Node similarity measures quantify how similar a pair of nodes are in a network. These
similarity measures turn out to be an important fundamental tool for many real world …

Adversarial social network analysis explores how social links can be altered or otherwise
manipulated to hinder unwanted information collection. To date, however, problems of this …

Centrality measures can rank nodes in a social network according to their importance.
However, in many cases, a node may want to avoid being highly ranked by such measures …

Centrality measures are the most commonly advocated social network analysis tools for
identifying leaders of covert organizations. While the literature has predominantly focused …

Social network analysis tools can infer various attributes just by scrutinizing one's
connections. Several researchers have studied the problem faced by an evader whose goal …

Attribute inference—the process of analyzing publicly available data in order to uncover
hidden information—has become a major threat to privacy, given the recent technological …

Group centrality measures are a generalization of standard centrality, designed to quantify
the importance of not just a single node (as is the case with standard measures) but rather …

Increasing terrorist activities globally have attracted the attention of many researchers, policy
makers and security agencies towards counterterrorism. The clandestine nature of terrorist …

Social networks arise as a result of complex interactions among people, and homophily
plays an important role in this process. If we view homophily as a dominant force in network …

In this thesis, we study the theory of parametrized complexity and examine parameterized
complexity of the Hiding Leader problem. We discuss standard tools and techniques for …