Related papers: Implicit Smartphone User Authentication with Senso…

In this study, a novel method to obtain user-dependent human activity recognition models unobtrusively by exploiting the sensors of a smartphone is presented. The recognition consists of two models: sensor fusion-based user-independent…

Impostors are attackers who take over a smartphone and gain access to the legitimate user's confidential and private information. This paper proposes a defense-in-depth mechanism to detect impostors quickly with simple Deep Learning…

Mobile devices store a diverse set of private user data and have gradually become a hub to control users' other personal Internet-of-Things devices. Access control on mobile devices is therefore highly important. The widely accepted…

We present ConXsense, the first framework for context-aware access control on mobile devices based on context classification. Previous context-aware access control systems often require users to laboriously specify detailed policies or they…

Context modeling and recognition represent complex tasks that allow mobile and ubiquitous computing applications to adapt to the user's situation. Current solutions mainly focus on limited context information generally processed on…

With the latest developments in technology, extra and extra human beings depend on their private gadgets to keep their touchy information. Concurrently, the surroundings in which these gadgets are linked have grown to grow to be greater…

We introduce a novel approach to user authentication called Motion ID. The method employs motion sensing provided by inertial measurement units (IMUs), using it to verify the persons identity via short time series of IMU data captured by…

Opportunistic affect sensing offers unprecedented potential for capturing spontaneous affect ubiquitously, obviating biases inherent in the laboratory setting. Facial expression and voice are two major affective displays, however most…

Text entry makes up about one-fourth of the smartphone interaction events, and is known to be challenging and difficult. However, there has been little study about the characteristics of text entry in the context of smartphone app usage. In…

Sensitive inferences and user re-identification are major threats to privacy when raw sensor data from wearable or portable devices are shared with cloud-assisted applications. To mitigate these threats, we propose mechanisms to transform…

Protecting personal computers (PCs) from unauthorized access typically relies on password authentication, which is know to suffer from cognitive burden and weak credentials. As many users nowadays carry mobile devices with advanced security…

With the rapid advancement of large language models (LLMs), intelligent conversational assistants have demonstrated remarkable capabilities across various domains. However, they still mainly rely on explicit textual input and do not know…

In this paper, a part-based technique for real time detection of users' faces on mobile devices is proposed. This method is specifically designed for detecting partially cropped and occluded faces captured using a smartphone's front-facing…

While the study of language as typed on smartphones offers valuable insights, existing data collection methods often fall short in providing contextual information and ensuring user privacy. We present a privacy-respectful approach -…

There is growing concern about how personal data are used when users grant applications direct access to the sensors of their mobile devices. In fact, high resolution temporal data generated by motion sensors reflect directly the activities…

The more new features that are being added to smartphones, the harder it becomes for users to find them. This is because the feature names are usually short, and there are just too many to remember. In such a case, the users may want to ask…

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…

Person re-identification is a critical security task for recognizing a person across spatially disjoint sensors. Previous work can be computationally intensive and is mainly based on low-level cues extracted from RGB data and implemented on…

Behavioral biometrics-based continuous authentication is a promising authentication scheme, which uses behavioral biometrics recorded by built-in sensors to authenticate smartphone users throughout the session. However, current continuous…

Communication between connected objects in the Internet of Things (IoT) often requires secure and reliable authentication mechanisms to verify identities of entities and prevent unauthorized access to sensitive data and resources. Unlike…