Cyberspace Safety and Security

13th International Symposium, CSS 2021, Virtual Event, November 9–11, 2021, Proceedings

AvWeizhi Meng,Mauro Conti

Häftad, Engelska, 2022

Del 13172 i serien Lecture Notes in Computer Science

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Beskrivning

The LNCS 13172 constitute the proceedings of the 13th International Symposium on Cyberspace Safety and Security, CSS 2021, held online, in November 2021.The 9 full papers and 5 short papers presented in this book were carefully reviewed and selected from 35 submissions. The conference focuses on Cyberspace Safety and Security, such as authentication, access control, availability, integrity, privacy, confidentiality, dependability and sustainability issues of cyberspace.

Produktinformation

Utgivningsdatum:2022-01-12
Mått:155 x 235 x 13 mm
Vikt:353 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:217
Förlag:Springer Nature Switzerland AG
ISBN:9783030940287

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Nätverk och kommunikation inom Data och IT
Databaser inom Data och IT

Innehållsförteckning

Encrypted Malicious Traffic Detection Based on Ensemble Learning.- A Federated Learning Assisted Conditional Privacy Preserving Scheme for Vehicle Networks.- Dissecting Membership Inference Risk in Machine Learning.- Webshell Detection Based on Explicit Duration Recurrent Network.- A Practical Botnet Traffic Detection System using GNN.- Vulnerability and Transaction behavior based detection of Malicious Smart Contracts.- A novel method of template protection and two-factor authentication protocol based on biometric and PUF.- Realizing Information Flow Control in ABAC Mining.- Weak Password Scanning System for Penetration Testing.- Environmental Adaptive Privacy Preserving Contact Tracing System for Respiratory Infectious Diseases.- A Privacy-Preserving Logistics Information System with Traceability.- Post-quantum Key Escrow for Supervised Secret Data Sharing on Consortium Blockchain.- Flexible and Survivable Single Sign-On.- The Analysis and Implication of Data Deduplication in Digital Forensics.

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