Related papers: BinCtx: Multi-Modal Representation Learning for Ro…
Static detection technologies based on signature-based approaches that are widely used in Android platform to detect malicious applications. It can accurately detect malware by extracting signatures from test data and then comparing the…
While smartphones and WiFi networks are bringing many positive changes to people's lives, they are susceptible to traffic analysis attacks, which infer user's private information from encrypted traffic. Existing traffic analysis attacks…
Mobile applications (apps) often transmit sensitive data through network with various intentions. Some transmissions are needed to fulfill the app's functionalities. However, transmissions with malicious receivers may lead to privacy…
As the smartphone market leader, Android has been a prominent target for malware attacks. The number of malicious applications (apps) identified for it has increased continually over the past decade, creating an immense challenge for all…
Multimodal deception detection aims to identify deceptive behavior by analyzing audiovisual cues for forensics and security. In these high-stakes settings, investigators need verifiable evidence connecting audiovisual cues to final…
Annotating user interfaces (UIs) that involves localization and classification of meaningful UI elements on a screen is a critical step for many mobile applications such as screen readers and voice control of devices. Annotating object…
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…
The pervasiveness of the Android operating system, with the availability of applications almost for everything, is readily accessible in the official Google play store or a dozen alternative third-party markets. Additionally, the vital role…
The canonical approach to video action recognition dictates a neural model to do a classic and standard 1-of-N majority vote task. They are trained to predict a fixed set of predefined categories, limiting their transferable ability on new…
Multimedia event detection is the task of detecting a specific event of interest in an user-generated video on websites. The most fundamental challenge facing this task lies in the enormously varying quality of the video as well as the…
Deceptive patterns (DPs) are user interface designs deliberately crafted to manipulate users into unintended decisions, often by exploiting cognitive biases for the benefit of companies or services. While numerous studies have explored ways…
Different from a unimodal model whose input is from a single modality, the input (called multi-modal input) of a multi-modal model is from multiple modalities such as image, 3D points, audio, text, etc. Similar to unimodal models, many…
Research on backdoor attacks against multimodal contrastive learning models faces two key challenges: stealthiness and persistence. Existing methods often fail under strong detection or continuous fine-tuning, largely due to (1) cross-modal…
Detecting and intercepting malicious requests are one of the most widely used ways against attacks in the network security. Most existing detecting approaches, including matching blacklist characters and machine learning algorithms have all…
Recent video diffusion models generate photorealistic, temporally coherent videos, yet they fall short as reliable world models for autonomous driving, where structured motion and physically consistent interactions are essential. Adapting…
Screen recordings of mobile applications are easy to obtain and capture a wealth of information pertinent to software developers (e.g., bugs or feature requests), making them a popular mechanism for crowdsourced app feedback. Thus, these…
With the escalating threat of malware, particularly on mobile devices, the demand for effective analysis methods has never been higher. While existing security solutions, including AI-based approaches, offer promise, their lack of…
With the digital breakthrough, smart phones have become very essential component. Mobile devices are very attractive attack surface for cyber thieves as they hold personal details (accounts, locations, contacts, photos) and have potential…
There are over 1.2 million applications on the Google Play store today with a large number of competing applications for any given use or function. This creates challenges for users in selecting the right application. Moreover, some of the…
Machine learning-based malware detection dominates current security defense approaches for Android apps. However, due to the evolution of Android platforms and malware, existing such techniques are widely limited by their need for constant…