Searched for: author%3A%22Liang%2C+K.%22
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Li, Wenting (author), Wang, Ping (author), Liang, K. (author)
Password-only authentication is one of the most popular secure mechanisms for real-world online applications. But it easily suffers from a practical threat - password leakage, incurred by external and internal attackers. The external attacker may compromise the password file stored on the authentication server, and the insider may...
journal article 2023
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Liang, K. (author), Smaragdakis, G. (author)
contribution to periodical 2023
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Zhou, Junwei (author), Lei, Botian (author), Lang, Huile (author), Panaousis, Emmanouil (author), Liang, K. (author), Xiang, Jianwen (author)
Genotype imputation estimates missing genotypes from the haplotype or genotype reference panel in individual genetic sequences, which boosts the potential of genome-wide association and is essential in genetic data analysis. However, the genetic sequences involve people's privacy, confirming an individual's identification and even disease...
journal article 2023
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Chen, E. (author), Zhu, Yan (author), Liang, K. (author), Yin, Hongjian (author)
The increasing popularity of remote Cloud File Sharing (CFS) has become a major concern for privacy breach of sensitive data. Aiming at this concern, we present a new resource sharing framework by integrating enterprise-side Attribute-Based Access Control/eXtensible Access Control Markup Language (ABAC/XACML) model, client-side Ciphertext...
journal article 2023
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Ghavamipour, Ali Reza (author), Turkmen, Fatih (author), Wang, Rui (author), Liang, K. (author)
Synthetic data generation plays a crucial role in many areas where data is scarce and privacy/confidentiality is a significant concern. Generative Adversarial Networks (GANs), arguably one of the most widely used data synthesis techniques, allow for the training of a model (i.e., generator) that can generate real-looking data by playing a min...
conference paper 2023
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Wang, Wei (author), Liu, Dongli (author), Xu, Peng (author), Yang, Laurence Tianruo (author), Liang, K. (author)
It has become a trend for clients to outsource their encrypted databases to remote servers and then leverage the Searchable Encryption technique to perform secure data retrieval. However, the method has yet to be considered a crucial need for replication on searchable encrypted data. It calls for challenging works on Dynamic Searchable...
journal article 2023
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Gordijn, Daan (author), Kromes, R.G. (author), Giannetsos, Thanassis (author), Liang, K. (author)
This work aims to provide a more secure access control in Hyperledger Fabric blockchain by combining multiple ID’s, attributes, and policies with the components that regulate access control. The access control system currently used by Hyperledger Fabric is first completely analyzed. Next, a new implementation is proposed that builds upon the...
conference paper 2023
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Grishkov, I. (author), Kromes, R.G. (author), Giannetsos, Thanassis (author), Liang, K. (author)
This paper offers a prototype of a Hyperledger Fabric-IPFS based network architecture including a smart contract based encryption scheme that meant to improve the security of user’s data that is being uploaded to the distributed ledger. A new extension to the self-encryption scheme was deployed by integrating data owner’s identity into the...
conference paper 2023
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Li, Wenting (author), Yang, Jiahong (author), Cheng, Haibo (author), Wang, Ping (author), Liang, K. (author)
Modeling password distributions is a fundamental problem in password security, benefiting the research and applications on password guessing, password strength meters, honey password vaults, etc. As one of the best segment-based password models, WordPCFG has been proposed to capture individual semantic segments (called words) in passwords....
conference paper 2023
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Wang, Lili (author), Lin, Ye (author), Yao, Ting (author), Xiong, Hu (author), Liang, K. (author)
Existing proxy re-encryption (PRE) schemes to secure cloud data sharing raise challenges such as supporting the heterogeneous system efficiently and achieving the unbounded feature. To address this problem, we proposed a fast and secure unbounded cross-domain proxy re-encryption scheme, named FABRIC, which enables the delegator to authorize...
journal article 2023
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Zhu, Hangyu (author), Wang, R. (author), Jin, Yaochu (author), Liang, K. (author)
Federated learning (FL) is an emerging privacy preserving machine learning protocol that allows multiple devices to collaboratively train a shared global model without revealing their private local data. Nonparametric models like gradient boosting decision trees (GBDTs) have been commonly used in FL for vertically partitioned data. However,...
