相关论文: Interpretable by Design: MH-AutoML for Transparent…

Today's mobile platforms provide only coarse-grained permissions to users with regard to how third- party applications use sensitive private data. Unfortunately, it is easy to disguise malware within the boundaries of legitimately-granted…

The problem of malicious software (malware) detection and classification is a complex task, and there is no perfect approach. There is still a lot of work to be done. Unlike most other research areas, standard benchmarks are difficult to…

Machine learning and deep learning (ML/DL) have been extensively applied in malware detection, and some existing methods demonstrate robust performance. However, several issues persist in the field of malware detection: (1) Existing work…

Enhancing yield is recognized as a paramount driver to reducing production costs in semiconductor smart manufacturing. However, optimizing and ensuring high yield rates is a highly complex and technical challenge, especially while…

Automated algorithm design is entering a new phase: Large Language Models can now generate full optimisation (meta)heuristics, explore vast design spaces and adapt through iterative feedback. Yet this rapid progress is largely…

As big data becomes ubiquitous across domains, and more and more stakeholders aspire to make the most of their data, demand for machine learning tools has spurred researchers to explore the possibilities of automated machine learning…

The android operating system is being installed in most of the smart devices. The introduction of intrusions in such operating systems is rising at a tremendous rate. With the introduction of such malicious data streams, the smart devices…

AutoML systems provide a black-box solution to machine learning problems by selecting the right way of processing features, choosing an algorithm and tuning the hyperparameters of the entire pipeline. Although these systems perform well on…

Android is an open software platform for mobile devices with a large market share in the smartphone sector. The openness of the system as well as its wide adoption lead to an increasing amount of malware developed for this platform. ANANAS…

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…

Mobile task automation is an attractive technique that aims to enable voice-based hands-free user interaction with smartphones. However, existing approaches suffer from poor scalability due to the limited language understanding ability and…

The widespread adoption of Android devices for sensitive operations like banking and communication has made them prime targets for cyber threats, particularly Advanced Persistent Threats (APT) and sophisticated malware attacks. Traditional…

With the emerging trend of GPT models, we have established a framework called AutoML-GPT that integrates a comprehensive set of tools and libraries. This framework grants users access to a wide range of data preprocessing techniques,…

The vulnerability of smartphones to cyberattacks has been a severe concern to users arising from the integrity of installed applications (\textit{apps}). Although applications are to provide legitimate and diversified on-the-go services,…

Mobile malware has been growing in scale and complexity spurred by the unabated uptake of smartphones worldwide. Android is fast becoming the most popular mobile platform resulting in sharp increase in malware targeting the platform.…

Over the last decade, the long-running endeavour to automate high-level processes in machine learning (ML) has risen to mainstream prominence, stimulated by advances in optimisation techniques and their impact on selecting ML…

Malware authors reuse the same program segments found in other applications for performing the similar kind of malicious activities such as information stealing, sending SMS and so on. Hence, there may exist several semantically similar…

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…

Autonomous agents have become increasingly important for interacting with the real world. Android agents, in particular, have been recently a frequently-mentioned interaction method. However, existing studies for training and evaluating…

Android malware continues to evolve through obfuscation and polymorphism, posing challenges for both signature-based defenses and machine learning models trained on limited and imbalanced datasets. Synthetic data has been proposed as a…