Article
Computer Science, Information Systems
Zhi-Yan Zhao, Peng Zeng
Summary: PKEET is a new cryptographic primitive that allows a proxy to check whether two ciphertexts encrypted under different public keys are of the same plaintext. In this paper, an efficient all-or-nothing public key encryption scheme with authenticated equality test (AoN-PKEAET) is proposed, which provides a new feature of ciphertext authentication before the plaintext equality test to prevent misjudgement.
Article
Computer Science, Information Systems
Xiaoying Shen, Baocang Wang, Licheng Wang, Pu Duan, Benyu Zhang
Summary: In this paper, we propose an efficient and verifiable group public key encryption scheme with equality test, GPKEET/BP, that does not require bilinear pairings. Experimental results show that the test algorithm of our scheme is about 92% faster than the existing scheme by Ling et al., making our GPKEET/BP scheme better suited for group ciphertext equality test situations.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Xin Hou, Xiaofeng Jia, Jun Shao
Summary: We introduce a new cryptographic primitive called public key encryption with public-verifiable decryption delegation (PKE-PVD2), which allows the original decryptor to transmit the decryption key for a specific ciphertext to a designated recipient in a public-verifiable and privacy-preserving manner. This is particularly useful in scenarios where special decryption delegation is required, such as retrieving specific messages from ciphertexts as crucial evidence in court proceedings. We present the first PKE-PVD2 scheme and its security proof using bilinear pairing in the random oracle model, and provide experimental results demonstrating its effectiveness and efficiency.
JOURNAL OF INFORMATION SECURITY AND APPLICATIONS
(2023)
Article
Physics, Multidisciplinary
Huijun Zhu, Qingji Xue, Tianfeng Li, Dong Xie
Summary: This paper introduces a public key encryption supporting equality test (PKEwET) scheme with the ability to trace ciphertexts. The scheme supports authorization and traceability, and achieves a desirable level of security against adversaries with and without a trapdoor. The paper also discusses the performance of the presented scheme.
Article
Computer Science, Theory & Methods
Yu-Chi Chen, Xin Xie, Hung-Yu Tsao, Raylin Tso
Summary: Public key encryption with equality test provides basic cryptographic functionalities without revealing plaintext data. The extended version, public encryption with filtered equality test (PKE-FET), allows testing of ciphertext only for specific data. This paper revisits the notion of PKE-FET on different security models, formalizes its security definition, and introduces a new scheme to enhance security levels.
DESIGNS CODES AND CRYPTOGRAPHY
(2021)
Article
Computer Science, Information Systems
Xi-Jun Lin, Lin Sun, Haipeng Qu, Xiaoshuai Zhang
Summary: PKEET-FA is a critical cryptographic primitive for protecting outsourced data in cloud-based email systems. It offers more efficient equality tests and supports flexible authorization policies, making it more flexible than previous proposals.
COMPUTER COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Willy Susilo, Fuchun Guo, Zhen Zhao, Ge Wu
Summary: Cloud computing removes the need for local hardware architecture and reduces the computation costs for users. To protect privacy, data is encrypted before being sent to the cloud server. However, there are challenges in performing equality tests among multiple ciphertexts in cloud computing, such as information disclosure and redundant computation cost. This article proposes a novel public-key encryption scheme and extends it to the concept of flexible multi-ciphertext equality testing to improve efficiency and security in cloud computing.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Computer Science, Information Systems
Siyue Dong, Zhen Zhao, Baocang Wang, Wen Gao, Shanshan Zhang
Summary: This research proposes a concept of certificateless encryption supporting multi-ciphertext equality test, which addresses the key escrow problem. The scheme enhances security and reduces computational overhead by incorporating proxy-assisted authorization.
Article
Computer Science, Hardware & Architecture
Tian Yang, Sha Ma, Jiaojiao Du, Chengyu Jiang, Qiong Huang
Summary: Public key encryption with equality test (PKEET) is important in cloud storage, allowing a third party to test whether two ciphertexts contain the same message without decryption. To prevent continuous testing by an untrusted third party, we propose the concept of revocable public key encryption with equality test (R-PKEET). Our scheme achieves lightweight revocation and lower computational complexity by utilizing Shamir's secret sharing and Lagrange interpolating polynomial.