journal article 2023
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He, Daojing (author), Du, Runmeng (author), Zhu, Shanshan (author), Zhang, Min (author), Liang, K. (author), Chan, Sammy (author)
Data island effectively blocks the practical application of machine learning. To meet this challenge, a new framework known as federated learning was created. It allows model training on a large amount of scattered data owned by different data providers. This article presents a parallel solution for computing logistic regression based on...
journal article 2022
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Xu, Peng (author), Susilo, Willy (author), Wang, Wei (author), Chen, Tianyang (author), Wu, Qianhong (author), Liang, K. (author), Jin, Hai (author)
Dynamic searchable symmetric encryption (DSSE) has been widely recognized as a promising technique to delegate update and search queries over an outsourced database to an untrusted server while guaranteeing the privacy of data. Many efforts on DSSE have been devoted to obtaining a good tradeoff between security and performance. However, it...
journal article 2022
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Xie, Jiahong (author), Cheng, Haibo (author), Zhu, Rong (author), Wang, Ping (author), Liang, K. (author)
To date there are few researches on the semantic information of passwords, which leaves a gap preventing us from fully understanding the passwords characteristic and security. We propose a new password probability model for semantic information based on Markov Chain with both generalization and accuracy, called WordMarkov, that can capture the...
conference paper 2022
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Wang, Xingkai (author), Cao, Zhenfu (author), LIU, Z. (author), Liang, K. (author)
Gordon et al. (TCC 2015) systematically studied the security of Multi-client Verifiable Computation (MVC), in which a set of computationally-weak clients outsource the computation of a general function f over their private inputs to an untrusted server. They introduced the universally composable (UC) security of MVC and proposed a scheme...
conference paper 2022
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Zheng, Yubo (author), Xu, Peng (author), Wang, Wei (author), Chen, Tianyang (author), Susilo, Willy (author), Liang, K. (author), Jin, Hai (author)
Many practical secure systems have been designed to prevent real-world attacks via maximizing the attacking cost so as to reduce attack intentions. Inspired by this philosophy, we propose a new concept named delay encryption with keyword search (DEKS) to resist the notorious keyword guessing attack (KGA), in the context of secure cloud-based...
conference paper 2022
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Zhao, Zhendong (author), Chen, Xiaojun (author), Xuan, Yuexin (author), Dong, Ye (author), Wang, Dakui (author), Liang, K. (author)
Backdoor attack is a type of serious security threat to deep learning models. An adversary can provide users with a model trained on poisoned data to manipulate prediction behavior in test stage using a backdoor. The backdoored models behave normally on clean images, yet can be activated and output incorrect prediction if the input is stamped...
conference paper 2022
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He, Xiaoxi (author), Cheng, Haibo (author), Xie, Jiahong (author), Wang, Ping (author), Liang, K. (author)
Passwords have been widely used in online authentication, and they form the front line that protects our data security and privacy. But the security of password may be easily harmed by insecure password generator. Massive reports state that users are always keen to generate new passwords by reusing or fine-tuning old secrets. Once an old...
conference paper 2022
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Ning, Jianting (author), Huang, Xinyi (author), Susilo, Willy (author), Liang, K. (author), Liu, Ximeng (author), Zhang, Yinghui (author)
Cloud-based data storage service has drawn increasing interests from both academic and industry in the recent years due to its efficient and low cost management. Since it provides services in an open network, it is urgent for service providers to make use of secure data storage and sharing mechanism to ensure data confidentiality and service...
journal article 2022
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Xu, J. (author), Wang, R. (author), Koffas, S. (author), Liang, K. (author), Picek, S. (author)
Graph Neural Networks (GNNs) are a class of deep learning-based methods for processing graph domain information. GNNs have recently become a widely used graph analysis method due to their superior ability to learn representations for complex graph data. Due to privacy concerns and regulation restrictions, centralized GNNs can be difficult to...
conference paper 2022
Searched for: author%3A%22Liang%2C+K.%22
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