Context-based anomaly tracking represents a new approach to security enhancement of
communication streams. By creating a system that develops an understanding of normal and …

In view of the imbalance of abnormal data in social networks, the bandwidth value of
detection algorithm is high. To solve this problem, a real-time anomaly detection algorithm …

Online Social Networks as new phenomenon have affected our life in many positive ways;
however it can be considered as way of malicious activities. Identifying anomalous users …

Network behavior anomaly detection is an effective approach to discover unknown attacks,
where generating high‐efficacy network behavior representation is one of the most crucial …

Random anomalous behavior is a false or redundant behavior that randomly appears in the
network structure, affecting the analysis result of the network. Current methods mainly …

With the recent advances in Internet technology, various aspects of the human lifestyle are
influenced by the digital world. Users join social networks to communicate and perform their …

The problem of the network security is taken up since eighties (Denning et al., 1987) and is
developed up today (Beltilch et al., 2004, Bera, 2010, Dasgupta, 1999, Basile, 2007, Wilson …

The advent of online social media including Facebook, Twitter, Flickr and Youtube has
drawn massive attention in recent years. These online platforms generate massive data …

Many real-world systems, including social media, molecular networks, and payment
transaction networks, can be modeled as graphs. On these networked systems, there exist …

This research is a step forward in improving the accuracy of detecting anomaly in a data
graph representing connectivity between people in an online social network. The proposed …