4 papers
Multi-feature Dataset for Windows PE Malware Classification
Muhammad Irfan Yousuf, Izza Anwer, Tanzeela Shakir +2
This paper describes a multi-feature dataset for training machine learning classifiers for detecting malicious Windows Portable Executable (PE) files. The dataset includes four fea…
An Empirical Study of Compression-friendly Community Detection Methods
Muhammad Irfan Yousuf, Izza Anwer, Muhammad Abid
Real-world graphs are massive in size and we need a huge amount of space to store them. Graph compression allows us to compress a graph so that we need a lesser number of bits per…
Empirical Characterization of Graph Sampling Algorithms
Muhammad Irfan Yousuf, Izza Anwer, Raheel Anwar
Graph sampling allows mining a small representative subgraph from a big graph. Sampling algorithms deploy different strategies to replicate the properties of a given graph in the s…
Weighted Edge Sampling for Static Graphs
Muhammad Irfan Yousuf, Raheel Anwar
Graph Sampling provides an efficient yet inexpensive solution for analyzing large graphs. While extracting small representative subgraphs from large graphs, the challenge is to cap…