New Framework for Authentication and key Establishment to Secure 6LoWPAN Networks

Alshrif, Fatma Foad; Sundararajan, Elankovan; Ahmad, Rami; Alkhatib, Yousef

doi:10.1109/iceei52609.2021.9611135

Cited by 10 publications

(3 citation statements)

References 30 publications

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“…Authentication refers to a set of security forces that ensure data have come from the source and have not been tampered with along the way [136]. Its approach ensures that active attacks, such as DoS and spoofing are mitigated.…”

Section: Authenticationmentioning

confidence: 99%

Machine Learning for Wireless Sensor Networks Security: An Overview of Challenges and Issues

Ahmad

Wazirali

Abu-Ain

2022

Sensors

Self Cite

112

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Energy and security are major challenges in a wireless sensor network, and they work oppositely. As security complexity increases, battery drain will increase. Due to the limited power in wireless sensor networks, options to rely on the security of ordinary protocols embodied in encryption and key management are futile due to the nature of communication between sensors and the ever-changing network topology. Therefore, machine learning algorithms are one of the proposed solutions for providing security services in this type of network by including monitoring and decision intelligence. Machine learning algorithms present additional hurdles in terms of training and the amount of data required for training. This paper provides a convenient reference for wireless sensor network infrastructure and the security challenges it faces. It also discusses the possibility of benefiting from machine learning algorithms by reducing the security costs of wireless sensor networks in several domains; in addition to the challenges and proposed solutions to improving the ability of sensors to identify threats, attacks, risks, and malicious nodes through their ability to learn and self-development using machine learning algorithms. Furthermore, this paper discusses open issues related to adapting machine learning algorithms to the capabilities of sensors in this type of network.

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Section: Authenticationmentioning

confidence: 99%

Machine Learning for Wireless Sensor Networks Security: An Overview of Challenges and Issues

Ahmad

Wazirali

Abu-Ain

2022

Sensors

Self Cite

112

View full text Add to dashboard Cite

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“…Engaging in Personal Interactive Transmission Sessions via TCP streams may introduce difficulties concerning the security of transmitting personal data, the integrity of communication, and possible limitations in performance [7]. The Common Weakness Enumeration (CWE) 319: "Cleartext Transmission of Sensitive Information" Web Application Vulnerabilities Index focuses on the possible risk of personal or confidential data being transmitted without encryption, which could result in the data being exposed in cleartext or plaintext and susceptible to eavesdropping by unauthorised individuals [8].…”

Section: Introductionmentioning

confidence: 99%

Examining Potential Threats of Eavesdropping in TCP Stream of Personal Interactive Transmission Session

Abubakar,

Muhammed Najmuddin,

Mohd Alwi

et al. 2024

IJPCC

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This study establishes that Personal Interactive Transmission Sessions conducted using TCP streams provide exceptional convenience and immediacy. However, they also provide noteworthy challenges and considerations, especially in terms of security, integrity, and performance. This study investigates the security weaknesses present in potential eavesdropping threats on TCP Streams during personal interactive transmission sessions. An experimental analysis was carried out, by doing a comprehensive analysis of network traffic using Wireshark. The investigation reveals a notable vulnerability in the management of user-provided data, together with the possible risks of eavesdropping, emphasizing the urgent need for enhanced security measures. The findings underscore the need of proactive cybersecurity strategies, such as frequent security audits, vulnerability assessments, and the implementation of robust encryption methods, to safeguard user privacy and ensure data integrity. To enhance risk mitigation, data protection, and user confidence in the digital environment, organizations should prioritize addressing potential eavesdropping threats during transmission sessions that involve sensitive personal data.

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“…Some of these lightweight encryption algorithms were analyzed in [14] to show that AES requires a high rate of power consumption. Furthermore, other works have proposed lightweight authentication algorithms for WSN [15] and others have used watermarking technology for the authentication process also [16] to reduce security costs and extend the WSN lifetime.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Trust-Based Framework for Securing and Reducing Cost in Low-Cost 6LoWPAN Wireless Sensor Networks

et al. 2022

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Wireless Sensor Networks (WSNs) are the core of the Internet of Things (IoT) technology, as they will be used in various applications in the near future. The issue of security and power consumption is still one of the most important challenges facing this type of network. 6LoWPAN protocol was developed to meet these challenges in networks with limited power and resources. The 6LoWPAN uses a hierarchical topology and the traditional method of encryption and key management, keeping power consumption levels high. Therefore, in this paper, a technique has been developed that helps in balancing security and energy consumption by exploiting the Trust technique between low-cost WSN nodes called Trust-Cluster Head (Trust-CH). Trust between nodes is built by monitoring the behavior of packet transmission, the number of repetitions and the level of security. The Trust-CH model provides a dynamic multi-level encryption system that depends on the level of Trust between WSN nodes. It also proposes a dynamic clustering system based on the absolute-trust level in the mobile node environment to minimize power consumption. Along with a set of performance metrics (i.e., power consumption and network lifetime), the Cooja simulator was used to evaluate the Trust-CH model. The results were compared to a static symmetric encryption model together with various models from previous studies. It has been proven that the proposed model increases the network lifetime by 40% compared to previous studies, as well as saves as much as 28% power consumption in the case of using a static encryption model. While maintaining the proposed model’s resistance to many malicious attacks on the network.

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New Framework for Authentication and key Establishment to Secure 6LoWPAN Networks

Cited by 10 publications

References 30 publications

Machine Learning for Wireless Sensor Networks Security: An Overview of Challenges and Issues

Machine Learning for Wireless Sensor Networks Security: An Overview of Challenges and Issues

Examining Potential Threats of Eavesdropping in TCP Stream of Personal Interactive Transmission Session

Adaptive Trust-Based Framework for Securing and Reducing Cost in Low-Cost 6LoWPAN Wireless Sensor Networks

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