This two-volume set LNICST 398 and 399 constitutes the post-conference proceedings of the 17
th International Conference on Security and Privacy in Communication Networks, SecureComm 2021, held in September 2021. Due to COVID-19 pandemic the conference was held virtually.
The 56 full papers were carefully reviewed and selected from 143 submissions. The papers focus on the latest scientific research results in security and privacy in wired, mobile, hybrid and ad hoc networks, in IoT technologies, in cyber-physical systems, in next-generation communication systems in web and systems security and in pervasive and ubiquitous computing.
Reihe
Auflage
Sprache
Verlagsort
Verlagsgruppe
Springer International Publishing
Zielgruppe
Illustrationen
96
42 s/w Abbildungen, 96 farbige Abbildungen
XVII, 527 p. 138 illus., 96 illus. in color.
Maße
Höhe: 235 mm
Breite: 155 mm
Dicke: 30 mm
Gewicht
ISBN-13
978-3-030-90021-2 (9783030900212)
DOI
10.1007/978-3-030-90022-9
Schweitzer Klassifikation
Anonymous Short Communications over Social Networks.- A Sybil detection method in OSN based on DistilBERT and Double-SN-LSTM for text analysis.- ePayment Security 31 An Empirical Study on Mobile Payment Credential Leaks and Their Exploits.- System-Wide Security for Offline Payment Terminals.- Horus: A Security Assessment Framework for Android Crypto Wallets.- Systems Security.- Leakuidator: Leaky resource attacks and countermeasures.- Jabbic lookups: a backend telemetry-based system for malware triage Octavian.- Facilitating Parallel Fuzzing with Mutually-exclusive Task Distribution.- Flowrider: Fast On-Demand Key Provisioning for CloudNetworks.- Mobile Security & Privacy.- Mobile Handset Privacy: Measuring The Data iOS and Android Send to Apple And Google Douglas Leith.- Who's Accessing My Data? Application-Level Access Control for Bluetooth Low Energy.- HTPD: Secure and Flexible Message-Based Communication for Mobile Apps.- Smartphone Location Spoofing Attack in Wireless Networks.- IoT Security & Privacy 42 Compromised through Compression.- iDDAF: An Intelligent Deceptive Data Acquisition Framework for Secure Cyber-physical Systems.
