Related papers: Android Anti-forensics: Modifying CyanogenMod
In the context of preventing and fighting crime, the analysis of mobile phone traffic, among actors of a criminal network, is helpful in order to reconstruct illegal activities on the base of the relationships connecting those specific…
Android is a widely used operating system that employs a permission-based access control model. The Android Permissions System (APS) is responsible for mediating application resource requests. APS is a critical component of the Android…
Android malware is a spreading disease in the virtual world. Anti-virus and detection systems continuously undergo patches and updates to defend against these threats. Most of the latest approaches in malware detection use Machine Learning…
The ever-increasing number of Android devices and the accelerated evolution of malware, reaching over 35 million samples by 2024, highlight the critical importance of effective detection methods. Attackers are now using Artificial…
The current state-of-the-art Android malware detection systems are based on machine learning and deep learning models. Despite having superior performance, these models are susceptible to adversarial attacks. Therefore in this paper, we…
Security issues, threats, and attacks in relation with the IoT have been identified as promising and challenging area of research. Eventually, the need for a forensics methodology for investigating IoT-related crime is therefore essential.…
Making applications aware of the mobility experienced by the user can open the door to a wide range of novel services in different use-cases, from smart parking to vehicular traffic monitoring. In the literature, there are many different…
Digital investigators often get involved with cases, which seemingly point the responsibility to the person to which the computer belongs, but after a thorough examination malware is proven to be the cause, causing loss of precious time.…
Deep learning has shown its power in many applications, including object detection in images, natural-language understanding, and speech recognition. To make it more accessible to end users, many deep learning models are now embedded in…
With millions of apps that can be downloaded from official or third-party market, Android has become one of the most popular mobile platforms today. These apps help people in all kinds of ways and thus have access to lots of user's data…
In recent years, learning-based Android malware detection has seen significant advancements, with detectors generally falling into three categories: string-based, image-based, and graph-based approaches. While these methods have shown…
Android is the most widely used smartphone OS with 82.8% market share in 2015. It is therefore the most widely targeted system by malware authors. Researchers rely on dynamic analysis to extract malware behaviors and often use emulators to…
Today, a mobile phone is not just a phone but it is a computer that you can also use for calling someone. Besides, in criminal investigations the importance of evidence from the mobile phone is increasing as more and more phones are seized…
With the prolific growth in usage of smartphones across the spectrum of people in the society it becomes mandatory to handle and configure these devices effectively to achieve optimum results from it. This paper proposes a context sensitive…
Vendors in the Android ecosystem typically customize their devices by modifying Android Open Source Project (AOSP) code, adding in-house developed proprietary software, and pre-installing third-party applications. However, research has…
Android applications are executed on smartphones equipped with a variety of resources that must be properly accessed and controlled, otherwise the correctness of the executions and the stability of the entire environment might be negatively…
Mobile devices have become an indispensable component of modern life. Their high storage capacity gives these devices the capability to store vast amounts of sensitive personal data, which makes them a high-value target: these devices are…
Bring Your Own Device (BYOD) is a growing trend among enterprises, aiming to improve workers' mobility and productivity via their smartphones. The threats and dangers posed by the smartphones to the enterprise are also ever-growing. Such…
With the releases of Android Oreo and Pie, Android introduced some background execution limitations for apps. Google restricted the execution of background services to save energy and to prevent apps from running endlessly in the…
The Android ecosystem faces a notable challenge known as fragmentation, which denotes the extensive diversity within the system. This issue is mainly related to differences in system versions, device hardware specifications, and…