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Classification of various attacks and their defence mechanism in online social networks: a survey
SR Sahoo, BB Gupta - Enterprise Information Systems, 2019 - Taylor & Francis
Due to the popularity and user friendliness of the Internet, numbers of users of online social
networks (OSNs) and social media have grown significantly. However, globally utilised …
networks (OSNs) and social media have grown significantly. However, globally utilised …
Learn to be efficient: Build structured sparsity in large language models
Abstract Large Language Models (LLMs) have achieved remarkable success with their
billion-level parameters, yet they incur high inference overheads. The emergence of …
billion-level parameters, yet they incur high inference overheads. The emergence of …
Mush: Multi-stimuli hawkes process based sybil attacker detector for user-review social networks
User-Review Social Networks (URSNs) now become the targets of Sybil attacks, where fake
reviews are posted by attackers to raise the reputation of listed services or products. Unlike …
reviews are posted by attackers to raise the reputation of listed services or products. Unlike …
DatingSec: Detecting malicious accounts in dating apps using a content-based attention network
Dating apps have gained tremendous popularity during the past decade. Compared with
traditional offline dating means, dating apps ease the process of partner finding significantly …
traditional offline dating means, dating apps ease the process of partner finding significantly …
DeepScan: Exploiting deep learning for malicious account detection in location-based social networks
Our daily lives have been immersed in widespread location-based social networks (LBSNs).
As an open platform, LBSNs typically allow all kinds of users to register accounts. Malicious …
As an open platform, LBSNs typically allow all kinds of users to register accounts. Malicious …