A Comprehensive Survey on the Cooperation of Fog Computing Paradigm-Based IoT Applications: Layered Architecture, Real-Time Security Issues, and Solutions

Burhan, Muhammad; Alam, Hina; Arsalan, Ahmad; Rehman, Rana Asif; Anwar, Muhammad; Faheem, Muhammad; Ashraf, Muhammad Waqar

doi:10.1109/access.2023.3294479

Cited by 29 publications

(8 citation statements)

References 198 publications

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“…The unique characteristics of IoT elements, including resource limitations, extensive scope, diversity, prioritization of functionality above security, increased privacy needs, cost-effective design, and complex trust administration, pose challenges for traditional IDS systems. Burhan et al argue that network construction, flexibility, multiple devices, interaction, cooperation with the real world, limited resources, confidentiality, broad scale, trust administration, and insufficient security preparation necessitate the creation of IDS for the IoT [9].…”

Section: Background and Analysismentioning

confidence: 99%

Implementation of a multi-stage intrusion detection systems framework for strengthening security on the internet of things

Rani,

Parasa,

Hemanand

et al. 2024

MATEC Web Conf.

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The Internet of Things (IoT) expansion has introduced a new era of interconnectedness and creativity inside households. Various independent gadgets are now controlled from a distance, enhancing efficiency and organization. This results in increased security risks. Competing vendors rapidly develop and release novel connected devices, often paying attention to security concerns. As a result, there is a growing number of assaults against smart gadgets, posing risks to users' privacy and physical safety. The many technologies used in IoT complicate efforts to provide security measures for smart devices. Most intrusion detection methods created for such platforms rely on monitoring network activities. On multiple platforms, intrusions are challenging to detect accurately and consistently via network traces. This research provides a Multi-Stage Intrusion Detection System (MS-IDS) for intrusion detection that operates on the host level. The study employs personal space and kernel space data and Machine Learning (ML) methods to identify different types of intrusions in electronic devices. The proposed MS-IDS utilizes tracing methods that automatically record device activity, convert this data into numerical arrays to train multiple ML methods, and trigger warnings upon detecting an incursion. The research used several ML methods to enhance the ability to see with little impact on the monitoring devices. The study evaluated the MS-IDS approach in a practical home automation system under genuine security risks.

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Section: Background and Analysismentioning

confidence: 99%

Implementation of a multi-stage intrusion detection systems framework for strengthening security on the internet of things

Rani,

Parasa,

Hemanand

et al. 2024

MATEC Web Conf.

View full text Add to dashboard Cite

show abstract

“…The authors of [32] have identified the conventional real-time security concerns that end-users face in an IoT network. They have proposed a layered architecture within the fog computing paradigm to address these issues.…”

Section: Related Workmentioning

confidence: 99%

Secure Computing for Fog-Enabled Industrial IoT

Alvi,

Ali,

Saleh

et al. 2024

Sensors

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Smart cities are powered by several new technologies to enhance connectivity between devices and develop a network of connected objects which can lead to many smart industrial applications. This network known as the Industrial Internet of Things (IIoT) consists of sensor nodes that have limited computing capacity and are sometimes not able to execute intricate industrial tasks within their stipulated time frame. For faster execution, these tasks are offloaded to nearby fog nodes. Internet access and the diverse nature of network types make IIoT nodes vulnerable and are under serious malicious attacks. Malicious attacks can cause anomalies in the IIoT network by overloading complex tasks, which can compromise the fog processing capabilities. This results in an increased delay of task computation for trustworthy nodes. To improve the task execution capability of the fog computing node, it is important to avoid complex offloaded tasks due to malicious attacks. However, even after avoiding the malicious tasks, if the offloaded tasks are too complex for the fog node to execute, then the fog nodes may struggle to process all legitimate tasks within their stipulated time frame. To address these challenges, the Trust-based Efficient Execution of Offloaded IIoT Trusted tasks (EEOIT) is proposed for fog nodes. EEOIT proposes a mechanism to detect malicious nodes as well as manage the allocation of computing resources so that IIoT tasks can be completed in the specified time frame. Simulation results demonstrate that EEOIT outperforms other techniques in the literature in an IIoT setting with different task densities. Another significant feature of the proposed EEOIT technique is that it enhances the computation of trustable tasks in the network. The results show that EEOIT entertains more legitimate nodes in executing their offloaded tasks with more executed data, with reduced time and with increased mean trust values as compared to other schemes.

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“…The proposed system faces the challenge of scalability due to the increase in the number of terminals. [14] Cloud-edge-terminal collaborative.…”

Section: Ref Environmentmentioning

confidence: 99%

“…Furthermore, based on this system, a corresponding caching strategy was proposed to improve the cache hit rate [13]. M. Burhan et al examined the layered architecture of fog-based IoT networks alongside IoT applications operating within the context of the fog computing paradigm [14]. Faheem M et al proposed a blockchain-based smart contract framework in Solana blockchain for integrating and monitoring distributed energy resources (DERs) in the smart grid.…”

Section: Ref Environmentmentioning

confidence: 99%

Blockchain Based Decentralized and Proactive Caching Strategy in Mobile Edge Computing Environment

Bai,

Zhu,

2024

Sensors

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In the mobile edge computing (MEC) environment, the edge caching can provide the timely data response service for the intelligent scenarios. However, due to the limited storage capacity of edge nodes and the malicious node behavior, the question of how to select the cached contents and realize the decentralized security data caching faces challenges. In this paper, a blockchain-based decentralized and proactive caching strategy is proposed in an MEC environment to address this problem. The novelty is that the blockchain was adopted in an MEC environment with a proactive caching strategy based on node utility, and the corresponding optimization problem was built. The blockchain was adopted to build a secure and reliable service environment. The employed methodology is that the optimal caching strategy was achieved based on the linear relaxation technology and the interior point method. Additionally, in a content caching system, there is a trade-off between cache space and node utility, and the caching strategy was proposed to solve this problem. There was also a trade-off between the consensus process delay of blockchain and the caching latency of content. An offline consensus authentication method was adopted to reduce the influence of the consensus process delay on the content caching. The key finding was that the proposed algorithm can reduce latency and can ensure the security data caching in an IoT environment. Finally, the simulation experiment showed that the proposed algorithm can achieve up to 49.32%, 43.11%, and 34.85% improvements on the cache hit rate, the average content response latency, and the average system utility, respectively, compared to the random content caching algorithm, and it achieved up to 9.67%, 8.11%, and 5.95% increases, successively, compared to the greedy content caching algorithm.

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A Comprehensive Survey on the Cooperation of Fog Computing Paradigm-Based IoT Applications: Layered Architecture, Real-Time Security Issues, and Solutions

Cited by 29 publications

References 198 publications

Implementation of a multi-stage intrusion detection systems framework for strengthening security on the internet of things

Implementation of a multi-stage intrusion detection systems framework for strengthening security on the internet of things

Secure Computing for Fog-Enabled Industrial IoT

Blockchain Based Decentralized and Proactive Caching Strategy in Mobile Edge Computing Environment

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