Zobrazeno 1 - 10
of 2 554
pro vyhledávání: '"Ma Jianfeng"'
Autor:
Ma Jianfeng, Gan Mailin, Yang Yitang, Chen Lei, Zhao Ye, Niu Lili, Wang Yan, Zhang Shunhua, Wang Jingyong, Zhu Li, Shen Linyuan
Publikováno v:
Scientific Data, Vol 10, Iss 1, Pp 1-10 (2023)
Abstract Intrauterine growth restriction (IUGR) impairs neonatal weight and causes multiple organ dysplasia. IUGR not only threatens human health but is also a significant constraint to the development of animal husbandry. However, the molecular mech
Externí odkaz:
https://doaj.org/article/2f146a252c4742949c9aa4136aac983b
Publikováno v:
Ceramics-Silikáty, Vol 65, Iss 2, Pp 176-186 (2021)
Ceramsite was sintered using coal gasification slag, fly ash, construction spoils, and municipal sludge. The influence of the municipal sludge content on the ceramsite performance was studied by TG-DSC, XRD, MIP, and SEM. The optimal sintering condit
Externí odkaz:
https://doaj.org/article/6edb2ab3ac7a467f8cf958d714195677
Metaverse is a vast virtual world parallel to the physical world, where the user acts as an avatar to enjoy various services that break through the temporal and spatial limitations of the physical world. Metaverse allows users to create arbitrary dig
Externí odkaz:
http://arxiv.org/abs/2409.10850
Autor:
WU Qixuan, MA Jianfeng, SUN Cong
Publikováno v:
网络与信息安全学报, Vol 5, Iss 2, Pp 50-57 (2019)
In order to avert the drawback of traditional information flow integrity analysis on ignoring the specific system architecture and associated attack events, an integrity threat tree to quantify the integrity of the system information flow, and the co
Externí odkaz:
https://doaj.org/article/372767669e5543799522325591fead5c
Memory corruption attacks (MCAs) refer to malicious behaviors of system intruders that modify the contents of a memory location to disrupt the normal operation of computing systems, causing leakage of sensitive data or perturbations to ongoing proces
Externí odkaz:
http://arxiv.org/abs/2309.05978
Autor:
Niu, Jun, Zhu, Xiaoyan, Zeng, Moxuan, Zhang, Ge, Zhao, Qingyang, Huang, Chunhui, Zhang, Yangming, An, Suyu, Wang, Yangzhong, Yue, Xinghui, He, Zhipeng, Guo, Weihao, Shen, Kuo, Liu, Peng, Shen, Yulong, Jiang, Xiaohong, Ma, Jianfeng, Zhang, Yuqing
Membership inference (MI) attacks threaten user privacy through determining if a given data example has been used to train a target model. However, it has been increasingly recognized that the "comparing different MI attacks" methodology used in the
Externí odkaz:
http://arxiv.org/abs/2307.06123
Federated Learning (FL) is a widely adopted privacy-preserving machine learning approach where private data remains local, enabling secure computations and the exchange of local model gradients between local clients and third-party parameter servers.
Externí odkaz:
http://arxiv.org/abs/2305.04095
Metaverse is a vast virtual environment parallel to the physical world in which users enjoy a variety of services acting as an avatar. To build a secure living habitat, it's vital to ensure the virtual-physical traceability that tracking a malicious
Externí odkaz:
http://arxiv.org/abs/2209.08893
Artificial intelligence and machine learning have been integrated into all aspects of our lives and the privacy of personal data has attracted more and more attention. Since the generation of the model needs to extract the effective information of th
Externí odkaz:
http://arxiv.org/abs/2202.05469
Backdoor injection attack is an emerging threat to the security of neural networks, however, there still exist limited effective defense methods against the attack. In this paper, we propose BAERASE, a novel method that can erase the backdoor injecte
Externí odkaz:
http://arxiv.org/abs/2201.09538