A Novel Design of FANET Routing Protocol Aided 5G Communication Using IoT

Khan, Inam Ullah; Abdollahi, Asrin; Jamil, Abdul; Baig, Bisma; Aziz, Muhammad Adnan; Subhan, Fazal

doi:10.13052/jmm1550-4646.1851

Cited by 7 publications

(4 citation statements)

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“…FANET nodes need to be lightweight devices like RPi in order to be easily integrated into a unmanned vehicle man-aging system's primary tasks (autopilot, sensing) along with other, lateral operations. RPis are commonly used, as shown in [28] and [29], as they offer a powerful operating system with several functionalities in a lightweight package.…”

Section: System Architecturementioning

confidence: 99%

Optimizing IoT security via TPM integration: An energy efficiency case study for node authentication

Anestis Papakotoulas,

Theodoros Mylonas,

Kakia Panagidi

et al. 2024

ITU J-FET

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The widespread adoption of Internet of Things (IoT) applications in different technical fields has resulted in a significant increase in connected devices while amplifying concerns regarding security and privacy. The presence of security vulnerabilities in various layers of IoT design has emerged as an important issue. Trusted computing, particularly leveraging the Trusted Platform Module (TPM), is seen as a promising approach to counter these vulnerabilities. This paper investigates thoroughly the utilization of TPM technology to enhance node authentication with a focus on energy efficiency. Researchers closely examine each layer to carefully outline an adversary model that is tailored to the IoT ecosystem. The node authentication scheme that is proposed leverages TPM, which has advantages both in terms of processing time and energy. The outcome of this study can be applied to Flying AdHoc Network (FANET) nodes that operate in areas with high levels of traffic, where there are strict safety and reliability standards. Experiments conducted present the essential significance of TPM in ensuring secure node authentication across various application environments. The adoption of TPM technology is validated through rigorous performance assessments, revealing significant improvements in both energy efficiency and security.

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Section: System Architecturementioning

confidence: 99%

Optimizing IoT security via TPM integration: An energy efficiency case study for node authentication

Anestis Papakotoulas,

Theodoros Mylonas,

Kakia Panagidi

et al. 2024

ITU J-FET

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“…The progress of wireless communication technology was thoroughly compared and evaluated for various parameter configurations in this research study [28]. The architecture, optimization techniques, mobility models, heuristic calculations, and routing protocols used in flying ad hoc networks were all explicitly covered in the introduction [29]. This study covered the issue of energy conservation for flying IoT.…”

Section: Related Workmentioning

confidence: 99%

Energy Based Random Repeat Trust Computation in Delay Tolerant Network

Dheenathayalan¹,

Paramasivan²

2023

Computer Systems Science and Engineering

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As the use of mobile devices continues to rise, trust administration will significantly improve security in routing the guaranteed quality of service (QoS) supply in Mobile Ad Hoc Networks (MANET) due to the mobility of the nodes. There is no continuance of network communication between nodes in a delay-tolerant network (DTN). DTN is designed to complete recurring connections between nodes. This approach proposes a dynamic source routing protocol (DSR) based on a feed-forward neural network (FFNN) and energybased random repetition trust calculation in DTN. If another node is looking for a node that swerved off of its path in this situation, routing will fail since it won't recognize it. However, in the suggested strategy, nodes do not stray from their pathways for routing. It is only likely that the message will reach the destination node if the nodes encounter their destination or an appropriate transitional node on their default mobility route, based on their pattern of mobility. The EBRRTC-DTN algorithm (Energy based random repeat trust computation) is based on the time that has passed since nodes last encountered the destination node. Compared to other existing techniques, simulation results show that this process makes the best decision and expertly determines the best and most appropriate route to send messages to the destination node, which improves routing performance, increases the number of delivered messages, and decreases delivery delay. Therefore, the suggested method is better at providing better QoS (Quality of Service) and increasing network lifetime, tolerating network system latency.

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“…Therefore, nature inspired E-AntHocNet has improved overall standards of communication. But still security is the main concern which needs to be addressed with possible solutions [14][15][16]. Machine learning technique decision tree enhance connectivity in between nodes by using received signal strength indicator (RSSI).…”

Section: Literature Surveymentioning

confidence: 99%

An Intelligent Machine Learning based Intrusion Detection System (IDS) for Smart cities networks

Ayub,

Haider,

Haider

et al. 2023

EAI Endorsed Trans Smart Cities

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INTRODUCTION: Internet of Things (IoT) along with Cloud based systems are opening a new domain of development. They have several applications from smart homes, Smart farming, Smart cities, smart grid etc. Due to IoT sensors operating in such close proximity to humans and critical infrastructure, there arises privacy and security issues. Securing an IoT network is very essential and is a hot research topic. Different types of Intrusion Detection Systems (IDS) have been developed to detect and prevent an unauthorized intrusion into the network.OBJECTIVES: The paper presents a Machine Learning based light, fast and reliable Intrusion Detection System (IDS).METHODS: Multiple Supervised machine learning algorithms are applied and their results are compared. Algorithms applied include Linear Discriminant analysis, Quadratic Discriminant Analysis, XG Boost, KNN and Decision Tree.RESULTS: Simulation results showed that KNN Algorithm gives us the highest accuracy, followed by XG Boost and Decision Tree which are not far behind.CONCLUSION: A fast, secure and intelligent IDS is developed using machine learning algorithms. The resulting IDS can be used in various types of networks especially in IoT based networks.

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A Novel Design of FANET Routing Protocol Aided 5G Communication Using IoT

Cited by 7 publications

References 0 publications

Optimizing IoT security via TPM integration: An energy efficiency case study for node authentication

Optimizing IoT security via TPM integration: An energy efficiency case study for node authentication

Energy Based Random Repeat Trust Computation in Delay Tolerant Network

An Intelligent Machine Learning based Intrusion Detection System (IDS) for Smart cities networks

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