—Traditional approaches to K-anonymity provide privacy guarantees over publicly released data sets with specified quasi-identifiers. However, the most common public releases of...
Machine learning has great utility within the context of network intrusion detection systems. In this paper, a behavior analysis-based learning framework for host level network in...
Haiyan Qiao, Jianfeng Peng, Chuan Feng, Jerzy W. R...
We carry out a comprehensive study of long-range interactions on a large data set of non-homologous proteins. Our study reveals that the long-range interactions between amino acid...
This paper deals with the problem of structuralizing education and training videos for high-level semantics extraction and nonlinear media presentation in e-learning applications....
Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication t...