Dataset Information

Data on Vulnerability Detection in Android.

ABSTRACT: The data in this article have been collaborated from mainly four sources- Google Playstore, Wandoujia (third party app store market), AMD and Androzoo. These data include ~85,000 APKs (Android Package Kit), both malicious and benign from these data sources. Static and dynamic features are extracted from these APK files, and then supervised machines learning algorithms are employed for malware detection in Android. This data article also provides the Python code for data analysis. For feature extraction, a generic algorithm has also been incorporated, thereby, selecting important and relevant feature subset. Conclusive results obtained from this data set are further comprehended and interpreted in our latest research study "A Novel Parallel Classifier Scheme for Vulnerability Detection in Android" (Garg et al., 2018). This proved to be precious contribution for ensembling classifiers in machine learning to detect malware in Android.

SUBMITTER: Garg S

PROVIDER: S-EPMC6377051 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Data on Vulnerability Detection in Android.

Garg Shivi S Baliyan Niyati N

Data in brief 20181215

The data in this article have been collaborated from mainly four sources- Google Playstore, Wandoujia (third party app store market), AMD and Androzoo. These data include ~85,000 APKs (Android Package Kit), both malicious and benign from these data sources. Static and dynamic features are extracted from these APK files, and then supervised machines learning algorithms are employed for malware detection in Android. This data article also provides the Python code for data analysis. For feature ext ...[more]

PMID: 30815521

Similar Datasets

Project description:BACKGROUND:Infectious diseases often lead to death among children under 5 years in many underdeveloped and developing countries. One of the main reasons behind this is an unawareness of disease symptoms among mothers and child caregivers. To overcome this, we propose the EasyDetectDisease mobile health app to educate mothers about the early symptoms of pediatric diseases and to provide them with practical advice for preventing the spread of such diseases in children under 5 years. The EasyDetectDisease app includes detailed knowledge of infectious diseases, including the corresponding symptoms, causes, incubation period, preventive measures, nutritional guidelines such as breastfeeding, video tutorials of child patients, and video guidelines by pediatric health experts to promote child health. It also provides information on the diagnosis of the infectious diseases based on symptoms. OBJECTIVE:The objective of this study was to evaluate the usability (eg, ease of use, easy detection of disease, functionality, and navigation of interfaces) of the EasyDetectDisease app among mothers of children under 5 years of age. METHODS:Two health sessions, held in Pakistan, were used to evaluate the usability of EasyDetectDisease by 30 mothers of children under 5 years. The app was evaluated based on various quantitative and qualitative measures. RESULTS:The participating mothers confirmed that they were able to diagnose diseases accurately and that after following the instructions provided, their children recovered rapidly without any nutritional deficiency. All participating mothers showed an interest in using the EasyDetectDisease app if made available by governmental public health agencies, and they suggested its inclusion in all mobile phones as a built-in health app in the future. CONCLUSIONS:EasyDetectDisease was modified into a user-friendly app based on feedback collected during the usability sessions. All participants found it acceptable and easy to use, especially illiterate mothers. The EasyDetectDisease app proved to be a useful tool for child health care at home and for the treatment of infectious diseases and is expected to reduce the mortality rate of children under 5 years of age.

Dataset Information

Data on Vulnerability Detection in Android.

Publications

Data on Vulnerability Detection in Android.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets