1 citations · 2 across the 3 of their papers we have counts for
6 papers
Machine-Learning Based Objective Function Selection for Community Detection
Asa Bornstein, Amir Rubin, Danny Hendler
NECTAR, a Node-centric ovErlapping Community deTection AlgoRithm, presented in 2016 by Cohen et. al, chooses dynamically between two objective functions which function to optimize,…
A Cycle Joining Construction of the Prefer-Max De Bruijn Sequence
Gal Amram, Amir Rubin, Gera Weiss
We propose a novel construction for the well-known prefer-max De Bruijn sequence, based on the cycle joining technique. We further show that the construction implies known results…
Modeling infection methods of computer malware in the presence of vaccinations using epidemiological models: An analysis of real-world data
Elad Yom-Tov, Nir Levy, Amir Rubin
Computer malware and biological pathogens often use similar mechanisms of infections. For this reason, it has been suggested to model malware spread using epidemiological models de…
AMSI-Based Detection of Malicious PowerShell Code Using Contextual Embeddings
Amir Rubin, Shay Kels, Danny Hendler
PowerShell is a command-line shell, supporting a scripting language. It is widely used in organizations for configuration management and task automation but is also increasingly us…
Detecting Malicious PowerShell Commands using Deep Neural Networks
Danny Hendler, Shay Kels, Amir Rubin
Microsoft's PowerShell is a command-line shell and scripting language that is installed by default on Windows machines. While PowerShell can be configured by administrators for res…
Node-Centric Detection of Overlapping Communities in Social Networks
Yehonatan Cohen, Danny Hendler, Amir Rubin
We present NECTAR, a community detection algorithm that generalizes Louvain method's local search heuristic for overlapping community structures. NECTAR chooses dynamically which o…