Zobrazeno 1 - 10
of 285
pro vyhledávání: '"Hafid, Abdelhakim"'
User profiling is a critical component of adaptive risk-based authentication, yet it raises significant privacy concerns, particularly when handling sensitive data. Profiling involves collecting and aggregating various user features, potentially crea
Externí odkaz:
http://arxiv.org/abs/2410.20555
Maximal Extractable Value (MEV) represents a pivotal challenge within the Ethereum ecosystem; it impacts the fairness, security, and efficiency of both Layer 1 (L1) and Layer 2 (L2) networks. MEV arises when miners or validators manipulate transactio
Externí odkaz:
http://arxiv.org/abs/2407.19572
Autor:
Ebrahim, Maad, Hafid, Abdelhakim
Real-time Internet of Things (IoT) applications require real-time support to handle the ever-growing demand for computing resources to process IoT workloads. Fog Computing provides high availability of such resources in a distributed manner. However,
Externí odkaz:
http://arxiv.org/abs/2405.12236
The full realization of smart city technology is dependent on the secure and honest collaboration between IoT applications and edge-computing. In particular, resource constrained IoT devices may rely on fog-computing to alleviate the computing load o
Externí odkaz:
http://arxiv.org/abs/2405.00844
Autor:
Shahsavari, Yahya, Dambri, Oussama A., Baseri, Yaser, Hafid, Abdelhakim Senhaji, Makrakis, Dimitrios
Wearable devices and medical sensors revolutionize health monitoring, raising concerns about data privacy in ML for healthcare. This tutorial explores FL and BC integration, offering a secure and privacy-preserving approach to healthcare analytics. F
Externí odkaz:
http://arxiv.org/abs/2404.10092
Publikováno v:
Computers & Security, Volume 142, July 2024, 103883
The emergence of quantum computing poses a formidable security challenge to network protocols traditionally safeguarded by classical cryptographic algorithms. This paper provides an exhaustive analysis of vulnerabilities introduced by quantum computi
Externí odkaz:
http://arxiv.org/abs/2404.08232
Ethereum smart contracts are highly powerful, immutable, and able to retain massive amounts of tokens. However, smart contracts keep attracting attackers to benefit from smart contract flaws and Ethereum unexpected behavior. Thus, methodologies and t
Externí odkaz:
http://arxiv.org/abs/2403.19805
Fog computing emerged as a promising paradigm to address the challenges of processing and managing data generated by the Internet of Things (IoT). Load balancing (LB) plays a crucial role in Fog computing environments to optimize the overall system p
Externí odkaz:
http://arxiv.org/abs/2310.05187
Autor:
Ebrahim, Maad, Hafid, Abdelhakim
In this paper, we propose a load balancing algorithm based on Reinforcement Learning (RL) to optimize the performance of Fog Computing for real-time IoT applications. The algorithm aims to minimize the waiting delay of IoT workloads in dynamic enviro
Externí odkaz:
http://arxiv.org/abs/2301.09497
Autor:
Ebrahim, Maad, Hafid, Abdelhakim
The advent of Cloud Computing enabled the proliferation of IoT applications for smart environments. However, the distance of these resources makes them unsuitable for delay-sensitive applications. Hence, Fog Computing has emerged to provide such capa
Externí odkaz:
http://arxiv.org/abs/2210.13385