Survey on securing data storage in the cloud

Huang, Chun-Ta; Huang, Lei; Qin, Zhongyuan; Yuan, Hang; Zhou, Lan; Varadharajan, Vijay; Kuo, C.-C. Jay

doi:10.1017/atsip.2014.6

Cited by 78 publications

(29 citation statements)

References 98 publications

(123 reference statements)

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“…In recent years, cloud computing and edge computing that use resourses of providers are rapidly spreading in many fields. However, there are some security concerns such as unauthorized use and leak of data, and privacy compromise [1]. For solving these privacy concerns for end-users, many researches has been conducted [2]- [5].…”

Section: Introductionmentioning

confidence: 99%

HOG feature extraction from encrypted images for privacy-preserving machine learning

Kitayama

Kiya

2019

2019 IEEE International Conference on Consumer Electronics - Asia (ICCE-Asia)

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In this paper, we propose an extraction method of HOG (histograms-of-oriented-gradients) features from encryption-then-compression (EtC) images for privacypreserving machine learning, where EtC images are images encrypted by a block-based encryption method proposed for EtC systems with JPEG compression, and HOG is a feature descriptor used in computer vision for the purpose of object detection and image classification. Recently, cloud computing and machine learning have been spreading in many fields. However, the cloud computing has serious privacy issues for end users, due to unreliability of providers and some accidents. Accordingly, we propose a novel block-based extraction method of HOG features, and the proposed method enables us to carry out any machine learning algorithms without any influence, under some conditions. In an experiment, the proposed method is applied to a face image recognition problem under the use of two kinds of classifiers: linear support vector machine (SVM), gaussian SVM, to demonstrate the effectiveness.Index Terms-encryption-then-compression block-based encryption, histgram of oriented gradients

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Section: Introductionmentioning

confidence: 99%

HOG feature extraction from encrypted images for privacy-preserving machine learning

Kitayama

Kiya

2019

2019 IEEE International Conference on Consumer Electronics - Asia (ICCE-Asia)

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“…A lot of studies on secure, efficient and flexible communications have been reported [1]- [3]. For securing multimedia data, full encryption with provable security (like RSA, AES, etc) is the most secure option.…”

Section: Introductionmentioning

confidence: 99%

On the Security of Block Scrambling-Based EtC Systems against Extended Jigsaw Puzzle Solver Attacks

Chuman

Kurihara

Kiya

2018

IEICE Trans. Inf. & Syst.

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SUMMARYThe aim of this paper is to apply automatic jigsaw puzzle solvers, which are methods of assembling jigsaw puzzles, to the field of information security. Encryption-then-Compression (EtC) systems have been considered for the user-controllable privacy protection of digital images in social network services. Block scrambling-based encryption schemes, which have been proposed to construct EtC systems, have enough key spaces for protecting brute-force attacks. However, each block in encrypted images has almost the same correlation as that of original images. Therefore, it is required to consider the security from different viewpoints from number theory-based encryption methods with provable security such as RSA and AES. In this paper, existing jigsaw puzzle solvers, which aim to assemble puzzles including only scrambled and rotated pieces, are first reviewed in terms of attacking strategies on encrypted images. Then, an extended jigsaw puzzle solver for block scrambling-based encryption scheme is proposed to solve encrypted images including inverted, negative-positive transformed and color component shuffled blocks in addition to scrambled and rotated ones. In the experiments, the jigsaw puzzle solvers are applied to encrypted images to consider the security conditions of the encryption schemes.

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“…With the wide/rapid spread of distributed systems for information processing, such as cloud computing and social networks, not only transmission but also processing is done on the public Internet, and thus contents are transmitted over an insecure bandwidth-constrained communication channel [1], [2]. In the meantime, a lot of studies on secure, efficient and flexible communications have been reported.…”

Section: Introductionmentioning

confidence: 99%

An Encryption-then-Compression System for Lossless Image Compression Standards

Kurihara

Imaizumi

Shiota

et al. 2017

IEICE Trans. Inf. & Syst.

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SUMMARYIn many multimedia applications, image encryption has to be conducted prior to image compression. This letter proposes an Encryption-then-Compression system using JPEG XR/JPEG-LS friendly perceptual encryption method, which enables to be conducted prior to the JPEG XR/JPEG-LS standard used as an international standard lossless compression method. The proposed encryption scheme can provides approximately the same compression performance as that of the lossless compression without any encryption. It is also shown that the proposed system consists of four block-based encryption steps, and provides a reasonably high level of security. Existing conventional encryption methods have not been designed for international lossless compression standards, but for the first time this letter focuses on applying the standards.

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Survey on securing data storage in the cloud

Cited by 78 publications

References 98 publications

HOG feature extraction from encrypted images for privacy-preserving machine learning

HOG feature extraction from encrypted images for privacy-preserving machine learning

On the Security of Block Scrambling-Based EtC Systems against Extended Jigsaw Puzzle Solver Attacks

An Encryption-then-Compression System for Lossless Image Compression Standards

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