BibTeX
@article{IJASEIT7191,
author = {Madihah Mohd Saudi and Amirul Adli Che Ismail and Azuan Ahmad and Muhammad ‘Afif Husainiamer},
title = {CallDetect: Detection of Call Log Exploitation Inspired by Apoptosis},
journal = {International Journal on Advanced Science, Engineering and Information Technology},
volume = {10},
number = {5},
year = {2020},
pages = {1792--1797},
keywords = {call log exploitation; API; mobile malware; static analysis; apoptosis.},
abstract = {Currently, we saw the increment trend of mobile application(app) exploitation that leads to loss of confidential information and money. Many malware camouflages itself as a genuine mobile app or exploits vulnerabilities inside mobile apps. Hence, this paper presents a mobile app called CallDetect that detects Android Application Interface (API) exploitation for call logs inspired by apoptosis. Apoptosis is known as cell-programmed death, and it is part of the human immunology system. Once it suspects any danger that might cause any harm to the human body, it will kill the suspected danger and itself. In the case of CallDetect, it will scan and uninstall the potentially malicious mobile application on a mobile phone. CallDetect consists of 13 new classifications of API call log, which are used as the database for CallDetect. These classifications were built by using static analysis and open source tools in a controlled lab environment. There were 5560 training datasets from Drebin and 550 anonymous testing dataset from Google Playstore. Our finding showed that 39 mobile apps, or 7%, were identified with possible call log exploitation. This paper can be used as a reference for call log API exploitation and can be further enhanced by integrating it with permission and system call exploitation.},
issn = {2088-5334},
publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},
url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=7191},
doi = {10.18517/ijaseit.10.5.7191}
}
EndNote
%A Mohd Saudi, Madihah
%A Che Ismail, Amirul Adli
%A Ahmad, Azuan
%A Husainiamer, Muhammad ‘Afif
%D 2020
%T CallDetect: Detection of Call Log Exploitation Inspired by Apoptosis
%B 2020
%9 call log exploitation; API; mobile malware; static analysis; apoptosis.
%! CallDetect: Detection of Call Log Exploitation Inspired by Apoptosis
%K call log exploitation; API; mobile malware; static analysis; apoptosis.
%X Currently, we saw the increment trend of mobile application(app) exploitation that leads to loss of confidential information and money. Many malware camouflages itself as a genuine mobile app or exploits vulnerabilities inside mobile apps. Hence, this paper presents a mobile app called CallDetect that detects Android Application Interface (API) exploitation for call logs inspired by apoptosis. Apoptosis is known as cell-programmed death, and it is part of the human immunology system. Once it suspects any danger that might cause any harm to the human body, it will kill the suspected danger and itself. In the case of CallDetect, it will scan and uninstall the potentially malicious mobile application on a mobile phone. CallDetect consists of 13 new classifications of API call log, which are used as the database for CallDetect. These classifications were built by using static analysis and open source tools in a controlled lab environment. There were 5560 training datasets from Drebin and 550 anonymous testing dataset from Google Playstore. Our finding showed that 39 mobile apps, or 7%, were identified with possible call log exploitation. This paper can be used as a reference for call log API exploitation and can be further enhanced by integrating it with permission and system call exploitation.
%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=7191
%R doi:10.18517/ijaseit.10.5.7191
%J International Journal on Advanced Science, Engineering and Information Technology
%V 10
%N 5
%@ 2088-5334
IEEE
Madihah Mohd Saudi,Amirul Adli Che Ismail,Azuan Ahmad and Muhammad ‘Afif Husainiamer,"CallDetect: Detection of Call Log Exploitation Inspired by Apoptosis," International Journal on Advanced Science, Engineering and Information Technology, vol. 10, no. 5, pp. 1792-1797, 2020. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.10.5.7191.
RefMan/ProCite (RIS)
TY - JOUR
AU - Mohd Saudi, Madihah
AU - Che Ismail, Amirul Adli
AU - Ahmad, Azuan
AU - Husainiamer, Muhammad ‘Afif
PY - 2020
TI - CallDetect: Detection of Call Log Exploitation Inspired by Apoptosis
JF - International Journal on Advanced Science, Engineering and Information Technology; Vol. 10 (2020) No. 5
Y2 - 2020
SP - 1792
EP - 1797
SN - 2088-5334
PB - INSIGHT - Indonesian Society for Knowledge and Human Development
KW - call log exploitation; API; mobile malware; static analysis; apoptosis.
N2 - Currently, we saw the increment trend of mobile application(app) exploitation that leads to loss of confidential information and money. Many malware camouflages itself as a genuine mobile app or exploits vulnerabilities inside mobile apps. Hence, this paper presents a mobile app called CallDetect that detects Android Application Interface (API) exploitation for call logs inspired by apoptosis. Apoptosis is known as cell-programmed death, and it is part of the human immunology system. Once it suspects any danger that might cause any harm to the human body, it will kill the suspected danger and itself. In the case of CallDetect, it will scan and uninstall the potentially malicious mobile application on a mobile phone. CallDetect consists of 13 new classifications of API call log, which are used as the database for CallDetect. These classifications were built by using static analysis and open source tools in a controlled lab environment. There were 5560 training datasets from Drebin and 550 anonymous testing dataset from Google Playstore. Our finding showed that 39 mobile apps, or 7%, were identified with possible call log exploitation. This paper can be used as a reference for call log API exploitation and can be further enhanced by integrating it with permission and system call exploitation.
UR - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=7191
DO - 10.18517/ijaseit.10.5.7191
RefWorks
RT Journal Article
ID 7191
A1 Mohd Saudi, Madihah
A1 Che Ismail, Amirul Adli
A1 Ahmad, Azuan
A1 Husainiamer, Muhammad ‘Afif
T1 CallDetect: Detection of Call Log Exploitation Inspired by Apoptosis
JF International Journal on Advanced Science, Engineering and Information Technology
VO 10
IS 5
YR 2020
SP 1792
OP 1797
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 call log exploitation; API; mobile malware; static analysis; apoptosis.
AB Currently, we saw the increment trend of mobile application(app) exploitation that leads to loss of confidential information and money. Many malware camouflages itself as a genuine mobile app or exploits vulnerabilities inside mobile apps. Hence, this paper presents a mobile app called CallDetect that detects Android Application Interface (API) exploitation for call logs inspired by apoptosis. Apoptosis is known as cell-programmed death, and it is part of the human immunology system. Once it suspects any danger that might cause any harm to the human body, it will kill the suspected danger and itself. In the case of CallDetect, it will scan and uninstall the potentially malicious mobile application on a mobile phone. CallDetect consists of 13 new classifications of API call log, which are used as the database for CallDetect. These classifications were built by using static analysis and open source tools in a controlled lab environment. There were 5560 training datasets from Drebin and 550 anonymous testing dataset from Google Playstore. Our finding showed that 39 mobile apps, or 7%, were identified with possible call log exploitation. This paper can be used as a reference for call log API exploitation and can be further enhanced by integrating it with permission and system call exploitation.
LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=7191
DO - 10.18517/ijaseit.10.5.7191
