Fidr

Ajdari, Mohammadamin; Lee, Wonsik; Park, Pyeongsu; Kim, Joonsung; Kim, Jangwoo

doi:10.1145/3352460.3358303

Cited by 8 publications

(2 citation statements)

References 19 publications

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“…Yang et al [13] investigated on the sensor-cloud communication efficiency using data compression and classification. Ajdari et al [14] studied the importance of privacy to image data when it is collected and transferred over public networks. Especially, their study focused on IoT use cases where the need for privacy protection is established.…”

Section: Related Workmentioning

confidence: 99%

“…Cloud-assisted system is built for CS based data gathering [12] while secure video deduplication with CS is explored by Yang et al [13]. Privacy preserving approach is coupled with CS for outsourcing identity authentication and image storage [14]. CS is employed to have image damage monitoring when it is combined with data fusion approach [15].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Framework for Leveraging Image Security in Cloud with Simultaneous Compression and Encryption Using Compressive Sensing

Manikyam¹,

Devi²

2021

RIA

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In the contemporary era, technological innovations like cloud computing and Internet of Things (IoT) pave way for diversified applications producing multimedia content. Especially large volumes of image data, in medical and other domains, are produced. Cloud infrastructure is widely used to reap benefits such as scalability and availability. However, security and privacy of imagery is in jeopardy when outsourced it to cloud directly. Many compression and encryption techniques came into existence to improve performance and security. Nevertheless, in the wake of emergence of quantum computing in future, there is need for more secure means with multiple transformations of data. Compressive sensing (CS) used in existing methods to improve security. However, most of the schemes suffer from the problem of inability to perform compression and encryption simultaneously besides ending up with large key size. In this paper, we proposed a framework known as Cloud Image Security Framework (CISF) leveraging outsourced image security. The framework has an underlying algorithm known as Hybrid Image Security Algorithm (HISA). It is based on compressive sensing, simultaneous sensing and encryption besides random pixel exchange to ensure multiple transformations of input image. The empirical study revealed that the CISF is more effective, secure with acceptable compression performance over the state of the art methods.

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Section: Related Workmentioning

confidence: 99%