Efficient Auditing Scheme for Secure Data Storage in Fog-to-Cloud Computing

Zhang, Xingjun; Si, Wei

doi:10.1109/access.2020.2971630

Cited by 9 publications

(8 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To maintain the reputation of the cloud service, the fog nodes may send fraudulent auditing results to the data owners. Existing public auditing schemes 6,12,[18][19][20][21] do not allow the data owners to perform cross-verification on the public auditing results. To address this issue, the proposed auditing scheme has allowed the IoT device coordinator to verify the integrity of the healthcare data.…”

Section: Importance Of Cross-examining the Integrity Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Lightweight fog‐centric auditing scheme to verify integrity of IoT healthcare data in the cloud environment

Yoosuf

Anitha²

2021

Concurrency and Computation

View full text Add to dashboard Cite

IoT healthcare applications have become very popular among medical societies. At regular intervals, the healthcare IoT devices collect the patient's health information and transfer it to cloud storage. Storing the health records in the cloud environment increases the vulnerability. Integrity verification performed at regular intervals ensures the safety and security of the healthcare data stored in the cloud. Existing schemes use RSA and BLS signatures to verify the authenticity. However, the size of the signature is too large in RSA and BLS schemes. Using large signatures for proving the authenticity increases the computation overhead. IoT devices have minimal resource capacity, hence performing heavily weighted integrity schemes will create an unbearable workload. Likewise, private auditing increases the communication overhead between IoT devices and cloud storage. To overcome these issues, a fog-centric auditing scheme is proposed based on the Cramer-Shoup cryptosystem. The proposed scheme allows the fog nodes to perform integrity verification without compromising security. It reduces the communication overhead by 55%-60%. The size of the CS signature used in the scheme is far lesser than the existing signatures. Moreover, performing the inline deduplication on the fog layer improves the efficiency of cloud storage by 30%.

show abstract

Section: Importance Of Cross-examining the Integrity Resultsmentioning

confidence: 99%

“…To overcome the security issues in Tian et al, 19,20 Zhang et al 21 proposed a fog-centric public auditing scheme based on the Message Authentication Code (MAC) and HMAC (Keyed Hash Message Authentication Code). It uses homomorphic MAC-based tags to conduct public auditing on the fog nodes.…”

Section: Existing Fog-centric Auditing Schemesmentioning

confidence: 99%

Lightweight fog‐centric auditing scheme to verify integrity of IoT healthcare data in the cloud environment

Yoosuf

Anitha²

2021

Concurrency and Computation

View full text Add to dashboard Cite

show abstract

“…* Corresponding author. E-mail address: ku.cse09@gmail.com (2) Audit phase: During the time of the verification, the TPA sends a challenge message to the cloud server. After executing the GenProof algorithm, the cloud server will generate a response message from the stored data file.…”

Section: The Traditional Data Integrity Verification Technique Consis...mentioning

confidence: 99%

Partitioning-Based Data Sharing Approach for Data Integrity Verification in Distributed Fog Computing

Kaliyaperumal

Somasundaram

Nickolas

2023

Int. j. eng. technol. innov.

View full text Add to dashboard Cite

With the increasing popularity of the internet of things (IoT), fog computing has emerged as a unique cutting-edge approach along with cloud computing. This study proposes an approach for data integrity verification in fog computing that does not require metadata stored on the user side and can handle big data efficiently. In the proposed work, fuzzy clustering is used to cluster IoT data; dynamic keys are used to encrypt the clusters; and dynamic permutation is used to distribute encrypted clusters among fog nodes. During the process of data retrieval, fuzzy clustering and message authentication code (MAC) are used to verify the data integrity. Fuzzy clustering and dynamic primitives make the proposed approach more secure. The security analysis indicates that the proposed approach is resilient to various security attacks. Moreover, the performance analysis shows that the computation time of the proposed work is 50 times better than the existing tag regeneration scheme.

show abstract

“…Their system utilized the advantages of multicloud storage to ensure users' data protection and reliability. Zhang et al [10] designed an auditing system based on two private key cryptographic techniques, namely message authentication code (MAC) and homomorphic MAC, for secure data storage in fog-to-cloud computing. Krishnan et al [83] enhanced a clustering methodology with multiple mobile sinks for efficient data collection.…”

Section: E Data Utility Based Algorithmsmentioning

confidence: 99%

“…The serverless architecture is delegated to third-party providers in charge of dynamically provisioning and allocating resources. Another alternative execution model is the FC (or sometimes referred to as edge computing) [6]- [10]. The FC acts as a mediator between remote servers and hardware.…”

Section: Introductionmentioning

confidence: 99%

Energy Coherent Fog Networks Using Multi-Sink Wireless Sensor Networks

et al. 2021

View full text Add to dashboard Cite

Fog computing (FC) models the cloud computing paradigm expedient by bridging the breach between centralized data servers and diverse terrestrially distributed applications. It wields various wireless sensor networks (WSNs) that sprawl in the core of any IoT applications. Consequently, the operation of fog network turns on the efficiency of WSNs operation, while the all-inclusive network energy consumption depends on both FC and WSNs operation. This paper addresses how dissimilar organizations of a fog network can influence its effectiveness and energy savings. Chiefly, it appraises whether deploying multisink nodes in close enough vicinity to the fog nodes can give in energy savings and foster coherent data communication between WSNs and fog networks. To assess the multi-sink assignment problem the following four criteria are used: (i) Distance from the fog network nodes; (ii) Nodes degree; (iii) Sink nodes energy; and (iv) Sink nodes processing capabilities. This paper suggests four novel solutions to the multisink connectivity for some challenges of fog networks deeming: (i) Window Nondominant Set (WNS); (ii) Evaluation Based Approach (EBA); (iii) Harris Hawks Optimizer (HHO); and (iv) Modified HHO (MHHO). Distinct sets of experiments are conducted to check out algorithmic performance. The performance of all algorithms is measured and then compared to each other in terms of power consumption, runtime, packet loss, and localization error. One of the key supremacies of our approaches is the utilization of fog network for sensor networks data processing, principally with the large-scale networks. Yet, the communication challenges could need further study due to the limited communication range of the sensors.

show abstract

Efficient Auditing Scheme for Secure Data Storage in Fog-to-Cloud Computing

Cited by 9 publications

References 34 publications

Lightweight fog‐centric auditing scheme to verify integrity of IoT healthcare data in the cloud environment

Lightweight fog‐centric auditing scheme to verify integrity of IoT healthcare data in the cloud environment

Partitioning-Based Data Sharing Approach for Data Integrity Verification in Distributed Fog Computing

Energy Coherent Fog Networks Using Multi-Sink Wireless Sensor Networks

Contact Info

Product

Resources

About