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Titlebook: Information Security Practice and Experience; 16th International C Robert Deng,Feng Bao,Ding Wang Conference proceedings 2021 Springer Natu

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發(fā)表于 2025-3-21 16:54:01 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Information Security Practice and Experience
副標題16th International C
編輯Robert Deng,Feng Bao,Ding Wang
視頻videohttp://file.papertrans.cn/466/465323/465323.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Information Security Practice and Experience; 16th International C Robert Deng,Feng Bao,Ding Wang Conference proceedings 2021 Springer Natu
描述.This book constitutes the refereed proceedings of the 16th International Conference on Information Security Practice and Experience, ISPEC 2021, held in Nanjing, China, in December 2021...The 23 full papers presented in this volume were carefully reviewed and selected from 94 submissions. The conference focus on new information security technologies, including their applications and their integration with IT systems in various vertical sectors..
出版日期Conference proceedings 2021
關鍵詞access control; artificial intelligence; authentication; communication systems; computer hardware; comput
版次1
doihttps://doi.org/10.1007/978-3-030-93206-0
isbn_softcover978-3-030-93205-3
isbn_ebook978-3-030-93206-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2021
The information of publication is updating

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,Enhanced Mixup Training: a?Defense Method Against Membership Inference Attack,c-based inference methods to infer whether a particular data sample is in the training dataset of the target model. While several defenses have been proposed to mitigate privacy risks, they still suffer from some limitations: 1) Current defenses are limited to defend model-based attack and are still
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EPFSTO-ARIMA: Electric Power Forced Stochastic Optimization Predicting Based on ARIMA, especially for enterprise survival. Data poisoning attack is a typical attack faced by data sharing, EPSTO-ARIMA (Electric Power Stochastic Optimization Predicting Based on Autoregressive Integrated Moving Average model) would increase prediction error by generating adversarial shared data, which l
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,Message-Restriction-Free Commitment Scheme Based on?Lattice Assumption,t years, lattice-based cryptography has been intensively studied owing to its potential to be promising post-quantum cryptography. Therefore, the commitment schemes based on lattice assumption have been studied for practical applications. Typically, many applications require to commit arbitrary vect
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OblivShare: Towards Privacy-Preserving File Sharing with Oblivious Expiration Control,emand that their data is secure during the entire life cycle, and not residing in clouds indefinitely. A trending feature in industry is to set download constraints of shared files - a file can be downloaded for a restricted number of times and/or within a limited time framework. Metadata privacy be
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