Towards Secure Instance Migration in the Cloud

Syed, Toqeer Ali; Musa, Shahrulniza; Rahman, Abdur; Jan, Salman

doi:10.1109/cloudcomp.2015.7149664

Cited by 6 publications

(2 citation statements)

References 19 publications

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“…The following section elaborates on the implementation details of the proposed solution. Initially, the testbed environment set up on the Amazon cloud is presented [79]. After network design and configuration, the SCs are developed for all the entities described in section III.…”

Section: B Testbed Setupmentioning

confidence: 99%

A Novel Blockchain-Based Framework for Vehicle Life Cycle Tracking: An End-to-End Solution

et al. 2020

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Transactions related to vehicles include manufacturing, buying, selling, paying insurance(takaful), obtaining regular inspection, leasing a vehicle from banks, getting in an accident, engaging in a traffic violation, calculating price predictions and renting a vehicle. Many people perform transactions related to vehicles in their daily life; transportation authorities also perform vehicle transactions as part of managing vehicle fleets. But tracking these transactions is a challenging task. There are countrywide solutions that uses centralized systems. However, these solutions have problems with trust management, transparency, and access control. Therefore, we believe there is still room for integrated automation of various vehicle-related transactions. In this paper, we present a blockchainbased framework for vehicle tracking that incorporates the mentioned features. Moreover, blockchain is customized to enable usage control for additional transactions, such as inspection, renting and islamic insurance. The usage control model is integrated with IoT devices to continuously monitor the vehicles for certain conditions and remotely revoke access if needed [1]. The complete transaction set is recorded over an immutable ledger that provides trust, transparency and a complete history of record. In this paper, we also presents a prototype implementation of a permissioned blockchain, which will be made available under the GNUv3 General Public License. Performance analysis is performed on the newly proposed framework implementation over the permissioned blockchain to measure its adoption and suitability. INDEX TERMS Blockchain, decentralized applications, smart contracts, vehicle life cycle tracking VOLUME 4, 2016 This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.

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Section: B Testbed Setupmentioning

confidence: 99%

A Novel Blockchain-Based Framework for Vehicle Life Cycle Tracking: An End-to-End Solution

et al. 2020

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“…Hierarchical clustering algorithm constructs a hierarchy among sensitive attributes values in order to split them into two or more clusters either on the basis of closeness or using a reversible process to merge clusters attributes values [23]. The outcome of the hierarchical can be represented by dendrogram [24,25,26]. For N sensitive attributes to be clustered, the basic process of NxN distance similarity matrix of hierarchical clustering is as below:…”

Section: B Clusteringmentioning

confidence: 99%

Clustering based Privacy Preserving of Big Data using Fuzzification and Anonymization Operation

Khan¹,

Iqbal²,

Faizullah³

et al. 2019

IJACSA

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Big Data is used by data miner for analysis purpose which may contain sensitive information. During the procedures it raises certain privacy challenges for researchers. The existing privacy preserving methods use different algorithms that results into limitation of data reconstruction while securing the sensitive data. This paper presents a clustering based privacy preservation probabilistic model of big data to secure sensitive information..model to attain minimum perturbation and maximum privacy. In our model, sensitive information is secured after identifying the sensitive data from data clusters to modify or generalize it.The resulting dataset is analysed to calculate the accuracy level of our model in terms of hidden data, lossed data as result of reconstruction. Extensive experiements are carried out in order to demonstrate the results of our proposed model. Clustering based Privacy preservation of individual data in big data with minimum perturbation and successful reconstruction highlights the significance of our model in addition to the use of standard performance evaluation measures.

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Recent trends in applying TPM to cloud computing

Hosseinzadeh

Sequeiros

Inácio

et al. 2019

Security and Privacy

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Trusted platform modules (TPM) have become important safe‐guards against variety of software‐based attacks. By providing a limited set of cryptographic services through a well‐defined interface, separated from the software itself, TPM can serve as a root of trust and as a building block for higher‐level security measures. This article surveys the literature for applications of TPM in the cloud‐computing environment, with publication dates comprised between 2013 and 2018. It identifies the current trends and objectives of this technology in the cloud, and the type of threats that it mitigates. Toward the end, the main research gaps are pinpointed and discussed. Since integrity measurement is one of the main usages of TPM, special attention is paid to the assessment of run time phases and software layers it is applied to.

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Towards Secure Instance Migration in the Cloud

Cited by 6 publications

References 19 publications

A Novel Blockchain-Based Framework for Vehicle Life Cycle Tracking: An End-to-End Solution

A Novel Blockchain-Based Framework for Vehicle Life Cycle Tracking: An End-to-End Solution

Clustering based Privacy Preserving of Big Data using Fuzzification and Anonymization Operation

Recent trends in applying TPM to cloud computing

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