Article
Computer Science, Information Systems
Christiana Zaraket, Khalil Hariss, Maroun Chamoun, Tony Nicolas
Summary: This paper presents a new secure and efficient homomorphic encryption scheme for sensitive data. The scheme demonstrates high efficiency and security in implementation, and outperforms existing schemes in terms of performance.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Xiaopeng Yu, Wei Zhao, Yunfan Huang, Juan Ren, Dianhua Tang
Summary: This study proposes an efficient privacy-preserving outsourced logistic regression (POLR-O-2) scheme based on homomorphic encryption (HE) to address the privacy protection and efficiency issues encountered by data owners when training logistic regression models on cloud service providers.
SECURITY AND COMMUNICATION NETWORKS
(2022)
Article
Cardiac & Cardiovascular Systems
Jose Cabrero-Holgueras, Sergio Pastrana
Summary: Cardiovascular disease is a significant part of healthcare systems, and remote monitoring solutions are needed. Deep Learning has been successfully applied in healthcare, but computational requirements and limited datasets pose challenges. Machine-Learning-as-a-Service platforms have emerged, but privacy and security concerns remain. Homomorphic Encryption is a promising tool for improving cardiovascular health outside hospitals while ensuring privacy and legality.
FRONTIERS IN CARDIOVASCULAR MEDICINE
(2023)
Article
Computer Science, Theory & Methods
Asma Aloufi, Peizhao Hu, Yongsoo Song, Kristin Lauter
Summary: This article discusses the importance and applications of homomorphic encryption (HE), addresses the issue of secure computations on ciphertexts encrypted under multiple keys, and provides a comprehensive survey and analysis of the latest multi-key techniques and schemes.
ACM COMPUTING SURVEYS
(2022)
Article
Computer Science, Theory & Methods
Seungwan Hong, Seunghong Kim, Jiheon Choi, Younho Lee, Jung Hee Cheon
Summary: This study introduces an efficient sorting method for encrypted data using fully homomorphic encryption, utilizing k-way sorting networks to improve performance by reducing the depth of comparison operations. It proposes a formula to estimate the appropriate k value for optimal efficiency.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2021)
Article
Computer Science, Theory & Methods
Jung Hee Cheon, Wootae Kim, Jai Hyun Park
Summary: This paper introduces a method using domain extension polynomials (DEPs) to efficiently evaluate functions on large intervals in the state of homomorphic encryption. By iterating DEPs, the domain of a given function can be extended by a factor of k while preserving the features of the original function. This method is more efficient and requires less computational operations and memory compared to previous approaches.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2022)
Article
Computer Science, Theory & Methods
Lanxiang Chen, Yi Mu, Lingfang Zeng, Fatemeh Rezaeibagha, Robert H. Deng
Summary: In this paper, a novel approach is proposed to achieve privacy-preserving statistical analysis on an encrypted database. A privacy-preserving calculator is constructed to calculate attributes' count values for later statistical analysis, and an authenticable additive homomorphic encryption scheme is adopted to authenticate these encrypted count values. Furthermore, a cryptosystem based on binary vectors is proposed to achieve complex logic expressions for statistical analysis on encrypted data. Several protocols for statistical analysis, including conjunctive, disjunctive, and complex logic expressions, are designed with the aid of the proposed cryptographic calculator to achieve more complicated statistical functionalities. Experimental results show the feasibility and practicality of the proposed scheme.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2023)
Article
Computer Science, Information Systems
Jim Basilakis, Bahman Javadi
Summary: This paper examines accelerating binary operations on real numbers suitable for somewhat homomorphic encryption using a parallel solution based on SIMD. The results show that this method achieves good performance in terms of computational efficiency, memory space usage, and minimizing multiplicative circuit depth. These accelerated binary primitives are demonstrated to be applicable and efficient in various case studies, including min-max and sorting operations.
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING
(2021)
Article
Computer Science, Information Systems
Jun Zhang, Zoe L. Jiang, Ping Li, Siu Ming Yiu
Summary: Preparing large amounts of training data is crucial for the success of machine learning, while privacy-preserving techniques like homomorphic encryption are proposed to address individual privacy concerns. Collaboration between different institutions is common in the era of big data, but there are risks to data privacy when encrypting data under a single key in multi-institution scenarios.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Artificial Intelligence
Ahmad Al Badawi, Ling Chen, Saru Vig
Summary: This article presents FHSVM, a fast homomorphic evaluation method for non-linear SVM prediction using fully homomorphic encryption. Through design and optimization, FHSVM achieves efficient privacy-preserving machine learning applications in terms of real-time performance and data utilization.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Computer Science, Software Engineering
Sebastian Mazza, Daniel Patel, Ivan Viola
Summary: The study introduces a method for volume rendering directly on encrypted volume data using the homomorphic Paillier encryption algorithm to ensure the privacy of the volume data and rendered images from the rendering server. Novel approaches for encrypted-data compositing are introduced, along with performance and memory overhead analysis associated with the privacy-preserving scheme.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2021)
Article
Engineering, Chemical
Atharva Suryavanshi, Aisha Alnajdi, Mohammed Alhajeri, Fahim Abdullah, Panagiotis D. Christofides
Summary: In this work, secure and private communication links are established between sensor-controller and controller-actuator elements using semi-homomorphic encryption to ensure cyber-security in model predictive control (MPC) of nonlinear systems. The Paillier cryptosystem is implemented for encryption-decryption operations in the communication links. The closed-loop encrypted MPC is designed with a certain degree of robustness to the quantization errors in nonlinear systems, and the trade-off between accuracy and computational cost is discussed. Chemical process examples are employed to demonstrate the implementation of the proposed encrypted MPC design.
Article
Automation & Control Systems
Junsoo Kim, Hyungbo Shim, Kyoohyung Han
Summary: In this article, a dynamic feedback controller is presented that can compute the next state and control signal over encrypted data using the homomorphic properties of cryptosystems. It is shown that any linear time-invariant controller's state matrix can be converted to a matrix of integer components when the input and output of the plant are encrypted and transmitted back to the controller. The article also demonstrates the use of a cryptosystem based on the Learning With Errors problem for practical implementation, which allows both multiplication and addition over encrypted data. Additionally, it is shown that the injected random numbers during encryption can be controlled within a small bound through closed-loop stability.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Hao-Tian Wu, Yiu-Ming Cheung, Zhenwei Zhuang, Lingling Xu, Jiankun Hu
Summary: Reversible data hiding in ciphertext has potential applications for privacy protection and transmitting extra data in a cloud environment. However, applying homomorphic processing to an encrypted image with hidden data is challenging due to possible changes in image content caused by preprocessing or/and data embedding. To address this issue, a lossless data hiding method called random element substitution (RES) is proposed, which replaces the to-be-hidden bits with the random element of a cipher value. The RES method is combined with another preprocessing-free algorithm to generate two schemes for lossless data hiding in encrypted images.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Computer Science, Information Systems
Pyung Kim, Eunji Jo, Younho Lee
Summary: This study improved the existing hybrid homomorphic encryption, proposed an efficient search method working on multiple encrypted databases, and determined the optimal number of databases needed for 40-bit encrypted information. Experimental results showed the ability to quickly check the existence of specific data in a large encrypted database.
Article
Computer Science, Hardware & Architecture
Joppe W. Bos, Simon J. Friedberger
IEEE TRANSACTIONS ON COMPUTERS
(2019)
Article
Computer Science, Theory & Methods
Joppe W. Bos, Craig Costello, Huseyin Hisil, Kristin Lauter
JOURNAL OF CRYPTOLOGY
(2016)
Article
Computer Science, Theory & Methods
Estuardo Alpirez Bock, Joppe W. Bos, Chris Brzuska, Charles Hubain, Wil Michiels, Cristofaro Mune, Eloi Sanfelix Gonzalez, Philippe Teuwen, Alexander Treff
JOURNAL OF CRYPTOLOGY
(2019)
Article
Energy & Fuels
Emilio J. Palacios-Garcia, Xavier Carpent, Joppe W. Bos, Geert Deconinck
Summary: Residential demand side management (DMS) is an effective tool for maintaining network balance, but privacy concerns related to user personal consumption data have hindered its widespread adoption. This paper proposes a privacy-preserving aggregation algorithm based on additive random shares and a combination of symmetric and asymmetric key cryptography methods. The algorithm is compared with other techniques such as additive homomorphic encryption (AHE) and state-of-the-art MPC protocols. The results show that while generic techniques like homomorphic encryption are computationally expensive, MPC approaches provide better performance and resilience for large networks. The proposed additive random shares algorithm is considered the most balanced choice for DSM, offering good performance, simpler information flow, and the ability to add redundant intermediary parties for enhanced resilience.
Article
Computer Science, Theory & Methods
Joppe W. Bos, Simon J. Friedberger
JOURNAL OF CRYPTOGRAPHIC ENGINEERING
(2020)
Proceedings Paper
Computer Science, Software Engineering
Christopher Ambrose, Joppe W. Bos, Bjoern Fay, Marc Joye, Manfred Lochter, Bruce Murray
TOPICS IN CRYPTOLOGY - CT-RSA 2018
(2018)
Proceedings Paper
Computer Science, Software Engineering
Joppe W. Bos, Wouter Castryck, Ilia Iliashenko, Frederik Vercauteren
PROGRESS IN CRYPTOLOGY - AFRICACRYPT 2017
(2017)
Proceedings Paper
Computer Science, Theory & Methods
Joppe W. Bos, Simon Friedberger
2017 IEEE 24TH SYMPOSIUM ON COMPUTER ARITHMETIC (ARITH)
(2017)
Article
Computer Science, Theory & Methods
Paul Bottinelli, Joppe W. Bos
JOURNAL OF CRYPTOGRAPHIC ENGINEERING
(2017)
Proceedings Paper
Computer Science, Hardware & Architecture
Charlotte Bonte, Carl Bootland, Joppe W. Bos, Wouter Castryck, Ilia Iliashenko, Frederik Vercauteren
CRYPTOGRAPHIC HARDWARE AND EMBEDDED SYSTEMS - CHES 2017
(2017)
Proceedings Paper
Computer Science, Hardware & Architecture
Joppe W. Bos, Charles Hubain, Wil Michiels, Philippe Teuwen
CRYPTOGRAPHIC HARDWARE AND EMBEDDED SYSTEMS - CHES 2016
(2016)
Proceedings Paper
Computer Science, Information Systems
Joppe Bos, Craig Costello, Leo Ducas, Ilya Mironov, Michael Naehrig, Valeria Nikolaenko, Ananth Raghunathan, Douglas Stebila
CCS'16: PROCEEDINGS OF THE 2016 ACM SIGSAC CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY
(2016)
Proceedings Paper
Computer Science, Theory & Methods
Joppe W. Bos, Craig Costello, Michael Naehrig, Douglas Stebila
2015 IEEE SYMPOSIUM ON SECURITY AND PRIVACY SP 2015
(2015)
Proceedings Paper
Computer Science, Theory & Methods
Thorsten Kleinjung, Joppe W. Bos, Aden K. Lenstra
ADVANCES IN CRYPTOLOGY - ASIACRYPT 2014, PT I
(2014)