Article
Computer Science, Information Systems
Hao Lin, Gaohua Zhao, Shouyou Song, Wei Wu, Wei Jiang
Summary: Public key encryption with equality test (PKEET) allows testing if two ciphertexts generated from different public keys contain the same message without decryption. It has been extensively researched for its security, efficiency, and functionality. Existing proposals of PKEET schemes have large ciphertext sizes, which pose a storage burden for cloud servers. To address this issue, this paper introduces a lightweight version of PKEET (L-PKEET) and presents a concrete construction that efficiently reduces ciphertext sizes.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Huijun Zhu, Licheng Wang, Haseeb Ahmad, Dong Xie
Summary: The proposed efficient public key encryption scheme with discrete logarithm improves computational efficiency and security, reducing time cost for decryption and test phase by at least 39% and 68% respectively compared to existing schemes.
Article
Automation & Control Systems
Tung-Tso Tsai, Han-Yu Lin, Han-Ching Tsai
Summary: Traditional public key cryptography requires certificates to link user identity and public key, but building a public key infrastructure is resource-intensive and complex. Certificateless public key encryption (CL-PKC) eliminates the need for certificates, and the certificateless public key encryption with equality test (CL-PKEET) mechanism is suitable for cloud applications, providing confidentiality of private data and equality testing of ciphertext. The proposed article introduces RCL-PKEET, the first revocable CL-PKEET scheme, which effectively removes illegal users while maintaining the effectiveness of existing CL-PKEET schemes. The security of the proposed scheme is formally demonstrated under the bilinear Diffie-Hellman assumption.
INFORMATION TECHNOLOGY AND CONTROL
(2022)
Article
Computer Science, Theory & Methods
Qinyi Li, Xavier Boyen
Summary: This research revises and enhances the PKEET security model and proposes a simple and efficient system to prevent attackers from skirting the test. The new system relies on weaker learning-with-errors assumptions while being more efficient and providing better security compared to existing literature.
THEORETICAL COMPUTER SCIENCE
(2021)
Article
Computer Science, Information Systems
Hao Lin, Fei Gao, Hua Zhang, Zhengping Jin, Wenmin Li, Qiaoyan Wen
Summary: This article introduces a new encryption scheme PKEET-FDA, where users can adaptively authorize multiple testers to test their ciphertexts, avoiding the issue of repeatedly encrypting messages while ensuring data security.
IEEE SYSTEMS JOURNAL
(2022)
Article
Computer Science, Information Systems
Huijun Zhu, Haseeb Ahmad, Qingji Xue, Tianfeng Li, Ziyu Liu, Ao Liu
Summary: The proliferation of big data has increased the amount of remotely stored data, making it essential to encrypt and secure the data for privacy preservation. However, performing operations on encrypted data is often challenging. To address this issue, a public key encryption approach based on the equality test function is proposed, which allows secure comparison of encrypted data without revealing the actual data.
Article
Computer Science, Information Systems
Hyung Tae Lee, San Ling, Jae Hong Seo, Huaxiong Wang, Taek-Young Youn
INFORMATION SCIENCES
(2020)
Article
Computer Science, Theory & Methods
Keita Emura, Jae Hong Seo, Yohei Watanabe
Summary: Revocation functionality is crucial for managing the reliability of cryptographic systems, especially in the context of identity-based encryption (IBE) schemes such as revocable IBE (RIBE) and the security notion of decryption key exposure resistance (DKER). This paper presents an RIBE scheme that achieves adaptive security, DKER, constant-size public parameters, and is constructed over prime-order bilinear groups, building upon previous techniques. The proposed RIBE scheme can be extended to chosen-ciphertext secure and server-aided schemes.
THEORETICAL COMPUTER SCIENCE
(2021)
Article
Computer Science, Theory & Methods
Benoit Libert, San Ling, Fabrice Mouhartem, Khoa Nguyen, Huaxiong Wang
Summary: Adaptive oblivious transfer is a protocol where the sender commits to a database initially, allowing the receiver to query the sender multiple times to obtain specific information, with the receiver's choices potentially influenced by previously obtained messages.
THEORETICAL COMPUTER SCIENCE
(2021)
Article
Computer Science, Information Systems
Martianus Frederic Ezerman, John Mark Lampos, San Ling, Buket Ozkaya, Jareena Tharnnukhroh
Summary: The spectral bounds on the minimum distance of quasi-twisted codes over finite fields are proposed based on eigenvalues of polynomial matrices and eigenspaces. The relationship between eigencodes of quasi-twisted codes and outer codes in its concatenated structure is explored, and comparisons show that the Jensen bound outperforms the spectral bound under special conditions. Performance comparisons of the Lally, Jensen, and spectral bounds are presented.
