FeSA: Automatic Federated Swarm Attestation on Dynamic Large-Scale IoT Devices

Kuang, Boyu; Fu, Anmin; Gao, Yansong; Zhang, Yuqing; Zhou, Jianying; Deng, Robert H.

doi:10.1109/tdsc.2022.3193106

Cited by 7 publications

(2 citation statements)

References 48 publications

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“…The literature proposes an eco-friendly and protected data center that uses a swarm technique to identify compromised devices. The system uses swarm authentication, as another type of attestation, to check the cybersecurity states of several devices in a vast network simultaneously [23,24]. The suggested approach tries to decrease duplication while also addressing issues such as verify the Denial of Service (DoS), and malware [25].…”

Section: Prior Studiesmentioning

confidence: 99%

Eco-friendly and Secure Data Center to Detection Compromised Devices Utilizing Swarm Approach

2024

IJIES

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Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the applying sigmoid fish swarm optimization (SiFSO) for early compromised device detection and subsequently alerting other network nodes. Additionally, our data center implements an innovative ant skyscape architecture (ASA) cooling mechanism, departing from traditional, unsustainable cooling strategies that harm the environment. To validate the effectiveness of these approaches, extensive simulations were conducted. The evaluations primarily revolved around the fish colony's ability to detect compromised devices, focusing on source tracing, realistic modelling, and an impressive 98% detection accuracy rate under ASA cooling solution with 0.16 ºC within 1,300 second. Compromised devices pose a substantial risk to green data centers, as attackers could manipulate and disrupt network equipment. Therefore, incorporating cyber enhancements into the green data center concept is imperative to foster more adaptable and efficient smart networks.

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Section: Prior Studiesmentioning

confidence: 99%

Eco-friendly and Secure Data Center to Detection Compromised Devices Utilizing Swarm Approach

2024

IJIES

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“…Te industrial control protocol is a collection of rules, standards, or conventions established for the exchange of data in the industrial control network, and it is an indispensable part of communication between entities of the Industrial Internet [1][2][3]. Terefore, industrial control protocols have become a common target for attackers to carry out network attacks.…”

Section: Introductionmentioning

confidence: 99%

IMCSA: Providing Better Sequence Alignment Space for Industrial Control Protocol Reverse Engineering

Huang

et al. 2022

Security and Communication Networks

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Nowadays, with the wide application of industrial control facilities, industrial control protocol reverse engineering has significant security implications. The reverse method of industrial protocol based on sequence alignment is the current mainstream method because of its high accuracy. However, this method will incur a huge time overhead due to unnecessary alignments during the sequence alignment process. In this paper, we optimize the traditional sequence alignment method by combining the characteristics of industrial control protocols. We improve the frequent sequence mining algorithm, Apriori, to propose a more efficient Bag-of-Words generation algorithm for finding keywords. Then, we precluster the messages based on the generated Bag-of-Words to improve the similarity of the message within a cluster. Finally, we propose an industrial control protocol message preclustering model for sequence alignment, namely, IMCSA. We evaluate it over five industrial control protocols, and the results show that IMCSA can generate clusters with higher message similarity, which will greatly reduce the invalid alignments existing in the sequence alignment stage and ultimately improve the overall efficiency.

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LICAPA: Lightweight collective attestation for physical attacks detection in highly dynamic networks

Wang,

Sun

2024

Pervasive and Mobile Computing

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FeSA: Automatic Federated Swarm Attestation on Dynamic Large-Scale IoT Devices

Cited by 7 publications

References 48 publications

Eco-friendly and Secure Data Center to Detection Compromised Devices Utilizing Swarm Approach

Eco-friendly and Secure Data Center to Detection Compromised Devices Utilizing Swarm Approach

IMCSA: Providing Better Sequence Alignment Space for Industrial Control Protocol Reverse Engineering

LICAPA: Lightweight collective attestation for physical attacks detection in highly dynamic networks

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