撰稿人：黄敏杰

7月9日下午2:30-4:00, 美国福德汉姆大学（Fordham University）Md Zakirul Alam Bhuiyan博士应邀在广州大学行政西前座428会议室给计算机科学网络与工程学院师生们做了一场题为“Trustworthy Data Collection Algorithms in IoT Platforms”的学术报告。报告由我院彭滔博士主持。报告中，Alam博士首先介绍了从信息来源来判定数据的可信度，指出物联网系统中数据安全和隐私保护的重要性，并详细介绍了使数据不可靠的诚信问题、收集错误等四个原因。随后Alam博士指出数据收集在安全性和隐私方面具有严峻挑战，重点介绍了对于数据收集中计算数据可信度算法。算法中对数据信号进行详细分析，并将数据分为直接信任、推荐信任、链接信任和数据回程信任，然后针对这四种不同的信任进行处理。进而Alam博士提出自适应数据可信度模型（Adaptive Data Trustworthiness Models），然后对于此模型详细介绍了可信的评审评分系统（Trustworthy Review Scoring System）。报告开展的过程中，全体师生都非常积极地参与讨论，大家对如何计算数据可信度、如何应对价值观的快速变化等问题进行了激烈的讨论。

报告人简介

Md Zakirul Alam Bhuiyan PhD, is currently an Assistant Professor of the Department of Computer and Information Sciences at the Fordham University, NY, USA. He is also a Visiting Professor of Guangzhou University, China. Earlier, he worked as an Assistant Professor at the Temple University. His research focuses on dependability, cybersecurity, big data, and cyber physical systems. He has over 120 papers published in prestigious venues, including top tier IEEE/ACM transactions/magazines. Two of his papers have been recognized as the ESI Highly Cited Papers in Computer Sciences (as of 01/2018). He has served as a lead guest/associate editor for IEEE TBD, ACM TCPS, IEEE IoT journal, INS, JNCA, FGCS, and so on. He has also received the IEEE TCSC Award for Early Career Research Excellence (2016-2017) and the IEEE Outstanding Leadership Awards (2016, 2017, 2018), and so on. He has served as an organizer, general chair, program chair, workshop chair, and TPC member of various international conferences, including IEEE INFOCOM. He is a Senior Member of IEEE and a member of ACM.