Computer or communication networks are so designed that they do not easily get disrupted under external attack and, moreover, these are easily reconstructed when they do get disrupted. These desirable properties of networks can be measured by various parameters such as connectivity, toughness, tenacity and rupture degree. Among these parameters, rupture degree is comparatively better parameter ...

In this article, a modeling process is defined to address challenges in analyzing attack scenarios and mitigating vulnerabilities in networked environments. Known system vulnerability data, system configuration data, and vulnerability scanner results are considered to create exploitation graphs (e-graphs) that are used to represent attack scenarios. Experiments carried out in a cluster computin...

The traditional parameter used as a measure of vulnerability of a network modeled by a graph with perfect nodes and edges that may fail is the edge connectivity λ. Of course , () p q K p λ = where p q ≤. In that case, failure of the network simply means that the surviving subgraph becomes disconnected upon the failure of individual edges. If, instead, failure of the network is defined to mean t...

Natural Disasters like hurricanes, floods or earthquakes can damage power grid devices and create cascading blackouts and islands. The nature of failure propagation and extent of damage is dependent on the structural features of the grid, which is different from that of random networks. This paper analyzes the structural vulnerability of real power grids to impending disasters and presents intu...

This paper aims at designing some data mining methods of evaluating the seismic vulnerability of regions in the built infrastructure. A supervised clustering methodology is employed, based on k-nearest neighbor graphs. Unlike other classification algorithms, the method has the advantage of taking into account any distribution of training instances and also data topology. For the particular prob...

In this paper, we study the impacts of non-Personal Identifiable Information (non-PII) on the privacy of graph data with attribute information (e.g., social networks data with users’ profiles (attributes)), namely Structure-Attribute Graph (SAG) data, both theoretically and empirically. Our main contributions are two-fold: (i) we conduct the first attribute-based anonymity analysis for SAG data...

The key contribution of this paper is to embed the analysis network in a framework based on mapping from input space whose elements are nodes graph or entire into an information probability distributions associated objects space. Specifically, node distribution its node-to-node distances and whole aggregation these distributions. In two proposed for analysis: Jensen-Shannon Wasserstein, respect...