Practical overview of security issues in wireless sensor network applications

Radhappa, Harish; Pan, Lei; Zheng, Xi; Wen, Sheng

doi:10.1080/1206212x.2017.1398214

Cited by 34 publications

(27 citation statements)

References 19 publications

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“…If the trusted third party wants to conduct periodic data integrity detection, the value of r can be moderate at this time. If the current network fluctuates greatly or the soft and hard environment is lack, the value of r can be reduced [14,15].…”

Section: Start Challengementioning

confidence: 99%

Detection Method of Data Integrity in Network Storage Based on Symmetrical Difference

Ding¹

2020

Symmetry

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In order to enhance the recall and the precision performance of data integrity detection, a method to detect the network storage data integrity based on symmetric difference was proposed. Through the complete automatic image annotation system, the crawler technology was used to capture the image and related text information. According to the automatic word segmentation, pos tagging and Chinese word segmentation, the feature analysis of text data was achieved. Based on the symmetrical difference algorithm and the background subtraction, the feature extraction of image data was realized. On the basis of data collection and feature extraction, the sentry data segment was introduced, and then the sentry data segment was randomly selected to detect the data integrity. Combined with the accountability scheme of data security of the trusted third party, the trusted third party was taken as the core. The online state judgment was made for each user operation. Meanwhile, credentials that cannot be denied by both parties were generated, and thus to prevent the verifier from providing false validation results. Experimental results prove that the proposed method has high precision rate, high recall rate, and strong reliability.

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Section: Start Challengementioning

confidence: 99%

Detection Method of Data Integrity in Network Storage Based on Symmetrical Difference

Ding¹

2020

Symmetry

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“…We are talking here about cryptanalysis. In this section, we talk about cryptography and the cryptographic systems used to secure the WSNs [86] [87].…”

Section: Basic Security Mechanisms In Wsnsmentioning

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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“…Wang et al [9] and Radhappa et al [10] summarized the current problems and open research questions that exist in wireless sensor networks. However, intrusion detection is not handled by them, with regard to port scanner and network mapping on low performance edge node devices.…”

Section: Related Workmentioning

confidence: 99%

Network Scanning and Mapping for IIoT Edge Node Device Security

Niedermaier

Fischer

Merli

et al. 2019

2019 International Conference on Applied Electronics (AE)

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The amount of connected devices in the industrial environment is growing continuously, due to the ongoing demands of new features like predictive maintenance. New business models require more data, collected by IIoT edge node sensors based on inexpensive and low performance Microcontroller Units (MCUs). A negative side effect of this rise of interconnections is the increased attack surface, enabled by a larger network with more network services. Attaching badly documented and cheap devices to industrial networks often without permission of the administrator even further increases the security risk. A decent method to monitor the network and detect "unwanted" devices is network scanning. Typically, this scanning procedure is executed by a computer or server in each sub-network. In this paper, we introduce network scanning and mapping as a building block to scan directly from the Industrial Internet of Things (IIoT) edge node devices. This module scans the network in a pseudo-random periodic manner to discover devices and detect changes in the network structure. Furthermore, we validate our approach in an industrial testbed to show the feasibility of this approach.

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Practical overview of security issues in wireless sensor network applications

Cited by 34 publications

References 19 publications

Detection Method of Data Integrity in Network Storage Based on Symmetrical Difference

Detection Method of Data Integrity in Network Storage Based on Symmetrical Difference

Attacks classification and security mechanisms in Wireless Sensor Networks

Network Scanning and Mapping for IIoT Edge Node Device Security

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