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Smartphones contain information that is more sensitive and personal than those found on computers and laptops. With an increase in the versatility of smartphone functionality, more data has become vulnerable and exposed to attackers.…

The Android operating system has been the most popular for smartphones and tablets since 2012. This popularity has led to a rapid raise of Android malware in recent years. The sophistication of Android malware obfuscation and detection…

As mobile phones have evolved into `smartphones', with complex operating systems running third- party software, they have become increasingly vulnerable to malicious applications (malware). We introduce a new design for mitigating malware…

Nowadays smartphones come embedded with multiple motion sensors, such as an accelerometer, a gyroscope and an orientation sensor. With these sensors, apps can gather more information and therefore provide end users with more functionality.…

Android is the predominant mobile operating system for the past few years. The prevalence of devices that can be powered by Android magnetized not merely application developers but also malware developers with criminal intention to design…

We explore the feasibility of AI assisted hand-gesture recognition using 802.11ad 60GHz (mmWave) technology in smartphones. Range-Doppler information (RDI) is obtained by using pulse Doppler radar for gesture recognition. We built a…

Mobile malware has increased rapidly last 10 years. This rapid increase is due to the rapid enhancement of mobile technology and their power to do most work for their users. Since mobile devices are personal devices, then a special action…

In this paper, we develop four malware detection methods using Hamming distance to find similarity between samples which are first nearest neighbors (FNN), all nearest neighbors (ANN), weighted all nearest neighbors (WANN), and k-medoid…

The astonishing spread of Android OS, not only in smartphones and tablets but also in IoT devices, makes this operating system a very tempting target for malware threats. Indeed, the latter are expanding at a similar rate. In this respect,…

With the widespread adoption of smartphones, ensuring pedestrian safety on roads has become a critical concern due to smartphone distraction. This paper proposes a novel and real-time assistance system called UWB-assisted Safe Walk (UASW)…

As the popularity of Android smart phones has increased in recent years, so too has the number of malicious applications. Due to the potential for data theft mobile phone users face, the detection of malware on Android devices has become an…

This study examines machine learning techniques like Decision Trees, Support Vector Machines, Logistic Regression, Neural Networks, and ensemble methods to detect Android malware. The study evaluates these models on a dataset of Android…

Due to its open-source nature, the Android operating system has consistently been a primary target for attackers. Learning-based methods have made significant progress in the field of Android malware detection. However, traditional…

Deep learning has emerged as a promising technology for achieving Android malware detection. To further unleash its detection potentials, software visualization can be integrated for analyzing the details of app behaviors clearly. However,…

Smartphones have become an intrinsic part of human's life. The smartphone unifies diverse advanced characteristics. It enables users to store various data such as photos, health data, credential bank data, and personal information. The…

As people store more personal data in their smartphones, the consequences of having it stolen or lost become an increasing concern. A typical counter-measure to avoid this risk is to set up a secret code that has to be entered to unlock the…

Smartphone apps often run with full privileges to access the network and sensitive local resources, making it difficult for remote systems to have any trust in the provenance of network connections they receive. Even within the phone,…

As the Internet of Things (IoT) continues to evolve, smartphones have become essential components of IoT systems. However, with the increasing amount of personal information stored on smartphones, user privacy is at risk of being…

Android malware has been on the rise in recent years due to the increasing popularity of Android and the proliferation of third party application markets. Emerging Android malware families are increasingly adopting sophisticated detection…

This paper presents a new Android malware detection method based on Graph Neural Networks (GNNs) with Jumping-Knowledge (JK). Android function call graphs (FCGs) consist of a set of program functions and their inter-procedural calls. Thus,…