… accuracy in the judgment process of malicious activity detection. … complete algorithm, to
analyze the user behaviors and feed the re… to assess user profiles and detect malicious users. …

… of malicious HTTP redirection chains. In uncovering such malicious chains, we build a per-user
browsing activity tree… trees of related browsing activities on a per use basis. We focus our …

… In the work of [22], a more sophisticated deep learning architecture along with feature
extraction techniques to detect malicious users in Dianping, a location-based social network, was …

… For this reason, we have focussed on deriving suitable features from user activity profiles,
so that if an anomaly is detected then this has a meaningful context. This also provokes a …

… malicious user detection framework called GitSec. GitSec makes use of both the descriptive
data and the fine-grained activity … legitimate and malicious users in developer communities. …

… to detect malicious users even when there is minimum information available. In this paper,
we aim to detect malicious users … We introduce the first methodology to detect malicious users …

… accounts across the OSN taking into account vulnerable user uncountable shared posts in
a … activity and behaviors. The research emphasizes detecting malicious users that are users …

… to classify the interest categories of certified users and users, precisions of 80% and 79.8% …
users with less likelihood of malicious activities based on the information posted by the user…

… which use these outlier factors to detect the malicious users present in the system. In Section
V, we propose malicious user detection technique which takes into consideration the users’ …

… Social network analysis involves analyzing the topological social structure of the accounts
within the network or extracting discriminative network features to detect malicious users. …