PICAndro: Packet InspeCtion-Based Android Malware Detection
The post-COVID epidemic world has increased dependence on online businesses for day-to-day life transactions over the Internet, especially using the smartphone or handheld devices. This increased dependence has led to new attack surfaces which need to be evaluated by security researchers. The large...
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Hindawi-Wiley
2021
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oai:doaj.org-article:8ca1d7ef3a2148bab217e53e964b5fa22021-11-22T01:10:29ZPICAndro: Packet InspeCtion-Based Android Malware Detection1939-012210.1155/2021/9099476https://doaj.org/article/8ca1d7ef3a2148bab217e53e964b5fa22021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/9099476https://doaj.org/toc/1939-0122The post-COVID epidemic world has increased dependence on online businesses for day-to-day life transactions over the Internet, especially using the smartphone or handheld devices. This increased dependence has led to new attack surfaces which need to be evaluated by security researchers. The large market share of Android attracts malware authors to launch more sophisticated malware (12000 per day). The need to detect them is becoming crucial. Therefore, in this paper, we propose PICAndro that can enhance the accuracy and the depth of malware detection and categorization using packet inspection of captured network traffic. The identified network interactions are represented as images, which are fed in the CNN engine. It shows improved performance with the accuracy of 99.12% and 98.91% for malware detection and malware class detection, respectively, with high precision.Vikas SihagGaurav ChoudharyManu VardhanPradeep SinghJung Taek SeoHindawi-WileyarticleTechnology (General)T1-995Science (General)Q1-390ENSecurity and Communication Networks, Vol 2021 (2021) |
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Technology (General) T1-995 Science (General) Q1-390 |
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Technology (General) T1-995 Science (General) Q1-390 Vikas Sihag Gaurav Choudhary Manu Vardhan Pradeep Singh Jung Taek Seo PICAndro: Packet InspeCtion-Based Android Malware Detection |
description |
The post-COVID epidemic world has increased dependence on online businesses for day-to-day life transactions over the Internet, especially using the smartphone or handheld devices. This increased dependence has led to new attack surfaces which need to be evaluated by security researchers. The large market share of Android attracts malware authors to launch more sophisticated malware (12000 per day). The need to detect them is becoming crucial. Therefore, in this paper, we propose PICAndro that can enhance the accuracy and the depth of malware detection and categorization using packet inspection of captured network traffic. The identified network interactions are represented as images, which are fed in the CNN engine. It shows improved performance with the accuracy of 99.12% and 98.91% for malware detection and malware class detection, respectively, with high precision. |
format |
article |
author |
Vikas Sihag Gaurav Choudhary Manu Vardhan Pradeep Singh Jung Taek Seo |
author_facet |
Vikas Sihag Gaurav Choudhary Manu Vardhan Pradeep Singh Jung Taek Seo |
author_sort |
Vikas Sihag |
title |
PICAndro: Packet InspeCtion-Based Android Malware Detection |
title_short |
PICAndro: Packet InspeCtion-Based Android Malware Detection |
title_full |
PICAndro: Packet InspeCtion-Based Android Malware Detection |
title_fullStr |
PICAndro: Packet InspeCtion-Based Android Malware Detection |
title_full_unstemmed |
PICAndro: Packet InspeCtion-Based Android Malware Detection |
title_sort |
picandro: packet inspection-based android malware detection |
publisher |
Hindawi-Wiley |
publishDate |
2021 |
url |
https://doaj.org/article/8ca1d7ef3a2148bab217e53e964b5fa2 |
work_keys_str_mv |
AT vikassihag picandropacketinspectionbasedandroidmalwaredetection AT gauravchoudhary picandropacketinspectionbasedandroidmalwaredetection AT manuvardhan picandropacketinspectionbasedandroidmalwaredetection AT pradeepsingh picandropacketinspectionbasedandroidmalwaredetection AT jungtaekseo picandropacketinspectionbasedandroidmalwaredetection |
_version_ |
1718418352913776640 |