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Analysis on Matrix GSW-FHE and Optimizing Bootstrapping

Xiufeng Zhao, Hefeng Mao, Shuai Liu, Weitao Song, Bo Zhang
2018 Security and Communication Networks  
computation and storage complexity of bootstrapping key generation, thus optimizing the bootstrapping procedure.  ...  We also give an extended version of matrix GSW-FHE by defining deterministic asymmetric encryption algorithm and propose hybrid homomorphic plaintext slot-wise switching method, which significantly reduces  ...  The comparison of storage complexity is illustrated in Table 2 .  ... 
doi:10.1155/2018/6362010 fatcat:sndfgc5csvdavfsmfnfhsgeuya

Logistic Regression on Homomorphic Encrypted Data at Scale

Kyoohyung Han, Seungwan Hong, Jung Hee Cheon, Daejun Park
2019 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Machine learning on (homomorphic) encrypted data is a cryptographic method for analyzing private and/or sensitive data while keeping privacy.  ...  While several studies have been reported on the prediction phase, few studies have been conducted on the training phase.In this paper, we present an efficient algorithm for logistic regression on homomorphic  ...  Then we explain our optimization of the baseline algorithm for efficient homomorphic evaluation (Sections 3.2).  ... 
doi:10.1609/aaai.v33i01.33019466 fatcat:lodh5a3h2nh4pd4ejaavx3a54u

Fully Homomorphic Encryption Based On the Parallel Computing

2018 KSII Transactions on Internet and Information Systems  
Fully homomorphic encryption(FHE) scheme may be the best method to solve the privacy leakage problem in the untrusted servers because of its ciphertext calculability.  ...  Experimental results show that the time overhead of the homomorphic operations in new FHE scheme will be reduced manyfold with the increasing of processing units number.  ...  cloud computing platform and encrypted with the traditional cryptographic methods.  ... 
doi:10.3837/tiis.2018.01.024 fatcat:h4ai4ywtmbfj5aehlfjmt7v35i

Co-designed accelerator for homomorphic encryption applications

Asma Mkhinini, Paolo Maistri, Régis Leveugle, Rached Tourki
2018 Advances in Science, Technology and Engineering Systems  
In this paper, we present a software/hardware co-designed modular polynomial multiplier in order to accelerate homomorphic schemes.  ...  Experimental results show competitive latencies when compared with handmade designs, while maintaining large advantages on resources.  ...  They provide a fast unit for polynomial operations using CRT and NTT for multiplication combined with an optimized memory access scheme and a Barrett reduction method.  ... 
doi:10.25046/aj030152 fatcat:ymhgzc46pffnnfxdftfonwws2y

Confidential machine learning on untrusted platforms: a survey

Sharma Sagar, Chen Keke
2021 Cybersecurity  
With a unified framework, we highlight the critical challenges and innovations in outsourcing machine learning confidentially.  ...  With such facilities, Jiang et al. ( 2018 ) can optimize matrix-matrix multiplication with only O(k) complexity for symmetric matrices of k dimensions.  ...  The RLWE with message packing realizes homomorphic additions more efficiently when compared to the Paillier scheme.  ... 
doi:10.1186/s42400-021-00092-8 pmid:34805760 pmcid:PMC8591683 fatcat:vmdemrhszjcynp6rytvckg7o5i

Secure and Practical Outsourcing of Linear Programming in Cloud Computing: A Survey

V. Sudarsan, N. Satyanarayana
2017 International Journal of Computer Applications  
In this paper, the modern cryptographic techniques in secure outsourcing along with the research work, which has been proposed in past years, has been presented.  ...  Various engineering, computing and optimization techniques are being used to solve this problem. The investigation has been performed for secure outsourcing of problem for the large-scale systems.  ...  The client-cloud server architecture can be perceived in the figure 1 below:- To solve most of the practical optimization problems, Linear Programming(LP) is the most efficient method to adopt.  ... 
doi:10.5120/ijca2017912903 fatcat:ers7g4pvz5ezpfu6ni2okfhxgm

SoK: Modular and Efficient Private Decision Tree Evaluation

Ágnes Kiss, Masoud Naderpour, Jian Liu, N. Asokan, Thomas Schneider
2019 Proceedings on Privacy Enhancing Technologies  
In this work, we identify the three phases of private decision tree evaluation protocols: feature selection, comparison, and path evaluation.  ...  We systematize constant-round protocols for each of these phases to identify the best available instantiations using the two main paradigms for secure computation: garbling techniques and homomorphic encryption  ...  We compare this method with the protocol of [JS18] that has the same asymptotic complexity. Path evaluation with computationally restricted client.  ... 
doi:10.2478/popets-2019-0026 dblp:journals/popets/KissNLAS19 fatcat:x4whavquyzbuxcdz6j2mcjyrhq

A SURVEY OF HOMOMORPHIC ENCRYPTION OF DATA IN CLOUD FOR SECURE STORAGE

S. Gnana Sophia, K.K Thanammal And S SSujatha
2021 Zenodo  
In this paper wereviewe the homomorphic encryption techniques, Advantages and disadvantages of various research papers.  ...  Lu, Y. and Zhu, M. 2018 Homomorphic encryption algorithm The algorithms' correctness and computational efficiency are tested. Computational complexity Rahman, M.  ...  They will, however, deal with this issue by using a common method to inject an error into a message before encryption.  ... 
doi:10.5281/zenodo.5166891 fatcat:olzgoycipfdwnce4iwl6vfkopu

TASTY

Wilko Henecka, Stefan K ögl, Ahmad-Reza Sadeghi, Thomas Schneider, Immo Wehrenberg
2010 Proceedings of the 17th ACM conference on Computer and communications security - CCS '10  
TASTY provides most recent techniques and optimizations for practical secure two-party computation with low online latency.  ...  We use TASTY to compare protocols for secure multiplication based on homomorphic encryption with those based on garbled circuits and highly efficient Karatsuba multiplication.  ...  Then, S evaluates the polynomial p under homomorphic encryption: p(yi) = a k y k i a k−1 y k−1 i . . . a0 . This is done efficiently with Horner's method.  ... 
doi:10.1145/1866307.1866358 dblp:conf/ccs/HeneckaKSSW10 fatcat:vu3zcsodhbbexhsamaxv64xwra

Search-and-Compute on Encrypted Data [chapter]

Jung Hee Cheon, Miran Kim, Myungsun Kim
2015 Lecture Notes in Computer Science  
The other solution is to use a privacy homomorphic scheme. However, no secure solutions have been developed that meet the efficiency requirements.  ...  Second, we apply two optimization techniques to improve the efficiency of the circuit primitives. One technique is to exploit SIMD techniques to accelerate their basic operations.  ...  We focus on a method of optimizing these circuits with respect to the depth and required homomorphic operations. To do this, we make use of SIMD along with automorphism operation.  ... 
doi:10.1007/978-3-662-48051-9_11 fatcat:bqbbfkdz6fb3plyej6vurbcdb4

Improved Garbled Circuit Building Blocks and Applications to Auctions and Computing Minima [chapter]

Vladimir Kolesnikov, Ahmad-Reza Sadeghi, Thomas Schneider
2009 Lecture Notes in Computer Science  
Performance improvement comes both from building on our efficient basic blocks and several problemspecific GC optimizations.  ...  We describe efficient GC constructions for addition, subtraction, multiplication, and comparison functions.  ...  We obtain an efficient comparison protocol by evaluating the comparison circuit of §3.2 with the GC protocol of [KS08] and an efficient OT protocol.  ... 
doi:10.1007/978-3-642-10433-6_1 fatcat:6tyw6fx76rfxjkji7j5erpurlu

ML with HE: Privacy Preserving Machine Learning Inferences for Genome Studies [article]

Ş. S. Mağara, C. Yıldırım, F. Yaman, B. Dilekoğlu, F. R. Tutaş, E. Öztürk, K. Kaya, Ö. Taştan, E. Savaş
2022 arXiv   pre-print
This work proposes a secure multi-label tumor classification method using homomorphic encryption, whereby two different machine learning algorithms, SVM and XGBoost, are used to classify the encrypted  ...  Preserving the privacy and security of big data in the context of cloud computing, while maintaining a certain level of efficiency of its processing remains to be a subject, open for improvement.  ...  XGBoost inference phase is adapted for HE with an efficient encoding method that speeds up the costly secure comparison operation.  ... 
arXiv:2110.11446v2 fatcat:dnb2vr6abjfudp6d5gmqka5r24

Optimization of the MOVA Undeniable Signature Scheme [chapter]

Jean Monnerat, Yvonne Anne Oswald, Serge Vaudenay
2005 Lecture Notes in Computer Science  
The original MOVA scheme uses characters on Z * n and some additional candidates homomorphisms were proposed with its generalization.  ...  Our optimizations focus on the quartic residue symbol and an homomorphism based on the computation of a discrete logarithm in a hidden subgroup of Z * n .  ...  A comparison with practical parameters (e.g., a modulus n of 1024 bits) with the Jacobi symbol as well as RSA using standard efficient methods is presented at the end of this article.  ... 
doi:10.1007/11554868_14 fatcat:4k5gqsfouvbgpjgd4qmz7nmbcm

Depth Optimized Efficient Homomorphic Sorting [chapter]

Gizem S. Çetin, Yarkın Doröz, Berk Sunar, Erkay Savaş
2015 Lecture Notes in Computer Science  
We first consider a number of well known comparison based sorting algorithms as well as some sorting networks, and analyze their circuit implementations with respect to multiplicative depth.  ...  The reduced depth allows much reduced noise growth and thereby makes it possible to select smaller parameter sizes in somewhat homomorphic encryption instantiations resulting in greater efficiency savings  ...  The secure comparison protocol by Fischlin [13] uses the GM-homomorphic encryption scheme [19] and the method by Sander et al.  ... 
doi:10.1007/978-3-319-22174-8_4 fatcat:fnq2bweewfddnoyblk7d6tsf4y

cuSCNN: A Secure and Batch-Processing Framework for Privacy-Preserving Convolutional Neural Network Prediction on GPU

Yanan Bai, Quanliang Liu, Wenyuan Wu, Yong Feng
2021 Frontiers in Computational Neuroscience  
However, they suffer an efficiency and energy loss when dealing with a larger-scale dataset, due to the complicated encoded methods and intractable ciphertext operations.  ...  the linear layers of CNN, which is a naive method to secure matrix computation operations. (2) To improve the computation efficiency on GPU, a hybrid optimization approach based on CUDA (Compute Unified  ...  time than the comparison methods.  ... 
doi:10.3389/fncom.2021.799977 pmid:35002664 pmcid:PMC8734535 fatcat:alrboxgsxzcthk7mgjmsgvjowy
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