A5011982610- Cryptography and Data Security
- Privacy-Preserving Technologies in Data
- Blockchain Technology Applications and Security
- Cryptographic Implementations and Security
- Complexity and Algorithms in Graphs
- Coding theory and cryptography
- Chaos-based Image/Signal Encryption
- Cryptography and Residue Arithmetic
- Optimization and Search Problems
- Service-Oriented Architecture and Web Services
- Graph Theory and Algorithms
- Mobile Ad Hoc Networks
- Advanced Steganography and Watermarking Techniques
- Advanced Software Engineering Methodologies
- Tensor decomposition and applications
- Model-Driven Software Engineering Techniques
- Advanced Computational Techniques and Applications
- Computational Physics and Python Applications
- Cloud Data Security Solutions
- VLSI and FPGA Design Techniques
- Polynomial and algebraic computation
- Security in Wireless Sensor Networks
- Parallel Computing and Optimization Techniques
Anhui University of Technology
2024
ShanghaiTech University
2019-2023
Shanghai Institute of Microsystem and Information Technology
2022-2023
University of Chinese Academy of Sciences
2022-2023
Wuhan University
2018
Chongqing University
2017
United Nations University Institute on Computing and Society
2007
Zhengzhou University of Light Industry
2006
University of Wollongong
2005
In the recent years, vulnerabilities of conventional public key infrastructure are exposed by real-world attacks, such as certificate authority's single-point-of-failure or clients' private information leakage. Aimed at first issue, one type approach is that multiple entities introduced to assist operations, including registration, update, and revocation. However, it inefficient in computation. Another make publicly visible bringing log servers. Nevertheless, data synchronization among...
Graph Partitioning is widely used in many real-world applications such as fraud detection and social network analysis, order to enable the distributed graph computing on large graphs. However, existing works fail balance computation cost communication machines with different power (including capability, bandwidth memory size), they only consider replication factor neglect difference of realistic data centers. In this paper, we propose a general partitioning algorithm WindGP, which can...
An <inline-formula><tex-math notation="LaTeX">$(n,m,t)$</tex-math></inline-formula> -homomorphic secret sharing (HSS) scheme for a function family notation="LaTeX">$\mathcal F$</tex-math></inline-formula> allows notation="LaTeX">$n$</tex-math></inline-formula> clients to share their data notation="LaTeX">$x_{1}, \ldots,x_{n}$</tex-math></inline-formula> among notation="LaTeX">$m$</tex-math></inline-formula> servers and then distribute the computation of any notation="LaTeX">$f\in {\mathcal...
There are two main security concerns in outsourcing computations. One is how to protect the privacy of outsourced data, and other ensure correctness Homomorphic secret sharing (HSS) schemes allow a client store set private data on servers then offload computation servers. Such that each individual server learns no information about data. While HSS use key verify results exist relieve both concerns, current literature lacks <italic xmlns:mml="http://www.w3.org/1998/Math/MathML"...
The kernel function of the Diffie-Hellman (DH) protocol is a modular exponentiation over finite field with high computational complexity. In this paper, we propose novel key generation algorithm for DH agreement that derives efficiency from constructing parallel architecture. Compared to serial structure traditional binary representation (BR) method, our significantly more on and suitable hardware implementation in an ephemeral-static mode which thought be secure (Rosorla, 1999)
In recent years, Graph Neural Networks (GNNs) have ignited a surge of innovation, significantly enhancing the processing geometric data structures such as graphs, point clouds, and meshes. As domain continues to evolve, series frameworks libraries are being developed push GNN efficiency new heights. While graph-centric achieved success in past, advent efficient tensor compilers has highlighted urgent need for tensor-centric libraries. Yet, GNNs remain scarce due unique challenges limitations...
When using machine learning classifiers to classify data in cloud computing, it is crucial maintain privacy and ensure the correctness of classification results. To address these security concerns, we propose a new verifiable homomorphic secret sharing (VHSS) scheme. Our approach involves distributing task executing polynomial form classifier among two servers who produce partial results on encrypted data. Each server cannot obtain any information, result can be reconstructed verified...
Against the problems emerged in protocols presented by N. Modadugu, D.Boneh and M. Kim (2000), new server-aided public key generation on low-power devices are proposed this paper. The secure against some passive attacks, such as "collusion attack" "the third party attack". In addition, efficiency of primality test is improved Prospective applications would be found mobile e-commence, ad-hoc, military communications
Catalano and Fiore propose a scheme to transform linearly-homomorphic encryption into homomorphic capable of evaluating quadratic computations on ciphertexts. Their is based the (such as Goldwasser-Micali, Paillier ElGamal) need perform large integer operation servers. Then, their have numerous At same time, cannot verify evaluate more than degree-4 computations. To solve these problems, we no longer use which number theory assumptions. We label pseudorandom function encrypt message,...
Due to the great development of secure multi-party computation, many practical computation schemes have been proposed. As an example, different auction mechanisms widely studied, which can protect bid privacy while satisfying various economic properties. However, as far we know, none them solve problems for multiple data providers (e.g., cloud resource auctions) in malicious security model. In this paper, use techniques cut-and-choose and garbled circuits propose a general framework against...