报告人：林晖副教授 福建师范大学
报告题目：A Data Trustworthiness Enhanced Reputation Mechanism for Mobile Crowd Sensing in Smart City
时 间：2017年5月24日 (星期三) 14:30 ~ 15:30
地 点：仓山校区成功楼603报告厅
主 办：数学与计算机科学学院, 福建省网络安全与密码技术重点实验室
参加对象：全院老师和相关研究生
报告摘要：Smart cities use Internet-of-Things (IoT) based advanced sensing, monitoring, processing, and high-speed communications and networking technologies to improve people’s quality of life and construct the sustainable inhabitation. Mobile Crowd Sensing (MCS) arises as an emerging technology to assist smart city applications through crowd sensing services wheredata is gathered and stored from intelligent devices interacting continuously with citizens. For the success of the burgeoning MCS technology in smart city applications, it is vital to address the key challenge of data trustworthiness in MCS. Therefore, this paper proposesa Data Trustworthiness enhanced Reputation Mechanism (DTRM) to defend against internal attacks and enhance data trustworthiness for MCS in smart city. In the DTRM, the sensitivity-level based data category, metagraph theory based user group division and reputation transferring are integrated into the reputation query and evaluation process.The cost analysis indicates that the DTRM has a linear communication and computation complexity. Simulation results demonstrate the superior performance of the DTRM compared to existing reputation mechanisms under internal mobile attacks and bad mouthing attacks.
