A context-aware encryption protocol suite for edge computing-based IoT devices

Dar, Zaineb; Awada, Ahmad; Khan, Farrukh Aslam; Zeshan, Furkh; Sherazi, Hafiz Husnain Raza

doi:10.1007/s11227-019-03021-2

Cited by 17 publications

(17 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This proposed method improves the utilization of links and also incorporate more GTS nodes. In [23], the authors propose an encryption protocol based on context awareness for IoT network which selects the best encryption protocol based on data confidentiality and device specifications. This method saved memory consumption by 79%, battery consumption by 56% and reduced execution time by 68%.…”

Section: Literature Surveymentioning

confidence: 99%

A metaheuristic optimization approach for energy efficiency in the IoT networks

et al. 2020

Self Cite

View full text Add to dashboard Cite

Recently Internet of Things (IoT) is being used in several fields like smart city, agriculture, weather forecasting, smart grids, waste management, etc. Even though IoT has huge potential in several applications, there are some areas for improvement. In the current work, we have concentrated on minimizing the energy consumption of sensors in the IoT network that will lead to an increase in the network lifetime. In this work, to optimize the energy consumption, most appropriate Cluster Head (CH) is chosen in the IoT network. The proposed work makes use of a hybrid meta-heuristic algorithm, namely, Whale Optimization Algorithm (WOA) with Simulated Annealing (SA). To select the optimal CH in the clusters of IoT network, several performance metrics such as the number of alive nodes, load, temperature, residual energy, cost function has been used. The proposed approach is then compared with several state-of-the-art optimization algorithms like Artificial Bee Colony (ABC) algorithm, Genetic Algorithm (GA), Adaptive Gravitational Search algorithm (AGSA), Whale Optimization Algorithm (WOA). The results prove the superiority of the proposed hybrid approach over existing approaches.

show abstract

Section: Literature Surveymentioning

confidence: 99%

A metaheuristic optimization approach for energy efficiency in the IoT networks

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…Confidentiality is a significant hindrance for mobile users that wish to utilise mobile apps and services. The MEC paradigm introduces limitations affecting data confidentiality [21], [65], [66]. As the data is transmitted and received within shared and sometimes public networks and stored or processed in distributed and shared edge networks, the likelihood of unauthorised access to sensitive data by service providers is relatively high [12], [23], [34], [35].…”

Section: ) Data Confidentialitymentioning

confidence: 99%

“…The ITU-T defines privacy [17] as the right of individuals to control what information related to them may be collected, analysed and stored and by whom and to whom that information may be revealed. By extension, privacy is also associated with specific technical means such as cryptography [61], [66]. Privacy mechanism will ensure information is not disclosed to any party other than the intended parties so that only the explicitly authorised parties can interpret the content being exchanged.…”

Section: Security Threat Challengesmentioning

confidence: 99%

Multi-Access Edge Computing Architecture, Data Security and Privacy: A Review

Ali

Gregory

2021

IEEE Access

View full text Add to dashboard Cite

Multi-Access Edge Computing (MEC) is an extension of cloud computing that aims to provide computation, storage, and networking capabilities at the edge of the network in close proximity to end-users. The MEC architecture supports applications and services that bridge between cloud computing and end-users. The architecture includes devices and systems that are interconnected, layered, and flexibly deployed. As a result of the technological advancements, MEC is facing a myriad of highly sophisticated threats. This paper provides a review of MEC Architecture, use cases, conceptual guidelines for MEC security architecture, security and privacy techniques, and identifies current and future challenges, their implications, and approaches to overcome the challenges. This research examined significant threats, described the MEC architecture, identified the susceptible functional layers, the different categories of threats, and the potential security safeguards. The research recommends that MEC providers should implement multiple layers of security controls to mitigate targeted attacks.

show abstract

“…For example, Zhao et al [20] proposed an efficient scheduling scheme for cloud resources to satisfy the QoS for Analytics as a Service (AaaS) alongside minimizing the energy consumption of DCs. A context-aware approach was proposed by Dar et al [21] to categorize the data and device according to their confidentiality level to minimize the energy consumption at different levels. Alqahtani et al [22] proposed a greedy heuristic approach to assign the computing resources at the edge level in order to process the tasks with minimal energy consumption.…”

Section: Related Workmentioning

confidence: 99%