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
سال انتشار :
آبان 1396
عنوان كنفرانس :
نوزدهمين سمپوزيوم بين المللي هوش مصنوعي و پردازش سيگنال
زبان مدرك :
لاتين
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.
كشور :
ايران
تعداد صفحه 2 :
6
از صفحه :
1
تا صفحه :
6
لينک به اين مدرک :
بازگشت