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Call Graph and Model Checking for Fine-Grained Android Malicious Behaviour Detection

Detecting Colluding Inter-App Communication in Mobile Environment

Department of Biosciences and Territory, University of Molise, 86090 Pesche, Italy
Institute for Informatics and Telematics, National Research Council of Italy, 56124 Pisa, Italy
Department of Medicine and Health Sciences “Vincenzo Tiberio”, University of Molise, 86100 Campobasso, Italy
Authors to whom correspondence should be addressed.
All authors contributed equally to this work.
Appl. Sci. 2020, 10(23), 8351;
Received: 30 September 2020 / Revised: 5 November 2020 / Accepted: 16 November 2020 / Published: 24 November 2020
(This article belongs to the Special Issue Cybersecurity)
The increase in computing capabilities of mobile devices has, in the last few years, made possible a plethora of complex operations performed from smartphones and tablets end users, for instance, from a bank transfer to the full management of home automation. Clearly, in this context, the detection of malicious applications is a critical and challenging task, especially considering that the user is often totally unaware of the behavior of the applications installed on their device. In this paper, we propose a method to detect inter-app communication i.e., a colluding communication between different applications with data support to silently exfiltrate sensitive and private information. We based the proposed method on model checking, by representing Android applications in terms of automata and by proposing a set of logic properties to reduce the number of comparisons and a set of logic properties automatically generated for detecting colluding applications. We evaluated the proposed method on a set of 1092 Android applications, including different colluding attacks, by obtaining an accuracy of 1, showing the effectiveness of the proposed method. View Full-Text
Keywords: colluding; malware; model checking; formal methods; security; Android; mobile colluding; malware; model checking; formal methods; security; Android; mobile
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MDPI and ACS Style

Casolare, R.; Martinelli, F.; Mercaldo, F.; Santone, A. Detecting Colluding Inter-App Communication in Mobile Environment. Appl. Sci. 2020, 10, 8351.

AMA Style

Casolare R, Martinelli F, Mercaldo F, Santone A. Detecting Colluding Inter-App Communication in Mobile Environment. Applied Sciences. 2020; 10(23):8351.

Chicago/Turabian Style

Casolare, Rosangela, Fabio Martinelli, Francesco Mercaldo, and Antonella Santone. 2020. "Detecting Colluding Inter-App Communication in Mobile Environment" Applied Sciences 10, no. 23: 8351.

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