Our paper “MISSILE: A System of Mobile Inertial Sensor-Based Sensitive Indoor Location Eavesdropping.” has been accepted for publish in IEEE Transactions on Information Forensics and Security (TIFS).
Our paper “Preserving User Privacy For Machine Learning: Local Differential Privacy or Federated Machine Learning?” has received the Best Theory Paper Award in the 1st International Workshop on Federated Machine Learning for User Privacy and Data Confidentiality (FML’19), in conjunction with IJCAI’19.
I have been awarded an RGC/GRF grant with title “Auditing Machine Learning as a Service” for HK$ 731,089 (2020-2022).
Our paper with title “A Boundary Differential Private Layer against Machine Learning Model Extraction Attacks” has been accepted by
ESORICS 2019. Congratulations to Huadi Zheng!
Our paper “Publishing Sensitive Trajectory Data Under Enhanced l-Diversity Model” has received the Best Paper Award in 20th IEEE International Conference on Mobile Data Management (MDM’19), Hong Kong.
Theme and Topics
Internet of Things (IoT) is renovating the way we monitor, understand, and control the physical world. While there are many successful stories on deploying IoT systems in various business sectors, we might underestimate the long-term challenge when facing the explosive amount of IoT and machine-to-machine (M2M) data. Almost all fields of data science need new IoT-aware solutions, including but not limited to data acquisition, cleaning, transformation, storage, integration, indexing, modeling, analysis, visualization, and interpretation.
The main focus of this special issue will be on the identification of problems in adopting existing data science techniques for IoT/M2M data and the renovation on them, with an emphasis on the retrieval and learning from these data. We welcome papers on new problems, techniques, methodologies and research directions for open problems in the context of IoT. Topics of interest include, but are not limited to:
- Data acquisition and cleaning techniques for IoT
- Data storage and indexing techniques for IoT
- Data modeling, representation, transformation, and integration techniques for IoT
- Streaming and query processing techniques for IoT
- Data mining and machine learning algorithms for IoT Big Data
- Data visualization and interpretation techniques for IoT
- Security, privacy and trust in Internet of Things
- Uncertainty and probabilistic IoT Big Data
- Data-driven IoT system design, implementation, and deployment
- Open issues for data management and analytics in IoT
- Manuscript Due: Aug 1, 2019
- First Notification: Nov 1, 2019
- Revised Manuscript: Feb 1, 2020
- Notification of Acceptance: Apr 1, 2020
- Camera Ready Paper Due: Jun 1, 2020
All submissions have to be prepared using the ACM template and submitted as a PDF via the Manuscript Central submission site at https://mc.manuscriptcentral.com/tds. More details about the submission can be found at https://tds.acm.org/authors.cfm.
- Haibo Hu, The Hong Kong Polytechnic University, China (email@example.com) web: http://haibohu.org
- Rik Sarkar, The University of Edinburgh, UK (firstname.lastname@example.org) web: https://homepages.inf.ed.ac.uk/rsarkar/
- Zhengzhang Chen, NEC Laboratories America, US (email@example.com) web: http://www.nec-labs.com/zhengzhang-chen
A research project entitled “AI Model Protection from Inversion Attacks” has been awarded by Huawei with HK$764,520.
20th IEEE International Conference on Mobile Data Management (MDM 2019) invites submissions for Advanced Seminar (i.e., Tutorial) proposals on all topics listed in the Call for Papers of the conference. More information can be found in conference website:
A research paper titled “CPP: Towards Comprehensive Privacy Preserving for Query Processing in Information Networks” has been published in Information Sciences, Volume 467, October 2018.
I was invited to give a talk in NDBC 2018 entitled “Ensuring Privacy and Integrity against Untrusted Cloud for Internet of Things Applications”.