相关论文: Enabling Strong Privacy Preservation and Accurate …
Blockchain technology with its secure, transparent and decentralized nature has been recently employed in many mobile applications. However, the mining process in mobile blockchain requires high computational and storage capability of…
The widespread use of mobile devices propels the development of new-fashioned video applications like 3D (3-Dimensional) stereo video and mobile cloud game via web or App, exerting more pressure on current mobile access network. To address…
In location-based services(LBSs), it is promising for users to crowdsource and share their Point-of-Interest(PoI) information with each other in a common cache to reduce query frequency and preserve location privacy. Yet most studies on…
Monitoring location updates from mobile users has important applications in many areas, ranging from public safety and national security to social networks and advertising. However, sensitive information can be derived from movement…
The large spread of sensors and smart devices in urban infrastructures are motivating research in the area of Internet of Thing (IoT), to develop new services and improve citizens' quality of life. Sensors and smart devices generate large…
Crowd-intelligence tries to gather, process, infer and ascertain massive useful information by utilizing the intelligence of crowds or distributed computers, which has great potential in Industrial Internet of Things (IIoT). A…
Mobile on-body sensing has distinct advantages for the analysis and understanding of crowd dynamics: sensing is not geographically restricted to a specific instrumented area, mobile phones offer on-body sensing and they are already deployed…
The advancement of smartphones with various type of sensors enabled us to harness diverse information with crowd sensing mobile application. However, traditional approaches have suffered drawbacks such as high battery consumption as a trade…
We present STAMP (Selective Task-Aware Mechanism for Text Privacy), a new framework for task-aware text privatization that achieves an improved privacy-utility trade-off. STAMP selectively allocates privacy budgets across tokens by jointly…
Organizations with a large user base, such as Samsung and Google, can potentially benefit from collecting and mining users' data. However, doing so raises privacy concerns, and risks accidental privacy breaches with serious consequences.…
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…
Today, location-based applications and services such as friend finders and geo-social networks are very popular. However, storing private position information on third-party location servers leads to privacy problems. In our previous work,…
Proof-of-Work (PoW) consensus mechanism is popular among current blockchain systems, which leads to an increasing concern about the tremendous waste of energy due to massive meaningless computation. To address this issue, we propose a novel…
In this paper, we study the privacy-preserving task assignment in spatial crowdsourcing, where the locations of both workers and tasks, prior to their release to the server, are perturbed with Geo-Indistinguishability (a differential…
People counting system in crowded places has become a very useful practical application that can be accomplished in various ways which include many traditional methods using sensors. Examining the case of real time scenarios, the algorithm…
Since the global spread of Covid-19 began to overwhelm the attempts of governments to conduct manual contact-tracing, there has been much interest in using the power of mobile phones to automate the contact-tracing process through the…
Privacy-preserving state estimation for linear time-invariant dynamical systems with crowd sensors is considered. At any time step, the estimator has access to measurements from a randomly selected sensor from a pool of sensors with…
Crowd counting and localization are important in applications such as public security and traffic management. Existing methods have achieved impressive results thanks to extensive laborious annotations. This paper propose a novel…
This paper explores mobile crowdsensing, which leverages mobile devices and their users for collective sensing tasks under the coordination of a central requester. The primary challenge here is the variability in the sensing capabilities of…
A plethora of contact tracing apps have been developed and deployed in several countries around the world in the battle against Covid-19. However, people are rightfully concerned about the security and privacy risks of such applications. To…