Articles

On one hand, Network Intrusion Detection Systems (NIDS) that are based on machine learning sometimes demand important domain expertise and experimentation. That makes performance be suboptimal in complex network environments. On other hand deep learning although its power can hardly deal with imbalanced data. That results in a bias towards normal traffic and reduced effectiveness […]

Applications of multimedia data deal more with security and privacy of video content since they are spreading in cloud computing environments. Encryption methods are limited because even if they can protect video content, they hardly succeed in balancing codec compatibility and security. And when they succeed, they impact video processing speed. To address this issue, […]

It is obvious to say that we should fight against fake news. Methods have been developed. Most of them are time consuming since they use large amounts of annotated data, and are mainly supervised. To address this problem, some researchers proposed a novel unsupervised fake news detection framework based on structural contrastive learning by combining […]

Fully homomorphic encryption (FHE) has experienced significant development and continuous breakthroughs in theory, enabling its widespread application in various fields, like outsourcing computation and secure multi-party computing, in order to preserve privacy. Nonetheless, the application of FHE is constrained by its substantial computing overhead and storage cost. Researchers have proposed practical acceleration solutions to address […]

However Attribute-based encryption (ABE) scheme supports users to acquire access authorization through collaborative works, it meets its limits when it is necessary to consider the different weights of collaboration users.  Revocable and verifiable weighted attribute-based encryption with collaborative access scheme (RVWABE-CA) may reach this step. Indeed, according to the authors, RVWABE-CA) can provide efficient weighted multi-user […]

The handy biometric data is a double-edged sword, paving the way of the prosperity of biometric authentication systems but bringing the personal privacy concern. To alleviate the concern, various biometric template protection schemes are proposed to protect the biometric template from information leakage. The preponderance of existing proposals is based on Hamming metric, which ignores […]

Deep learning models are well known to be susceptible to backdoor attack, where the attacker only needs to provide a tampered dataset on which the triggers are injected. Models trained on the dataset will passively implant the backdoor, and triggers on the input can mislead the models during testing. Our study shows that the model […]

This research critically reviews the definition of confidential computing (CC) and the security comparison of CC with other related technologies by the Confidential Computing Consortium (CCC). We demonstrate that the definitions by CCC are ambiguous, incomplete and even conflicting. We also demonstrate that the security comparison of CC with other technologies is neither scientific nor […]

With the advancement of communication technology, a large number of data are constantly transmitted through the internet for various purposes, which are prone to be illegally accessed by third parties. Therefore, securing such data is crucial to protect the transmitted information from falling into the wrong hands. Among data protection schemes, Secret Image Sharing is […]

Sharing PII is extremely useful in public affairs yet hard to implement due to the worries about privacy violations. Building a PII retrieval service over multi-cloud, which is a modern strategy to make services stable where multiple servers are deployed, seems to be a promising solution. However, three major technical challenges remain to be solved. […]