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Malware Detection with Confidence Guarantees on Android Devices
Malware Detection with Confidence Guarantees on Android Devices
- Source :
- IFIP Advances in Information and Communication Technology ISBN: 9783319449432, AIAI
- Publication Year :
- 2016
- Publisher :
- Springer International Publishing, 2016.
-
Abstract
- The evolution of ubiquitous smartphone devices has given rise to great opportunities with respect to the development of applications and services, many of which rely on sensitive user information. This explosion on the demand of smartphone applications has made them attractive to cybercriminals that develop mobile malware to gain access to sensitive data stored on smartphone devices. Traditional mobile malware detection approaches that can be roughly classified to signature-based and heuristic-based have essential drawbacks. The former rely on existing malware signatures and therefore cannot detect zero-day malware and the latter are prone to false positive detections. In this paper, we propose a heuristic-based approach that quantifies the uncertainty involved in each malware detection. In particular, our approach is based on a novel machine learning framework, called Conformal Prediction, for providing valid measures of confidence for each individual prediction, combined with a Multilayer Perceptron. Our experimental results on a real Android device demonstrate the empirical validity and both the informational and computational efficiency of our approach.
- Subjects :
- User information
Computer science
business.industry
02 engineering and technology
Smartphone application
computer.software_genre
Machine learning
Computer security
01 natural sciences
Mobile malware
010104 statistics & probability
Empirical validity
Multilayer perceptron
0202 electrical engineering, electronic engineering, information engineering
Malware
020201 artificial intelligence & image processing
Artificial intelligence
0101 mathematics
Android (operating system)
Android device
business
computer
Subjects
Details
- ISBN :
- 978-3-319-44943-2
- ISBNs :
- 9783319449432
- Database :
- OpenAIRE
- Journal :
- IFIP Advances in Information and Communication Technology ISBN: 9783319449432, AIAI
- Accession number :
- edsair.doi...........3425ad3e325de31e27f8417ea0795be6
- Full Text :
- https://doi.org/10.1007/978-3-319-44944-9_35