IEEE TRANSACTIONS ON INFORMATION THEORY
(2021)
Article
Computer Science, Information Systems
Bocong Chen, San Ling, Hongwei Liu
Summary: In this paper, the dimension of the hull RSk(a) boolean AND RSk(a)(perpendicular to) is completely determined in terms of the degree of the derivative of h and some relevant polynomials by expressing RSk(a) as an L-construction algebraic geometry code. As applications, the parameters of MDS entanglement-assisted quantum error-correcting codes constructed from RS codes are explicitly determined, and all linear complementary dual (resp. self-dual) RS codes are also fully described.
IEEE TRANSACTIONS ON INFORMATION THEORY
(2023)
Article
Computer Science, Information Systems
Gaojun Luo, Xiwang Cao, Martianus Frederic Ezerman, San Ling
Summary: In this paper, a new family of matrices is proposed by combining Vandermonde and Moore matrices. Using these matrices, a new family of convolutional codes with memory 1 and maximum distance profile is constructed. The alphabet sizes of these codes can be significantly smaller than previous results while maintaining the code rate.
IEEE TRANSACTIONS ON INFORMATION THEORY
(2023)
Article
Computer Science, Information Systems
Gaojun Luo, Martianus Frederic Ezerman, San Ling
Summary: This paper focuses on constructing locally repairable codes that achieve equality in the Singleton-type bound with (r, delta)-locality. We propose two constructions of q-ary optimal (r, delta) locally repairable codes with lengths up to q(2)+q using matrix-product codes, which include linear maximum distance separable codes. Additionally, we provide another construction of optimal (r, delta) locally repairable codes by utilizing optimal locally repairable codes as ingredients in the matrix-product approach. These three constructions are new and cover different parameter sets compared to previously constructed codes in the literature. Our construction proposals offer flexibility by allowing variations in r and delta for various scenarios.
IEEE TRANSACTIONS ON INFORMATION THEORY
(2023)
Article
Computer Science, Theory & Methods
Hyung Tae Lee, Jae Hong Seo
Summary: In this paper, the authors refine the definitions of the generic group model and security notions for functional encryption schemes. They then prove that for certain group-based functional encryption schemes satisfying specific conditions, they can reduce from selective security in the standard model to adaptive security in the generic group model, regardless of the functionalities of the schemes.
DESIGNS CODES AND CRYPTOGRAPHY
(2023)
Article
Computer Science, Information Systems
Gaojun Luo, Martianus Frederic Ezerman, San Ling, Xu Pan
Summary: In emerging storage technologies, the use of symbol-pair codes has been proposed as a solution to control errors caused by overlapping pairs of symbols in channel outputs. Instead of the usual minimum Hamming distance, the error-correcting capability of these codes depends on their minimum pair distance. Longer codes can be constructed conveniently from shorter ones using a matrix-product approach, and the parameters of a matrix-product code can be determined from the parameters of the ingredient codes. New families of MDS and almost MDS symbol-pair matrix-product codes have been constructed, which offer improved minimum pair distances compared to permutation equivalent codes.
IEEE TRANSACTIONS ON INFORMATION THEORY
(2023)
Proceedings Paper
Computer Science, Information Systems
Sungwook Kim, Hyeonbum Lee, Jae Hong Seo
Summary: This paper proposes three interactive zero-knowledge arguments for arithmetic circuit of size N in the common random string model, which can be converted to be non-interactive by Fiat-Shamir heuristics in the random oracle model. The three arguments have different communication and computational complexities, and the third argument does not rely on pairing-friendly elliptic curves. The soundness of the three arguments is proven under the standard discrete logarithm and/or the double pairing assumption.
ADVANCES IN CRYPTOLOGY- ASIACRYPT 2022, PT II
(2022)
Article
Computer Science, Information Systems
Bora Jeong, Sunpill Kim, Seunghun Paik, Jae Hong Seo
Summary: This study presents a deep learning-based technique for improved biometric authentication, specifically in facial recognition. It also introduces a method for protecting the feature vectors used in the recognition process. Additionally, an impersonation attack is proposed to assess the security of the protection method.
Proceedings Paper
Computer Science, Information Systems
Chanyang Ju, Wenyi Tang, Changhao Chenli, Gwangwoon Lee, Jae Hong Seo, Taeho Jung
Summary: Personal data provenance monitoring is necessary for transparency and accountability, but it faces challenges due to decentralized service provider relationships. We propose using blockchain to track data provenance and introduce a new extended vector commitment scheme. Experimental results show that the overhead of this scheme is negligible in most processes and acceptable in others.
2022 IEEE INTERNATIONAL CONFERENCE ON BLOCKCHAIN (BLOCKCHAIN 2022)
(2022)
Article
Computer Science, Information Systems
Heewon Chung, Kyoohyung Han, Chanyang Ju, Myungsun Kim, Jae Hong Seo
Summary: This paper presents a new short zero-knowledge argument for range proof and arithmetic circuits that does not require a trusted setup. It achieves the shortest proof size among similar systems without a trusted setup. The proposed method, Bulletproofs+, reduces both range proof and arithmetic circuit proof sizes, while maintaining comparable computational overheads to Bulletproofs. It has been recognized as an improvement over Bulletproofs with its zero-knowledge weighted inner product argument.
Proceedings Paper
Computer Science, Artificial Intelligence
Sunpill Kim, Yunseong Jeong, Jinsu Kim, Jungkon Kim, Hyung Tae Lee, Jae Hong Seo
Summary: In this study, a modular architecture called IronMask was proposed for protecting face templates, and its effectiveness was evaluated through experiments with two face recognition systems. IronMask maintains high recognition performance while protecting user privacy, providing a high level of security against known attacks.
2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, CVPR 2021
(2021)
Article
Computer Science, Information Systems
Chanyang Ju, Hyeonbum Lee, Heewon Chung, Jae Hong Seo, Sungwook Kim
Summary: The paper focuses on verifying the accuracy of CNNs in image recognition and classification, proposing a predicate function based on validating matrix multiplication operations. By reducing the proving cost, an efficient sum-check protocol is provided for convolution operations, which is approximately 2x cheaper in terms of communication costs compared to the state-of-the-art zkCNN approach.
Article
Computer Science, Information Systems
Xia Liang, Jie Guo, Peide Liu
Summary: This paper investigates a novel consensus model based on social networks to manage manipulative and overconfident behaviors in large-scale group decision-making. By proposing a novel clustering model and improved methods, the consensus reaching is effectively facilitated. The feedback mechanism and management approach are employed to handle decision makers' behaviors. Simulation experiments and comparative analysis demonstrate the effectiveness of the model.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Xiang Li, Haiwang Guo, Xinyang Deng, Wen Jiang
Summary: This paper proposes a method based on class gradient networks for generating high-quality adversarial samples. By introducing a high-level class gradient matrix and combining classification loss and perturbation loss, the method demonstrates superiority in the transferability of adversarial samples on targeted attacks.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Lingyun Lu, Bang Wang, Zizhuo Zhang, Shenghao Liu
Summary: Many recommendation algorithms only rely on implicit feedbacks due to privacy concerns. However, the encoding of interaction types is often ignored. This paper proposes a relation-aware neural model that classifies implicit feedbacks by encoding edges, thereby enhancing recommendation performance.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Jaehong Yu, Hyungrok Do
Summary: This study discusses unsupervised anomaly detection using one-class classification, which determines whether a new instance belongs to the target class by constructing a decision boundary. The proposed method uses a proximity-based density description and a regularized reconstruction algorithm to overcome the limitations of existing one-class classification methods. Experimental results demonstrate the superior performance of the proposed algorithm.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Hui Tu, Shifei Ding, Xiao Xu, Haiwei Hou, Chao Li, Ling Ding
Summary: Border-Peeling algorithm is a density-based clustering algorithm, but its complexity and issues on unbalanced datasets restrict its application. This paper proposes a non-iterative border-peeling clustering algorithm, which improves the clustering performance by distinguishing and associating core points and border points.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Long Tang, Pan Zhao, Zhigeng Pan, Xingxing Duan, Panos M. Pardalos
Summary: In this work, a two-stage denoising framework (TSDF) is proposed for zero-shot learning (ZSL) to address the issue of noisy labels. The framework includes a tailored loss function to remove suspected noisy-label instances and a ramp-style loss function to reduce the negative impact of remaining noisy labels. In addition, a dynamic screening strategy (DSS) is developed to efficiently handle the nonconvexity of the ramp-style loss.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Raghunathan Krishankumar, Sundararajan Dhruva, Kattur S. Ravichandran, Samarjit Kar
