Emerging Information Security and Applications〈1st ed. 2024〉 : 4th International Conference, EISA 2023, Hangzhou, China, December 6–7, 2023, Proceedings

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Emerging Information Security and Applications〈1st ed. 2024〉 : 4th International Conference, EISA 2023, Hangzhou, China, December 6–7, 2023, Proceedings

  • 著者名:Shao, Jun (EDT)/Katsikas, Sokratis K. (EDT)/Meng, Weizhi (EDT)
  • 価格 ¥13,153 (本体¥11,958)
  • Springer(2024/01/03発売)
  • 春分の日の三連休!Kinoppy 電子書籍・電子洋書 全点ポイント30倍キャンペーン(~3/22)
  • ポイント 3,570pt (実際に付与されるポイントはご注文内容確認画面でご確認下さい)
  • 言語:ENG
  • ISBN:9789819996131
  • eISBN:9789819996148

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Description

This volume constitutes the proceedings presented at the 4th International Conference on Emerging Information Security and Applications, EISA 2023, held in Hangzhou, China, in December 2023. 

The 11 full papers presented in this volume were thoroughly reviewed and selected from the 35 submissions. The topics of the book are related but not limited  to cyber intelligence techniques, multimedia security, blockchain and distributed ledger technology, malware and unwanted software, vulnerability analysis and reverse engineering, usable security and privacy, intrusion detection and prevention, authentication and access control, anonymity and privacy, cryptographic protection, digital forensics, cyber physical systems security, adversarial learning, security measurement, security management and policies, hardware and physical security.

Table of Contents

PtbStolen: Pre-trained Encoder Stealing Through Perturbed Samples.- Towards Efficient Universal Adversarial Attack on Audio Classification Models: A Two-step Method.- Privacy-Preserving Authenticated Federated Learning Scheme for Smart Healthcare System.- A Systematic Method for Constructing ICT Supply Chain Security Requirements.- Pairing Compression on Some Elliptic Curves with Subgroups of Embedding Degree 6 and its Applications to Pairing-based Cryptography.- Enhancing Chinese Named Entity Recognition with Disentangled Expert Knowledge.- Deep Neural Network Model over Encrypted Data.- Privacy Protection Mechanism for Fair Federated Learning.- Chinese Named Entity Recognition within the Electric Power Domain.- Adversarial Sampling Attacks and Defense in DNS Data Exfiltration.- CONNECTION: COvert chaNnel NEtwork attaCk Through bIt-rate mOdulatioN.

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