevented by utilizing secure node authentication, data fragmentation algorithms, fully homomorphic encryption, and access control model. The secure node authentication algorithm prevents attacks from accessing the network. To avoid network delays, the base station node utilizes the distance information between the participating nodes. To ensure the reliability of our proposed method, we simulate two well-known attacks, called Sybil and sinkhole attacks. Several experimental scenarios are conducted to observe their effect. Evaluation metrics such as malicious activity detection rate, energy consumption, end-to-end delay, and resilience time are measured. The performance of the proposed protocol is compared with SDA, SDAT, SDALFA, EESSDA, SDAACA, and EESDA, which is a widely used protocol in the area of secure data aggregation. The simulation results show that the proposed SEEDA method outperforms the existing scheme with 98.84% malicious nodes detection rate, 3.04 joules for energy consumption, the maximum delay of 0.038 seconds, and the resilient time 0.054, 0.075 seconds when 8%,16% of malicious nodes affecting the network.

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“…The neighbor nodes are faked by the adversary. The sinkhole attack able to drop the data packets or forward them to another attack, or tamper it with aggregated data [13], [14].…”

Section: B Sinkhole Attacksmentioning

confidence: 99%

“…Other than that, the Sybil attack can affect the data aggregation in the network by claiming a fake ID. The malicious node can also steal an identity to enable them to join into the network [3], [12], [13].…”

Section: Introductionmentioning

confidence: 99%

Secure and Energy-Efficient Data Aggregation Method Based on an Access Control Model

et al. 2019

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“…Through this process, a malicious node is inserted into the WSNs to set up false routing information and camouflage it as a regular node. In other words, information is collected from the inserted malicious node, and it is transmitted to a strategic node where packets are analyzed systematically [40].…”

Section: ) Camouflagementioning

confidence: 99%

A Survey on Security Requirements for WSNs: Focusing on the Characteristics Related to Security

Lee

et al. 2020

IEEE Access

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As WSNs combine with a diversity of next-generation technologies, wireless sensor networks (WSNs) have gained considerable attention as a promising ubiquitous technology. Even though several studies on WSNs are being undertaken, few systematically analyze the security issues relating to them. Moreover, recent systems tend to be implemented without sufficient consideration about owns security requirements, which can lead to lethal threats. Systems that do not consider security requirements may provide attackers the opportunity to reduce the overall efficiency and performance of the system. This means that inadequately applied security requirements can result in defective security of systems. Therefore, in this study, we emphasized the importance of security requirements to raise awareness regarding them. In addition, we analyzed literature that could be improved by including WSNs security requirements such as characteristics, constraints, and threats. Furthermore, we adopted a systematic methodology by referring to reliable literature and performed a different analysis from previous studies. We derived and mapped the different security factors based on the literature and illustrated the relationships of each security factor. Finally, our research compared with studies of a similar type to evaluate whether it provided a significant contribution. In other words, in this study, we analyzed various factors related to WSNs security based on reviewing the literature and show our contribution, such as a systematic analysis framework and factor mapping compared with traditional studies. Though there are some considerations, we expect that this research derived the essential security requirements in any WSNs environments. INDEX TERMS Wireless sensor network, security requirement, next-generation technologies.

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“…This technique causes a disturbance of the network operation or a denial of service (DoS) [ 29 ]. The active attacks can be initiated on five different layers of communication protocols [ 28 , 30 ]: physical layer attacks (where an attacker easily jams or intercepts any ongoing signal) [ 31 ], link-layer attacks (here, the attack is performed against the Media Access Control Protocol [ 32 ]), network layer attacks (including hello flood, wormhole attack, Sybil attack, selective forwarding, spoofed, and altered or replayed routing information [ 33 , 34 ]), transport layer attack (which mainly concerns flooding and desynchronization [ 33 ]), and the application layer attack, where an attacker attempts to overload the network nodes with sensor stimuli, triggering the network to forward massive volumes of traffic to a base station [ 35 ]. The application layer attacks include clock skewing, selective message forwarding, and data aggregation forwarding [ 36 ].…”

Section: Related Workmentioning

confidence: 99%

A Security Concept Based on Scaler Distribution of a Novel Intrusion Detection Device for Wireless Sensor Networks in a Smart Environment

Boni

Chen

et al. 2020

Sensors

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Following the significant improvement of technology in terms of data collection and treatment during the last decades, the notion of a smart environment has widely taken an important pedestal in the science industry. Built in order to better manage assets, smart environments provide a livable environment for users or citizens through the deployment of sensors responsible for data collection. Much research has been done to provide security to the involved data, which are extremely sensitive. However, due to the small size and the memory constraint of the sensors, many of these works are difficult to implement. In this paper, a different concept for wireless sensor security in smart environments is presented. The proposed security system, which is based on the scaler distribution of a novel electronic device, the intrusion detection system (IDS), reduces the computational functions of the sensors and therefore maximizes their efficiency. The IDS also introduces the concept of the feedback signal and “trust table” used to trigger the detection and isolation mechanism in case of attacks. Generally, it ensures the whole network security through cooperation with other IDSs and, therefore, eliminates the problem of security holes that may occur while adopting such a security technique.

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A Survey on Various Attacks and Countermeasures in Wireless Sensor Networks

Cited by 11 publications

References 9 publications

Secure and Energy-Efficient Data Aggregation Method Based on an Access Control Model

Secure and Energy-Efficient Data Aggregation Method Based on an Access Control Model

A Survey on Security Requirements for WSNs: Focusing on the Characteristics Related to Security

A Security Concept Based on Scaler Distribution of a Novel Intrusion Detection Device for Wireless Sensor Networks in a Smart Environment

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