Android Malware Classification by Applying Online Machine Learning
| Autor: | Tankut Acarman, Mahmut Çavdar, Abdurrahman Pektaş |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
021110 strategic
defence & security studies Software_OPERATINGSYSTEMS business.product_category Computer science business.industry 0211 other engineering and technologies Online machine learning 02 engineering and technology computer.software_genre Machine learning ComputingMilieux_MANAGEMENTOFCOMPUTINGANDINFORMATIONSYSTEMS ComputingMethodologies_PATTERNRECOGNITION Android malware 0202 electrical engineering electronic engineering information engineering Internet access Classification methods Malware 020201 artificial intelligence & image processing Android application Artificial intelligence Android (operating system) business computer |
| Zdroj: | Communications in Computer and Information Science ISBN: 9783319472164 ISCIS |
| Popis: | A malware is deployed to execute malicious activities in the compromised operating systems. The widespread use of android smart-phones with high speed Internet and permissions granted to applications for accessing internal logs provides a favorable environment for the execution of unauthorized and malicious activities. The major risk and challenge lies along classification of a large volume and variety of malware. A malware may evolve and continue to hide its malicious activies against security systems. Knowing malware features a priori and classification of a malware plays a crucial role at defending the safety and liability critical user's information. In this paper, we study android malware activities, features and apply online machine learning algorithm to classify a new android malware. We extract a fairly adequate set of malware features and we evaluate a machine learning based classification method. The runtime model is built and it can be implemented to detect variants of an android malware. The metrics illustrate the effectiveness of the proposed classification method. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|