Security Challenges of Selective Forwarding Attack and Design a Secure ECDH-Based Authentication Protocol to Improve RPL Security

Adarbah, Haitham Y.; Moghadam, Mostafa Farhadi; Maata, Rolou Lyn R.; Mohajerzadeh, Amir Hossein; Al‐Badi, Ali H.

doi:10.1109/access.2022.3221434

Cited by 6 publications

(4 citation statements)

References 65 publications

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“…Once, there was a safer method to store cryptocurrencies considered by researchers. In that method, the MITM attack [44] exposed the vulnerability of ledger hardware wallets. This attack permits a cybercriminal to create a duplicate or clone address of the cryptocurrency by showing it to the customer and utilizing the original address to deliver it to the wallet.…”

Section: Man-in-the-middle Attack [42]mentioning

confidence: 99%

Enhancing IoT Security through a Green and Sustainable Federated Learning Platform: Leveraging Efficient Encryption and the Quondam Signature Algorithm

Aljrees,

Kumar,

Singh

et al. 2023

Sensors

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This research paper introduces a novel paradigm that synergizes innovative algorithms, namely efficient data encryption, the Quondam Signature Algorithm (QSA), and federated learning, to effectively counteract random attacks targeting Internet of Things (IoT) systems. The incorporation of federated learning not only fosters continuous learning but also upholds data privacy, bolsters security measures, and provides a robust defence mechanism against evolving threats. The Quondam Signature Algorithm (QSA) emerges as a formidable solution, adept at mitigating vulnerabilities linked to man-in-the-middle attacks. Remarkably, the QSA algorithm achieves noteworthy cost savings in IoT communication by optimizing communication bit requirements. By seamlessly integrating federated learning, IoT systems attain the ability to harmoniously aggregate and analyse data from an array of devices while zealously guarding data privacy. The decentralized approach of federated learning orchestrates local machine-learning model training on individual devices, subsequently amalgamating these models into a global one. Such a mechanism not only nurtures data privacy but also empowers the system to harness diverse data sources, enhancing its analytical capabilities. A thorough comparative analysis scrutinizes varied cost-in-communication schemes, meticulously weighing both encryption and federated learning facets. The proposed approach shines by virtue of its optimization of time complexity through the synergy of offline phase computations and online phase signature generation, hinged on an elliptic curve digital signature algorithm-based online/offline scheme. In contrast, the Slow Block Move (SBM) scheme lags behind, necessitating over 25 rounds, 1500 signature generations, and an equal number of verifications. The proposed scheme, fortified by its marriage of federated learning and efficient encryption techniques, emerges as an embodiment of improved efficiency and reduced communication costs. The culmination of this research underscores the intrinsic benefits of the proposed approach: marked reduction in communication costs, elevated analytical prowess, and heightened resilience against the spectrum of attacks that IoT systems confront.

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Section: Man-in-the-middle Attack [42]mentioning

confidence: 99%

Enhancing IoT Security through a Green and Sustainable Federated Learning Platform: Leveraging Efficient Encryption and the Quondam Signature Algorithm

Aljrees,

Kumar,

Singh

et al. 2023

Sensors

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“…Routing algorithms that are often used in IoT networks are:  Routing protocol for low-power and lossy networks (RPL), commonly known as RPL, is a distance-vector routing system made for networks with low power and poor connectivity. It is made to work with devices that have limited memory, processing power, and power backup [8].  Dynamic source routing (DSR) is another reactive routing system that only finds a route between two nodes when it is needed.…”

Section: *Author For Correspondencementioning

confidence: 99%

Investigating the performance vulnerability of AODV protocol of IoT network under SYN-flood attack

2023

IJATEE

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Wireless technology is utilized by various Internet of Things (IoT) devices, such as smartphones, drones, and cameras, to establish multiple inter-device connections simultaneously. The flexibility of wireless networks allows users to create IoTbased ad-hoc networks on demand. This connectivity enables linking hundreds to thousands of people, leading to significant enhancements in productivity and profitability. However, the flexibility of the IoT network also introduces a range of threats that require attention. The primary research methodology employed in this study was simulation to investigate and identify existing vulnerabilities or loopholes in the transport layer of IoT networks that use the ad-hoc ondemand distance vector (AODV) routing protocol. The simulation software utilized was NetSim 12.02, which is based on the Institute of Electrical and Electronics Engineers (IEEE) 802.15.4 standard. We conducted simulations of synchronization (SYN) flood attacks on IoT networks by exploiting vulnerabilities in the underlying protocol. The tests and data collection for this study were conducted using the simulation software. The research demonstrates that the transport layer of the IoT network, when utilizing the AODV protocol, can be compromised to launch a SYN-flood attack,resulting in severe performance degradation of the system. The results demonstrate that SYN-flood attack nodes result in a decrease in throughput ranging from 9.1% to 17.79%, an increase in delay ranging from 1.08% to 3.26%, and an increase in network jitter ranging from 15.4% to 22.88%. These findings can assist IoT network administrators in better planning and implementing preventive measures against SYN flood attacks on IoT networks that utilize the AODV protocol.

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“…VANETs use Certificate Authorities (CAs) to authenticate automobiles and roadside equipment. Building trust in VANETs is very important because it is what makes safety-critical applications like avoiding collisions, managing traffic flow, and planning routes dynamically possible [74], [34], [8] work. However, relying on centralized CAs has significant concerns.…”

Section: Introductionmentioning

confidence: 99%

A New Framework for Enhancing VANETs through Layer 2 DLT Architectures with Multi-Party Threshold Key Management and PETs

Adarbah,

Kiraz,

Kardas

et al. 2024

Preprint

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This study provides an architectural framework and a comprehensive examination of how the combination of threshold key management, privacy-enhancing technologies (e.g., homomorphic encryption, secure multi-party computation), and decentralised ledger technologies (DLT) enhances the security and privacy of vehicle ad-hoc networks (VANETs). We also examine the challenges of existing VANET structures, with a particular focus on trust, privacy, and scalability concerns. Our proposed architecture shifts from centralised to decentralised systems, highlighting the advantages of a decentralized ledger framework, specifically in ensuring the robustness, strong availability, integrity, and resilience of data against various cyber security threats. The architecture uses Layer 2s instead of Layer 1s as Layer 2s is much cheaper and faster. Furthermore, we explore how the aforementioned advanced cryptographic mechanisms are utilized in VANETs for improving key management, the distribution of trust, and data privacy, together with privacy-preserving data analysis, aiming to achieve resilient vehicle-to-everything (V2X) communication and privacy-preserving data analysis. We conclude by highlighting potential future directions for more secure, efficient, and resilient VANET systems in the era of 5G and beyond.

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Security Challenges of Selective Forwarding Attack and Design a Secure ECDH-Based Authentication Protocol to Improve RPL Security

Cited by 6 publications

References 65 publications

Enhancing IoT Security through a Green and Sustainable Federated Learning Platform: Leveraging Efficient Encryption and the Quondam Signature Algorithm

Enhancing IoT Security through a Green and Sustainable Federated Learning Platform: Leveraging Efficient Encryption and the Quondam Signature Algorithm

Investigating the performance vulnerability of AODV protocol of IoT network under SYN-flood attack

A New Framework for Enhancing VANETs through Layer 2 DLT Architectures with Multi-Party Threshold Key Management and PETs

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