Crowdsensing has received widespread attention in recent years. It is extensively employed
in smart cities and intelligent transportation systems. This paper comprehensively surveys …

Crowdsourced localization plays a significant role for the applications in Internet of Things.
Even though existing studies have proposed privacy-preserving localization algorithms to …

This paper investigates the problem of participant selection considering colluding attacks for
crowdsourcing. Compared with existing work, a practical vulnerability-induced colluding …

The basic work of power data research is anomaly detection. It is necessary to find a method
suitable for processing current power system data. Research proposes an algorithm of fast …

In crowdsourcing systems, a challenge arises in efficiently recruiting workers with unknown
execution speed to complete tasks with precedence constraints within the shortest possible …

The rapid development of distributed edge intelligence in the Internet of things (IoT)
scenarios has resulted in massive edge devices continuously generating data, leading to …

Privacy‐preserving data aggregation is an important technology for mobile crowdsensing.
Blockchain‐assisted data aggregation enables the traceability of sensing data to improve …

The low transaction capacity, high transaction cost and long-term privacy concerns of the
current Ethereum platform are notorious. Developers are seeking alternative blockchain …

Privacy-preserving localization plays a crucial role in enabling various applications on the
Internet of Things (IoT). Existing work applies random zero-sum noise to develop privacy …

Federated learning is an enabling technology for the services in Internet of vehicles because
it can effectively alleviate privacy issues in data circulation and diversified intelligent …