Trust-aware internet of things service recommendation

Funding: 2019: $16,720
2020: $122,964
2021: $124,966
2022: $109,456
2018: $122,751
2019: $122,718
2020: $122,977

Project Member(s): Wang, X.

Funding or Partner Organisation: Australian Research Council (ARC DECRA Scheme)
Australian Research Council (ARC DECRA Scheme)

Start year: 2019

Summary: This project centres on the emerging Internet of Things, the number one technology that is expected to reshape the world and human society in the coming decades. It aims to develop innovative techniques and tools to recommend Internet of Things resources as services for trustworthy and cost-effective applications. This project will output novel techniques for the trust-aware recommendation of Internet of Things resources by modelling, evaluating, and relating Internet of Things data. The research will underpin innovative applications like smart home, urban computing, and mobile social sensing, which can significantly contribute to Australian society and the national economy. It also holds the potential to place Australia at the forefront of research and development in the vibrant and growing area of trustworthy Internet of Things.

Publications:

Altulyan, M, Yao, L, Kanhere, SS, Wang, X & Huang, C 2020, 'A unified framework for data integrity protection in people-centric smart cities', Multimedia Tools and Applications, vol. 79, no. 7-8, pp. 4989-5002.
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Chen, K, Yao, L, Zhang, D, Wang, X, Chang, X & Nie, F 2020, 'A Semisupervised Recurrent Convolutional Attention Model for Human Activity Recognition', IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 5, pp. 1747-1756.
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Huang, C, Yao, L, Wang, X, Benatallah, B & Zhang, X 2020, 'Software expert discovery via knowledge domain embeddings in a collaborative network', Pattern Recognition Letters, vol. 130, pp. 46-53.
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Xiao, Y, Pei, Q, Yao, L, Yu, S, Bai, L & Wang, X 2020, 'An enhanced probabilistic fairness-aware group recommendation by incorporating social activeness', Journal of Network and Computer Applications, vol. 156, pp. 102579-102579.
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CHEN, J, SU, S & WANG, X 2019, 'Towards Privacy-Preserving Location Sharing over Mobile Online Social Networks', IEICE Transactions on Information and Systems, vol. E102.D, no. 1, pp. 133-146.
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Li, M, Sun, Y, Su, S, Tian, Z, Wang, Y & Wang, X 2019, 'DPIF: A Framework for Distinguishing Unintentional Quality Problems From Potential Shilling Attacks', Computers, Materials & Continua, vol. 59, no. 1, pp. 331-344.
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Sun, Y, Tian, Z, Wang, Y, Li, M, Su, S, Wang, X & Fan, D 2019, 'Lightweight Anonymous Geometric Routing for Internet of Things', IEEE Access, vol. 7, pp. 29754-29762.
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Wang, Y, Sun, Y, Su, S, Tian, Z, Li, M, Qiu, J & Wang, X 2019, 'Location Privacy in Device-Dependent Location-Based Services: Challenges and Solution', Computers, Materials & Continua, vol. 59, no. 3, pp. 983-993.
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Yao, L, Wang, X, Sheng, QZ, Dustdar, S & Zhang, S 2019, 'Recommendations on the Internet of Things: Requirements, Challenges, and Directions', IEEE Internet Computing, vol. 23, no. 3, pp. 46-54.
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Bai, L, Yao, L, Kanhere, SS, Wang, X & Sheng, QZ 1970, 'STG2Seq: Spatial-Temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting', Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}, International Joint Conferences on Artificial Intelligence Organization, pp. 1981-1987.
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Bai, L, Yao, L, Kanhere, SS, Wang, X, Liu, W & Yang, Z 1970, 'Spatio-Temporal Graph Convolutional and Recurrent Networks for Citywide Passenger Demand Prediction', Proceedings of the 28th ACM International Conference on Information and Knowledge Management, CIKM '19: The 28th ACM International Conference on Information and Knowledge Management, ACM, Beijing, China, pp. 2293-2296.
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Bai, L, Yao, L, Kanhere, SS, Yang, Z, Chu, J & Wang, X 1970, 'Passenger Demand Forecasting with Multi-Task Convolutional Recurrent Neural Networks', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer International Publishing, Macau, China, pp. 29-42.
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Dong, M, Yao, L, Wang, X, Benatallah, B & Huang, C 1970, 'Similarity-Aware Deep Attentive Model for Clickbait Detection', Advances in Knowledge Discovery and Data Mining (LNAI), Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer International Publishing, Macau, China, pp. 56-69.
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Dong, M, Yao, L, Wang, X, Benatallah, B, Zhang, X & Sheng, QZ 1970, 'Dual-stream Self-Attentive Random Forest for False Information Detection', 2019 International Joint Conference on Neural Networks (IJCNN), 2019 International Joint Conference on Neural Networks (IJCNN), IEEE, Budapest, HUNGARY.
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Bai, L, Yao, L, Kanhere, SS, Wang, X & Yang, Z 1970, 'Automatic Device Classification from Network Traffic Streams of Internet of Things', 2018 IEEE 43rd Conference on Local Computer Networks (LCN), 2018 IEEE 43rd Conference on Local Computer Networks (LCN), IEEE, USA, pp. 597-605.
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FOR Codes: Interorganisational Information Systems and Web Services, Database Management, Application Software Packages (excl. Computer Games), Electronic Information Storage and Retrieval Services, Service oriented computing, Database systems, Application software packages

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.