The Concept Drift Problem in Android Malware Detection and Its Solution
المؤلفون المشاركون
Hu, Donghui
Ma, Zhongjin
Zhang, Xiaotian
Li, Peipei
Ye, Dengpan
Ling, Baohong
المصدر
Security and Communication Networks
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-09-18
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
Currently, the Android platform is the most popular mobile platform in the world and holds a dominant share in the mobile device market.
With the popularization of the Android platform, large numbers of Android malware programs have begun to emerge on the Internet, and the sophistication of these programs is developing rapidly.
While many studies have already investigated Android malware detection through machine learning and have achieved good results, most of these are based on static data sources and fail to consider the concept drift problem resulting from the rapid growth in the number of Android malware programs and normal Android applications, as well as rapid technological advancement in the Android environment.
To address this problem, this work proposes a solution based on an ensemble classifier.
This ensemble classifier is based on a streaming data-based Naive Bayes classifier.
Android malware has identifiable feature utilization tendencies.
On this basis, feature selection algorithm is introduced into the ensemble classifier, and a sliding window is maintained inside the ensemble classifier.
Based on the performance of the subclassifiers inside the sliding window, the ensemble classifier makes dynamic adjustments to address the concept drift problem in Android malware detection.
The experimental results from the proposed method demonstrate that it can effectively address the concept drift problem in Android malware detection in a streaming data environment.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Hu, Donghui& Ma, Zhongjin& Zhang, Xiaotian& Li, Peipei& Ye, Dengpan& Ling, Baohong. 2017. The Concept Drift Problem in Android Malware Detection and Its Solution. Security and Communication Networks،Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1202950
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Hu, Donghui…[et al.]. The Concept Drift Problem in Android Malware Detection and Its Solution. Security and Communication Networks No. 2017 (2017), pp.1-13.
https://search.emarefa.net/detail/BIM-1202950
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Hu, Donghui& Ma, Zhongjin& Zhang, Xiaotian& Li, Peipei& Ye, Dengpan& Ling, Baohong. The Concept Drift Problem in Android Malware Detection and Its Solution. Security and Communication Networks. 2017. Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1202950
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1202950
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر