6 citations · 12 across the 10 of their papers we have counts for
11 papers
A Comprehensive Overview of Backdoor Attacks in Large Language Models within Communication Networks
Haomiao Yang, Kunlan Xiang, Mengyu Ge +3
The Large Language Models (LLMs) are poised to offer efficient and intelligent services for future mobile communication networks, owing to their exceptional capabilities in languag…
Efficiency Boosting of Secure Cross-platform Recommender Systems over Sparse Data
Hao Ren, Guowen Xu, Tianwei Zhang +4
Fueled by its successful commercialization, the recommender system (RS) has gained widespread attention. However, as the training data fed into the RS models are often highly sensi…
New Secure Sparse Inner Product with Applications to Machine Learning
Guowen Xu, Shengmin Xu, Jianting Ning +4
Sparse inner product (SIP) has the attractive property of overhead being dominated by the intersection of inputs between parties, independent of the actual input size. It has intri…
Deep Learning for Encrypted Traffic Classification and Unknown Data Detection
Madushi H. Pathmaperuma, Yogachandran Rahulamathavan, Safak Dogan +2
Despite the widespread use of encryption techniques to provide confidentiality over Internet communications, mobile device users are still susceptible to privacy and security risks…
Achieve Efficient Position-Heap-based Privacy-Preserving Substring-of-Keyword Query over Cloud
Fan Yin, Rongxing Lu, Yandong Zheng +3
The cloud computing technique, which was initially used to mitigate the explosive growth of data, has been required to take both data privacy and users' query functionality into co…
Spatial Interpolation-based Learned Index for Range and kNN Queries
Songnian Zhang, Suprio Ray, Rongxing Lu +1
A corpus of recent work has revealed that the learned index can improve query performance while reducing the storage overhead. It potentially offers an opportunity to address the s…
Improved Fault Analysis on SIMECK Ciphers
Duc-Phong Le, Rongxing Lu, Ali A. Ghorbani
The advances of the Internet of Things (IoT) have had a fundamental impact and influence in sharping our rich living experiences. However, since IoT devices are usually resource-co…
Scalar Product Lattice Computation for Efficient Privacy-preserving Systems
Yogachandran Rahulamathavan, Safak Dogan, Xiyu Shi +3
Privacy-preserving applications allow users to perform on-line daily actions without leaking sensitive information. Privacy-preserving scalar product is one of the critical algorit…
An Accuracy-Lossless Perturbation Method for Defending Privacy Attacks in Federated Learning
Xue Yang, Yan Feng, Weijun Fang +4
Although federated learning improves privacy of training data by exchanging local gradients or parameters rather than raw data, the adversary still can leverage local gradients and…
An Efficient Fog-Assisted Unstable Sensor Detection Scheme with Privacy Preserved
Shuo Chen, Rongxing Lu, Jie Zhang
The Internet of Thing (IoT) has been a hot topic in both research community and industry. It is anticipated that in future IoT, an enormous number of sensors will collect the physi…
A Flexible Privacy-preserving Framework for Singular Value Decomposition under Internet of Things Environment
Shuo Chen, Rongxing Lu, Jie Zhang
The singular value decomposition (SVD) is a widely used matrix factorization tool which underlies plenty of useful applications, e.g. recommendation system, abnormal detection and…