Related papers: Andro-profiler: Detecting and Classifying Android …

Android OS experiences a blazing popularity since the last few years. This predominant platform has established itself not only in the mobile world but also in the Internet of Things (IoT) devices. This popularity, however, comes at the…

The battle to mitigate Android malware has become more critical with the emergence of new strains incorporating increasingly sophisticated evasion techniques, in turn necessitating more advanced detection capabilities. Hence, in this paper…

Android-based smart devices are exponentially growing, and due to the ubiquity of the Internet, these devices are globally connected to the different devices/networks. Its popularity, attractive features, and mobility make malware creator…

Since Android has become a popular software platform for mobile devices recently; they offer almost the same functionality as personal computers. Malwares have also become a big concern. As the number of new Android applications tends to be…

With the rapid advancement of machine learning (ML), ML-based Android malware detection has gained significant popularity due to its ability to automatically learn malicious patterns from Android apps. However, the lack of an in-depth and…

While machine-learning algorithms have demonstrated a strong ability in detecting Android malware, they can be evaded by sparse evasion attacks crafted by injecting a small set of fake components, e.g., permissions and system calls, without…

In the digitized world, smartphones and their apps play an important role. To name just a few examples, some apps offer possibilities for entertainment, others for online banking, and others offer support for two-factor authentication.…

Copious mobile operating systems exist in the market, but Android remains the user's choice. Meanwhile, its growing popularity has also attracted malware developers. Researchers have proposed various static solutions for Android malware…

Popularity and complexity of malicious mobile applications are rising, making their analysis difficult and labor intensive. Mobile application analysis is indeed inherently different from desktop application analysis: In the latter, the…

As cyber threats and malware attacks increasingly alarm both individuals and businesses, the urgency for proactive malware countermeasures intensifies. This has driven a rising interest in automated machine learning solutions. Transformers,…

With the growth of mobile devices and applications, the number of malicious software, or malware, is rapidly increasing in recent years, which calls for the development of advanced and effective malware detection approaches. Traditional…

Malware detection is a growing problem particularly on the Android mobile platform due to its increasing popularity and accessibility to numerous third party app markets. This has also been made worse by the increasingly sophisticated…

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…

The widespread use of smartphones in daily life has raised concerns about privacy and security among researchers and practitioners. Privacy issues are generally highly prevalent in mobile applications, particularly targeting the Android…

The amount of Android malware has increased greatly during the last few years. Static analysis is widely used in detecting such malware by analyzing the code without execution. The effectiveness of current tools relies on the app model as…

With the development in the field of smartphones and ever growing base of Internet, various softwares are left prone to many malicious activities like pharming, phishing, ransomware, spam, spoofing, spyware, eavesdropping, etc. These…

Android malware detection has been extensively studied using both traditional machine learning (ML) and deep learning (DL) approaches. While many state-of-the-art detection models, particularly those based on DL, claim superior performance,…

Malware are malicious programs that are grouped into families based on their penetration technique, source code, and other characteristics. Classifying malware programs into their respective families is essential for building effective…

Android has become the most popular mobile operating system. Correspondingly, an increasing number of Android malware has been developed and spread to steal users' private information. There exists one type of malware whose benign behaviors…

Nowadays, Android is the most dominant operating system in the mobile ecosystem, with billions of people using its apps daily. As expected, this trend did not go unnoticed by miscreants, and Android became the favorite platform for…