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Machine learning models are commonly used for malware classification; however, they suffer from performance degradation over time due to concept drift. Adapting these models to changing data distributions requires frequent updates, which…
Protecting sensitive information from unauthorized disclosure is a major concern of every organization. As an organizations employees need to access such information in order to carry out their daily work, data leakage detection is both an…
Drift in machine learning refers to the phenomenon where the statistical properties of data or context, in which the model operates, change over time leading to a decrease in its performance. Therefore, maintaining a constant monitoring…
It is well-known that malware constantly evolves so as to evade detection and this causes the entire malware population to be non-stationary. Contrary to this fact, prior works on machine learning based Android malware detection have…
Powered by machine learning services in the cloud, numerous learning-driven mobile applications are gaining popularity in the market. As deep learning tasks are mostly computation-intensive, it has become a trend to process raw data on…
Like many desktop operating systems in the 1990s, Android is now in the process of including support for multi-user scenarios. Because these scenarios introduce new threats to the system, we should have an understanding of how well the…
The Android operating system runs on the majority of smartphones nowadays. Its success is driven by its availability to a variety of smartphone hardware vendors on the one hand, and the customization possibilities given to its users on the…
Human values are an important aspect of life and should be supported in ubiquitous technologies such as mobile applications (apps). There has been a lot of focus on fixing certain kinds of violation of human values, especially privacy,…
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…
Android is among the most targeted platform by attackers. While attackers are improving their techniques, traditional solutions based on static and dynamic analysis have been also evolving. In addition to the application code, Android…
Uncertain changes in data streams present challenges for machine learning models to dynamically adapt and uphold performance in real-time. Particularly, classification boundary change, also known as real concept drift, is the major cause of…
Energy efficiency is an important criterion to judge the quality of mobile apps, but one third of our randomly sampled apps suffer from energy issues that can quickly drain battery power. To understand these issues, we conducted an…
The Android framework provides a rich set of APIs that can be exploited by developers to build their apps. However, the rapid evolution of these APIs jointly with the specific characteristics of the lifecycle of the Android components…
Cross-app collaboration via inter-component communication is a fundamental mechanism on Android. Although it brings the benefits such as functionality reuse and data sharing, a threat called component hijacking is also introduced. By…
Android apps should be designed to cope with stop-start events, which are the events that require stopping and restoring the execution of an app while leaving its state unaltered. These events can be caused by run-time configuration…
Data leakage is a very common problem that is often overlooked during splitting data into train and test sets before training any ML/DL model. The model performance gets artificially inflated with the presence of data leakage during the…
The impressive growth of smartphone devices in combination with the rising ubiquity of using mobile platforms for sensitive applications such as Internet banking, have triggered a rapid increase in mobile malware. In recent literature, many…
Vulnerabilities in Android smartphone chipsets have severe consequences, as recent real-world attacks have demonstrated that adversaries can leverage vulnerabilities to execute arbitrary code or exfiltrate confidential information. Despite…
Mobile developers face unique challenges when detecting and reporting crashes in apps due to their prevailing GUI event-driven nature and additional sources of inputs (e.g., sensor readings). To support developers in these tasks, we…
Contact tracing has historically been used to retard the spread of infectious diseases, but if it is exercised by hand in large-scale, it is known to be a resource-intensive and quite deficient process. Nowadays, digital contact tracing has…