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Science of Cyber Security: 5th International Conference, SciSec 2023, Melbourne, VIC, Australia, July 1114, 2023, Proceedings 1st ed. 2023 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 526 pages, height x width: 235x155 mm, weight: 819 g, 118 Illustrations, color; 46 Illustrations, black and white; XIV, 526 p. 164 illus., 118 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 14299
  • Izdošanas datums: 21-Nov-2023
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031459326
  • ISBN-13: 9783031459320
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  • Formāts: Paperback / softback, 526 pages, height x width: 235x155 mm, weight: 819 g, 118 Illustrations, color; 46 Illustrations, black and white; XIV, 526 p. 164 illus., 118 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 14299
  • Izdošanas datums: 21-Nov-2023
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031459326
  • ISBN-13: 9783031459320
Citas grāmatas par šo tēmu:

This book constitutes the refereed proceedings of the 5th International Conference on Science of Cyber Security, SciSec 2023, held in Melbourne, VIC, Australia, during July 11–14, 2023. 

The 21 full papers presented together with 6 short papers were carefully reviewed and selected from 60 submissions. The papers are organized in the topical sections named: ?ACDroid: Detecting Collusion Applications on Smart Devices; Almost Injective and Invertible Encodings for Jacobi Quartic Curves; Decompilation Based Deep Binary-Source Function Matching.
Session 1 Network and System Security.- ACDroid: Detecting Collusion
Applications on Smart Devices.- DomainIsolation: Lightweight Intra-enclave
Isolation for Confidential Virtual Machines.- Keeping Your Enemies Closer:
Shedding Light on the Attacker's Optimal Strategy.- Cyber Attacks against
Enterprise Networks: Characterization, Modelling and Forecasting.- Session 2
Cryptography and Authentication.- MCVDSSE: Secure Multi-Client Verifiable
Dynamic Symmetric Searchable Encryption.- A Graphical Password Scheme based
on Rounded Image Selection.- Implementation of the Elliptic Curve Method.-
Almost Injective and Invertible Encodings for Jacobi Quartic
Curves.- SeeStar: an Efficient Starlink Asset Detection
Framework.- Privacy-enhanced Anonymous and Deniable Post-Quantum
X3DH.- Session 3 AI for Security.- Fractional Dynamic: Analysis for Network
Malware Propagation.- Enhancing the Anti-steganalysis Ability via Multiple
Adversarial Network.- An Empirical study of AI models Performance for
Electricity Load Forecasting with Extreme Weather Conditions.- Session 4
Threat Detection and Analysis.- AST2Vec: A Robust Neural Code Representation
for Malicious PowerShell Detection.- Real-time Aggregation for Massive alerts
based on Dynamic Attack Granularity Graph.- Decompilation Based Deep
Binary-Source Function Matching.- Event-based Threat Intelligence Ontology
Model.- Session 5 Web and Privacy Security.- Optimally Blending Honeypots
into Production Networks: Hardness and Algorithms.- WebMea: A Google Chrome
Extension for Web Security and Privacy Measurement Studies.- Quantifying
Psychological Sophistication of Malicious Emails.- SVFL: Secure Vertical
Federated Learning on Linear Models.- Session 6: Cryptography and
Authentication II.- Multiprime Strategies for Serial Evaluation of eSIDH-Like
Isogenies.- Adaptively Secure Constrained Verifiable Random Function.- A
Robust Reversible Data Hiding Algorithm Based on Polar Harmonic Fourier
Moments.- Session 7: Advanced Threat Detection Techniques and
Blockchain.- VaultBox: Enhancing the Security and Effectiveness of Security
Analytics.- Two-stage Anomaly Detection in LEO Satellite Network.- Hydra: An
Efficient Asynchronous DAG-based BFT Protocol.- Redactable Blockchain in the
Permissioned Setting.- Session 8: Workshop Session.- A MULTI-LEVEL Sorting
Prediction Enhancement-based two-dimensional Reversible Data Hiding Algorithm
for Jpeg Images.- Research on Encrypted Malicious 5G Access Network Traffic
identification based on Deep Learning.- A Design of Network Attack Detection
Using Causal and Non-causal Temporal Convolutional.