Polonium: Tera-Scale Graph Mining and Inference for Malware Detection
By Duen Horng, Polo Chau, Carey Nachenberg, Jeffrey Wilhelm, Christos Faloutsos. 2011
153 citations recorded by the source corpus.
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Yizheng Chen
- Manos Antonakakis
- Roberto Perdisci
- Yacin Nadji
- Fabian Monrose
- Athanasios Kountouras
- Nikolaos Vasiloglou
- Acar Tamersoy
Citations in the corpus
- Attacking Graph-based Classification via Manipulating the Graph Structure (2019, methodology): “Graph-based classification methods have been widely applied to various security problems such as malware detection [14, 59], fraudulent user detection in social networks [10, 25, 36, 67, 68, 72, 74], fake review detection [1, 65], auction fraud detection [47], APT infection detection [46], and attri”
- Practical Attacks Against Graph-based Clustering (2017, methodology): “Beyond clustering, other graph-based techniques are used, such as belief propagation [18, 46].”
- Guilt by association: large scale malware detection by mining file-relation graphs (2014, methodology): “Symantec’s endpoint security products already incorporate many tiers of defence, including traditional Anti-Virus protection, Intrusion Detection, Behavioral Protection, and Insight, of which Polonium’s [7] machine-hygiene-based scores are a key component.”