Smart Privacy Protection for Big Video Data Storage Based on Hierarchical Edge Computing

Xiao, Di; Li, Min; Zheng, Haibin

doi:10.3390/s20051517

Cited by 5 publications

(3 citation statements)

References 33 publications

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“…The average communication overheads for PPMDS, EPA, and SPPDA are ⩽ 2000bits, ⩽ 3900bits, and ⩽ 4600 bits, respectively. Nowadays, multi-edge computations can handle up to 8 GB of data storage and computation [39].…”

Section: E Complexity Analysismentioning

confidence: 99%

C-NEST: Cloudlet-Based Privacy Preserving Multidimensional Data Stream Approach for Healthcare Electronics

Srivastava,

Mekala,

Hajar

et al. 2024

IEEE Trans. Consumer Electron.

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The Medical Internet of Things (MIoT) facilitates extensive connections between cyber and physical "things" allowing for effective data fusion and remote patient diagnosis and monitoring. However, there is a risk of incorrect diagnosis when data is tampered with from the cloud or a hospital due to third-party storage services. Most of the existing systems use an owner-centric data integrity verification mechanism, which is not computationally feasible for lightweight wearable-sensor systems because of limited computing capacity and privacy leakage issues. In this regard, we design a 2-step Privacy-Preserving Multidimensional Data Stream (PPMDS) approach based on a cloudlet framework with an Uncertain Data-integrity Optimization (UDO) model and Sparse-Centric SVM (SCS) model. The UDO model enhances health data security with an adaptive cryptosystem called Cloudlet-Nonsquare Encryption Secret Transmission (C-NEST) strategy by avoiding medical disputes during data streaming based on novel signature and key generation strategies. The SCS model effectively classifies incoming queries for easy access to data by solving scalability issues. The cloudlet server measures data integrity and authentication factors to optimize third-party verification burden and computational cost. The simulation outcomes show that the proposed system optimizes average data leakage error rate by 27%, query response time and average data transmission time are reduced by 31%, and average communication-computation cost are reduced by 61% when measured against state-of-the-art approaches.

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Section: E Complexity Analysismentioning

confidence: 99%

C-NEST: Cloudlet-Based Privacy Preserving Multidimensional Data Stream Approach for Healthcare Electronics

Srivastava,

Mekala,

Hajar

et al. 2024

IEEE Trans. Consumer Electron.

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show abstract

“…Users are authenticated and authorised by correlating information sources such as data points, user identity, service or workload, location, data classification, device health, and anomalies. Password-based user authentication has been proven to be ineffective and inefficient without enhancements like two-factor authentication requiring human intervention [47]. With the modernisation of user authentication, enabling Single Sign-On (SSO) capability may elevate access control and improve user experience.…”

Section: Securing the Trust Pillarsmentioning

confidence: 99%

A Maturity Framework for Zero-Trust Security in Multiaccess Edge Computing

Ali

Hijjawi

Campbell

et al. 2022

Security and Communication Networks

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Multiaccess Edge Computing (MEC) has been adopted to provide an environment that supports cloud computing capabilities and IT services at the network edge. The open architecture of cloud computing and network access at the edge provides malicious actors with many attack vectors. The MEC system entities cannot be permanently trusted due to the dynamic and shareable nature of MEC deployments. This paper presents a classification of MEC entities that can be used to define security controls based on the Zero-Trust Security approach. The security controls are organised into a maturity framework that can be used to guide the systematic development of trust and security in an MEC environment. In this framework, a Minimum Viable Security posture defines the first operational step towards full implementation of Zero-Trust Security in an MEC environment.

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“…The amount of data that each user has varied from GBs to TBs, and the local storage cannot keep up with this enormous demand on its own. Because of this, adopting a low-complexity, high-security cloud storage service is now a must in today's world [2]. In any case, the primary concern raised by these data is security, as they are stored in the fog.…”

Section: Introductionmentioning

confidence: 99%

Chaotic-Map Based Encryption for 3D Point and 3D Mesh Fog Data in Edge Computing

et al. 2023

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Recent decades have seen dramatic development and adoption of digital technology. This technological advancement generates a large amount of critical data that must be safeguarded. The security of confidential data is one of the primary concerns in fog computing. As a result, achieving a reliable level of security in the fog computing environment is crucial. In this context, 3D point and mesh fog data are becoming increasingly popular among the various types of data stored in the fog. Data encryption using chaotic behavior is one of the preferred research areas due to its unique properties, such as randomness, determinism, sensitivity to initial conditions, and ergodicity. In this paper, we have taken advantage of this chaotic behavior to achieve higher security. This study presents a novel approach for protecting the privacy of 3D point and mesh fog data. Initially, the fog data coordinates are transformed using the sequence generated by the chaotic behavior. Then, bifurcation analysis is used to depict the enhanced scope of the proposed map. The quality of the proposed chaotic system is assessed using metrics such as the Lyapunov exponent and approximate entropy. Results show that the proposed encryption framework performs superior when subjected to brute-force and statistical attacks. Further, the designed framework produces better results than the prior literature.

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Smart Privacy Protection for Big Video Data Storage Based on Hierarchical Edge Computing

Cited by 5 publications

References 33 publications

C-NEST: Cloudlet-Based Privacy Preserving Multidimensional Data Stream Approach for Healthcare Electronics

C-NEST: Cloudlet-Based Privacy Preserving Multidimensional Data Stream Approach for Healthcare Electronics

A Maturity Framework for Zero-Trust Security in Multiaccess Edge Computing

Chaotic-Map Based Encryption for 3D Point and 3D Mesh Fog Data in Edge Computing

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