Fully Homomorphic Encryption Using Hidden Ideal Lattice

Plantard, Thomas; Susilo, Willy; Zhang, Zhenfei

doi:10.1109/tifs.2013.2287732

Cited by 40 publications

(22 citation statements)

References 17 publications

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“…26 Recently, Qin et al 27 proposed a scheme which can integrate the two functions of data hiding and image compression into a single module seamlessly. Future work aims at designing a more efficient data hiding scheme in the encrypted domain by exploiting the fully homomorphic property of the cryptosystem.…”

Section: Discussionmentioning

confidence: 99%

Context adaptive binary arithmetic coding-based data hiding in partially encrypted H.264/AVC videos

Wang

2015

J. Electron. Imaging

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A scheme of data hiding directly in a partially encrypted version of H.264/AVC videos is proposed which includes three parts, i.e., selective encryption, data embedding and data extraction. Selective encryption is performed on context adaptive binary arithmetic coding (CABAC) bin-strings via stream ciphers. By careful selection of CABAC entropy coder syntax elements for selective encryption, the encrypted bitstream is format-compliant and has exactly the same bit rate. Then a data-hider embeds the additional data into partially encrypted H.264/AVC videos using a CABAC bin-string substitution technique without accessing the plaintext of the video content. Since bin-string substitution is carried out on those residual coefficients with approximately the same magnitude, the quality of the decrypted video is satisfactory. Video file size is strictly preserved even after data embedding. In order to adapt to different application scenarios, data extraction can be done either in the encrypted domain or in the decrypted domain. Experimental results have demonstrated the feasibility and efficiency of the proposed scheme. Xu and Wang: Context adaptive binary arithmetic coding-based data hiding in partially encrypted H.264/AVC videos Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 07/01/2015 Terms of Use: http://spiedl.org/terms Fig. 2 Diagram of data extraction in encrypted or decrypted domain. Xu and Wang: Context adaptive binary arithmetic coding-based data hiding in partially encrypted H.264/AVC videos Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 07/01/2015 Terms of Use: http://spiedl.org/terms Journal of Electronic Imaging 033028-7 May∕Jun 2015 • Vol. 24(3) Xu and Wang: Context adaptive binary arithmetic coding-based data hiding in partially encrypted H.264/AVC videos Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 07/01/2015 Terms of Use: http://spiedl.org/terms Journal of Electronic Imaging 033028-8 May∕Jun 2015 • Vol. 24(3) Xu and Wang: Context adaptive binary arithmetic coding-based data hiding in partially encrypted H.264/AVC videos Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 07/01/2015 Terms of Use: http://spiedl.org/terms Journal of Electronic Imaging 033028-9 May∕Jun 2015 • Vol. 24(3) Xu and Wang: Context adaptive binary arithmetic coding-based data hiding in partially encrypted H.264/AVC videos Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 07/01/2015 Terms of Use: http://spiedl.org/terms Journal of Electronic Imaging 033028-12 May∕Jun 2015 • Vol. 24(3) Xu and Wang: Context adaptive binary arithmetic coding-based data hiding in partially encrypted H.264/AVC videos Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 07/01/2015 Terms of Use: http://spiedl.org/terms Journal of Electronic Imaging 033028-13 May∕Jun 2015 • Vol. 24(3) Xu and Wang: Context adaptive binary arithmetic coding-based data hiding in partially encrypted H.264/AVC videos Downloaded From: http://electronicimaging.sp...

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Section: Discussionmentioning

confidence: 99%

Context adaptive binary arithmetic coding-based data hiding in partially encrypted H.264/AVC videos

Wang

2015

J. Electron. Imaging

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“…Aono et al [41] proposed a system that utilizes homomorphic encryption technology to protect data privacy and avoid leaking local data information to curious servers. Homomorphic encryption technology still has certain limitations, for example, it does not support noninteger data [42]. The chaotic model is highly nonlinear and extremely sensitive to initial values [43].…”

Section: Related Workmentioning

confidence: 99%

Novel Defense Schemes for Artificial Intelligence Deployed in Edge Computing Environment

Zhou

Liu

Zeng

2020

Wireless Communications and Mobile Computing

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The last few years have seen the great potential of artificial intelligence (AI) technology to efficiently and effectively deal with an incredible deluge of data generated by the Internet of Things (IoT) devices. If all the massive data is transferred to the cloud for intelligent processing, it not only brings considerable challenges to the network bandwidth but also cannot meet the needs of AI applications that require fast and real-time response. Therefore, to achieve this requirement, mobile or multiaccess edge computing (MEC) is receiving a substantial amount of interest, and its importance is gradually becoming more prominent. However, with the emerging of edge intelligence, AI also suffers from several tremendous security threats in AI model training, AI model inference, and private data. This paper provides three novel defense strategies to tackle malicious attacks in three aspects. First of all, we introduce a cloud-edge collaborative antiattack scheme to realize a reliable incremental updating of AI by ensuring the data security generated in the training phase. Furthermore, we propose an edge-enhanced defense strategy based on adaptive traceability and punishment mechanism to effectively and radically solve the security problem in the inference stage of the AI model. Finally, we establish a system model based on chaotic encryption with the three-layer architecture of MEC to effectively guarantee the security and privacy of the data during the construction of AI models. The experimental results of these three countermeasures verify the correctness of the conclusion and the feasibility of the methods.

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“…The present scheme is compared with the literatures ( [5], [11] and [12]) on various parameters and it is tabulated below: scheme. It is simple, noise free, IND-CPA secure, needs no bootstrapping with a message space Z N and the plain text integer is encoded into a matrix M 4 (Z N ) using CRT.…”

Section: Comparison With Other Schemesmentioning

confidence: 99%

Privacy Preserving Outsourced Calculations With Symmetric Fully Homomorphic Encryption

Umadevi,

Gopalan

2019

IJITEE

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Cloud computing is a new paradigm which provides cloud storage service to manage, maintain and back up private data remotely. For privacy concerns the data is kept encrypted and made available to users on demand through cloud service provider over the internet. The legacy encryption techniques rely on sharing of keys, so service providers and end users of the cloud have exclusive rights on the data thus the secrecy may loss. Homomorphic Encryption is a significant encryption technique which allows users to perform limited arithmetic on the enciphered data without loss of privacy and security. This paper addresses a new simple and non-bootstrappable Fully Homomorphic Encryption Scheme based on matrices as symmetric keys with access control.

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Fully Homomorphic Encryption Using Hidden Ideal Lattice

Cited by 40 publications

References 17 publications

Context adaptive binary arithmetic coding-based data hiding in partially encrypted H.264/AVC videos

Context adaptive binary arithmetic coding-based data hiding in partially encrypted H.264/AVC videos

Novel Defense Schemes for Artificial Intelligence Deployed in Edge Computing Environment

Privacy Preserving Outsourced Calculations With Symmetric Fully Homomorphic Encryption

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