شماره ركورد كنفرانس :
3297
عنوان مقاله :
A novel method to detect android malware using Locality Sensitive Hashing algorithms
پديدآورندگان :
Sayahi Ebrahim Department of Computer Science and Engineering and IT - Shiraz University , Hamzeh Ali Department of Computer Science and Engineering and IT - Shiraz University
كليدواژه :
(Random Forest (RF , ( Support Vector Machine (SVM , (k-nearest neighbor (KNN , Classifying , Android , Simhash , LSH
عنوان كنفرانس :
نوزدهمين سمپوزيوم بين المللي هوش مصنوعي و پردازش سيگنال
چكيده لاتين :
malware are programs which created to sabotage
a system or do some other malicious tasks. In this article, a new
method for classifying malware using a Locality Sensitive Hashing
algorithm called Simhash will be proposed. In this article, a hash
will be generated from specific parts of a file with the use of
Simhash algorithm and the bits of this hashes will be considered
as the features of the file. Finally, with the use of some of machine
learning algorithms, a model will be created from these features
and classifying is done using the model.