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Passwords remain the primary authentication method in online services, a domain increasingly crucial in our digital age. However, passwords suffer from several well-documented security and usability issues. Addressing these concerns, password managers and ...

The FemTech industry, a booming segment of the health technology market, trades in feminist empowerment largely by data tracking and collection. As issues of privacy and surveillance related to users' data collection have grown, scholars in health, ...

Despite stringent data protection regulations, such as the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and other country-specific laws, numerous websites continue to use cookies to track user activities, raising ...

Personal experiences are widely shared and varied among types of social media. This study aims to understand how social ties (acquaintance & stranger) and anonymity (real-name & anonymous) of social platforms affect users' willingness to share and post ...

Investigating digital privacy behavior requires consideration of its contextual nuances and the underlying social norms. This study delves into users' joint articulation of such norms by probing their implicit assumptions and "common sense" surrounding ...

In order to share image and video datasets for training and validation of machine learning, personal identifiable information (PII) of natural persons needs to be removed. Street scenes are widely used in computer vision research, and ...

Recommendation unlearning is an emerging task to serve users for erasing unusable data (e.g., some historical behaviors) from a well-trained recommender model. Existing methods process unlearning requests by fully or partially retraining the model after ...

In today's data-driven world, organizations face increasing pressure to comply with data disclosure policies, which require data masking measures and robust access control mechanisms. This paper presents Mascara, a middleware for specifying and enforcing ...

Conventionally, federated learning aims to optimize a single objective, typically the utility. However, for a federated learning system to be trustworthy, it needs to simultaneously satisfy multiple objectives, such as maximizing model performance, ...

The advent of artificial intelligence-generated content (AIGC) represents a pivotal moment in the evolution of information technology. With AIGC, it can be effortless to generate high-quality data that is challenging for the public to distinguish. ...

Web tracking technology is prevalent on the Internet today, with most websites employing user identification systems that can accurately identify users or devices behind browsers. While numerous works in literature attempt to create machine learning ...

During the TLS 1.3 handshake, an entity (e.g., a client application) commonly transmits a chain of certificates and certificates' digital signatures to the remote party to authenticate themselves. Towards a transition to post-quantum TLS, several ...

Organizations and their security operation centers often struggle to detect and respond effectively to an extensive quantity of ever-evolving cyberattacks. While collaboration, such as threat intelligence sharing between security teams, and response ...

Traditionally, deep learning practitioners would bring data into a central repository for model training and inference. Recent developments in distributed learning, such as federated learning and deep learning as a service (DLaaS), do not require ...

In the expanding machine-to-everything (M2X) economy, trust between participants is essential for secure and efficient interactions. Multi-factor challenge set self-sovereign identity authentication (MFSSIA) leverages blockchain technology to foster ...

Acoustic sensing has become increasingly prevalent for mobile and ambient devices for applications such as human activity recognition, health monitoring, and environmental sensing. These approaches develop audio featurization techniques to enable machine ...

We present results for exposing vulnerabilities in MAC address randomization using Wi-Fi network discovery traffic collected at MobiCom 2023. By analyzing probe request sequence numbers and vendor-specific information elements, we successfully link ...

Ensuring user privacy remains critical in mobile networks, particularly with the rise of connected devices and denser 5G infrastructure. Privacy concerns have persisted across 2G, 3G, and 4G/LTE networks. Recognizing these concerns, the 3rd Generation ...

COVID-19 caused an abrupt shift towards remote learning, and along with it, an increased adoption of remote, online proctoring technology to both dissuade and identify academic dishonesty (i.e., cheating). This shift also came with significant discontent ...

The sixth Workshop on CPS & IoT Security and Privacy is set to take place in Salt Lake City, UT, USA, on October 18, 2024, in conjunction with the ACM Conference on Computer and Communications Security (CCS'24). This workshop marks the amalgamation of ...