Summary: Health 4.0 is gaining global attention for better healthcare through digital technologies. This study proposes a new decision-making framework for selecting viable blockchain service providers in the Internet of Medical Things (IoMT). The framework addresses the limitations in previous studies and demonstrates its applicability in the Indian healthcare sector. The results show the top ranking BSPs, the importance of various criteria, and the effectiveness of the developed model.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Tao Tan, Hong Xie, Liang Feng
Summary: This paper proposes a heterogeneous update idea and designs HetUp Q-learning algorithm to enlarge the normalized gap by overestimating the Q-value corresponding to the optimal action and underestimating the Q-value corresponding to the other actions. To address the limitation, a softmax strategy is applied to estimate the optimal action, resulting in HetUpSoft Q-learning and HetUpSoft DQN. Extensive experimental results show significant improvements over SOTA baselines.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Chao Yang, Xianzhi Wang, Lina Yao, Guodong Long, Guandong Xu
Summary: This paper proposes a dynamic transformer-based architecture called Dyformer for multivariate time series classification. Dyformer captures multi-scale features through hierarchical pooling and adaptive learning strategies, and improves model performance by introducing feature-map-wise attention mechanisms and a joint loss function.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Xiguang Li, Baolu Feng, Yunhe Sun, Ammar Hawbani, Saeed Hammod Alsamhi, Liang Zhao
Summary: This paper proposes an enhanced scatter search strategy, using opposition-based learning, to solve the problem of automated test case generation based on path coverage (ATCG-PC). The proposed ESSENT algorithm selects the path with the lowest path entropy among the uncovered paths as the target path and generates new test cases to cover the target path by modifying the dimensions of existing test cases. Experimental results show that the ESSENT algorithm outperforms other state-of-the-art algorithms, achieving maximum path coverage with fewer test cases.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Shirin Dabbaghi Varnosfaderani, Piotr Kasprzak, Aytaj Badirova, Ralph Krimmel, Christof Pohl, Ramin Yahyapour
Summary: Linking digital accounts belonging to the same user is crucial for security, user satisfaction, and next-generation service development. However, research on account linkage is mainly focused on social networks, and there is a lack of studies in other domains. To address this, we propose SmartSSO, a framework that automates the account linkage process by analyzing user routines and behavior during login processes. Our experiments on a large dataset show that SmartSSO achieves over 98% accuracy in hit-precision.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Renchao Wu, Jianjun He, Xin Li, Zuguo Chen
Summary: This paper proposes a memetic algorithm with fuzzy-based population control (MA-FPC) to solve the joint order batching and picker routing problem (JOBPRP). The algorithm incorporates batch exchange crossover and a two-level local improvement procedure. Experimental results show that MA-FPC outperforms existing algorithms in terms of solution quality.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Guoxiang Zhong, Fagui Liu, Jun Jiang, Bin Wang, C. L. Philip Chen
Summary: In this study, we propose the AMFormer framework to address the problem of mixed normal and anomaly samples in deep unsupervised time-series anomaly detection. By refining the one-class representation and introducing the masked operation mechanism and cost sensitive learning theory, our approach significantly improves anomaly detection performance.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Jin Zhou, Kang Zhou, Gexiang Zhang, Ferrante Neri, Wangyang Shen, Weiping Jin
Summary: In this paper, the authors focus on the issue of multi-objective optimisation problems with redundant variables and indefinite objective functions (MOPRVIF) in practical problem-solving. They propose a dual data-driven method for solving this problem, which consists of eliminating redundant variables, constructing objective functions, selecting evolution operators, and using a multi-objective evolutionary algorithm. The experiments conducted on two different problem domains demonstrate the effectiveness, practicality, and scalability of the proposed method.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Georgios Charizanos, Haydar Demirhan, Duygu Icen
Summary: This article proposes a new fuzzy logistic regression framework that addresses the problems of separation and imbalance while maintaining the interpretability of classical logistic regression. By fuzzifying binary variables and classifying subjects based on a fuzzy threshold, the framework demonstrates superior performance on imbalanced datasets.
INFORMATION SCIENCES
(2024)
