Zobrazeno 1 - 10
of 161
pro vyhledávání: '"Shengshan Hu"'
Publikováno v:
IEEE Transactions on Parallel and Distributed Systems. 32:786-798
Proofs of retrievability and proofs of replication are two cryptographic tools that enable a remote server to prove that the users’ data has been correctly stored. Nevertheless, the literature either requires the users themselves to perform expensi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::65464d25e90e6e0157747de6130bfe69
https://doi.org/10.1109/tpds.2020.3030063
https://doi.org/10.1109/tpds.2020.3030063
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
While deep face recognition (FR) systems have shown amazing performance in identification and verification, they also arouse privacy concerns for their excessive surveillance on users, especially for public face images widely spread on social network
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::44617c0ef68c4dfe77a81824b4493fc3
https://doi.org/10.1109/cvpr52688.2022.01459
https://doi.org/10.1109/cvpr52688.2022.01459
The usage of deep learning is being escalated in many applications. Due to its outstanding performance, it is being used in a variety of security and privacy-sensitive areas in addition to conventional applications. One of the key aspects of deep lea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3175eff58d85544c315c333079780ab2
http://arxiv.org/abs/2205.06986
http://arxiv.org/abs/2205.06986
Fine-tuning attacks are effective in removing the embedded watermarks in deep learning models. However, when the source data is unavailable, it is challenging to just erase the watermark without jeopardizing the model performance. In this context, we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ebe587d0fa4d66384fbf8aa668a00532
Publikováno v:
CCS
Deep neural networks (DNNs) are vulnerable to adversarial attacks. A great effort has been directed to developing effective defenses against adversarial attacks and finding vulnerabilities of proposed defenses. A recently proposed defense called Trap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::942ad8063f96dfe18ca3b56f795f84de
https://doi.org/10.1145/3460120.3485378
https://doi.org/10.1145/3460120.3485378
Publikováno v:
ACM Multimedia
In this paper, we propose AdvHash, the first targeted mismatch attack on deep hashing through adversarial patch. After superimposed with the same adversarial patch, any query image with a chosen label will retrieve a set of irrelevant images with the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c33064583705527cfb4b7954b1b927af
https://doi.org/10.1145/3474085.3475396
https://doi.org/10.1145/3474085.3475396
Publikováno v:
IEEE Wireless Communications. 26:128-133
Autonomous driving is becoming one of the most popular applications of AI. Meanwhile, the advances in deep learning have promoted the rapid development of the voice controllable systems (VCSs), which have almost reached the maturity stage. Before aut
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::513bb7bb1e87b7812b00cf91686d1bd8
https://doi.org/10.1109/mwc.2019.1800477
https://doi.org/10.1109/mwc.2019.1800477
Publikováno v:
IEEE Communications Magazine. 57:120-126
Speech is a common and effective approach for communication between humans and modern mobile devices such as smartphones or home hubs. The remarkable advances in computing and networking have popularized automatic speech recognition (ASR) systems, wh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4354675d6998adda86397486b7cc801d
https://doi.org/10.1109/mcom.2019.1900006
https://doi.org/10.1109/mcom.2019.1900006
Publikováno v:
WCNC
Federated learning (FL) is a newly emerging distributed learning framework that is communication-efficient with user privacy guarantee. Wireless end-user devices can collaboratively train a global model while keeping their local training data private
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::617d5bc582132f376aac4f0f3130c146
https://doi.org/10.1109/wcnc49053.2021.9417334
https://doi.org/10.1109/wcnc49053.2021.9417334
Recently emerged federated learning (FL) is an attractive distributed learning framework in which numerous wireless end-user devices can train a global model with the data remained autochthonous. Compared with the traditional machine learning framewo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e9d68f9032e03bb24c5765f65fc3bc15