WELCOME TO AIBlock 2022
The 4th International Workshop on Application Intelligence and Blockchain Security (AIBlock)
Program:
21 June 2022 (Local time in Italy, GMT+2)
09:10 - 09:20am
Welcome
Workshop chairs
09:20 - 10:10am
Keynote (Session Chair: Chunhua Su):
Towards Decentralized Privacy-Preserving Application Intelligence
- Sherman S. M. Chow, Department of Information Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
Abstract: Application intelligence gathers metadata of applications to benefit the applications in security and performance, e.g., sanitizing malicious content, managing multi-source data for efficient retrieval, or collaboratively filtering redundant information. One might envision an extended notion in which the application users contribute information useful for application intelligence beyond metadata, perhaps motivated by earning in-application credits in the form of cryptocurrency.
This talk quickly overviews some interesting results in cryptography (Financial Crypt. '15, IEEE ICDCS '21, IEEE S&P '21, Usenix Security '22) that can contribute to privacy-preserving application intelligence, ideally in a decentralized setting, to reduce the trust assumption over many potentially compromised or colluding users.
Bio: Sherman Chow is an Associate Professor at The Chinese University of Hong Kong, Shatin, N.T., Hong Kong. He received the Early Career Award 2013/14 from the Hong Kong Research Grants Council. He was a research fellow at the Department of Combinatorics and Optimization, University of Waterloo, Canada, a position he commenced after receiving his Ph.D. degree from the Courant Institute of Mathematical Sciences, New York University, United States. His main interests are Cryptography, Security, and Privacy, with publications in AsiaCrypt, CCS, EuroCrypt, ITCS, NDSS, S&P, and Usenix Security.
10:10 - 11:10am
Session I (Session Chair: Chunhua Su):
- Efficient Verifiable Boolean Range Query for Light Client on Blockchain Database
Jianpeng Gong, Jiaojiao Wu, Jianfeng Wang and Shichong Tan
- Hybrid Isolation Model for Device Application Sandboxing Deployment in Zero Trust Architecture
Jingci Zhang, Jun Zheng, Zheng Zhang, Tian Chen, Kefan Qiu, Quanxin Zhang and Yuanzhang Li
- Towards Interpreting Vulnerability of Object Detection Models via Adversarial Distillation
Yaoyuan Zhang, Yu-an Tan, Mingfeng Lu, Lu Liu, Quanxin Zhang, Yuanzhang Li and Dianxin Wang
11:10 - 11:20
Break
11:20 - 12:40
Session II (Session Chair: Allen Au):
- SuppliedTrust: A Trusted Blockchain Architecture for Supply Chains
Yong Zhi Lim, Jianying Zhou and Martin Saerbeck
- Vulnerability Dection for Smart Contract via Bakward Bayesian Active Learning
Jiale Zhang, Liangqiong Tu, Jie Cai, Xiaobing Sun, Bin Li, Weitong Chen and Yu Wang
- Universal Physical Adversarial Attack via Background Image
Dianxin Wang, Yidan Xu, Juan Wang, Yuanzhang Li, Yajie Wang and Zixuan Xu
- A Multi-Agent Deep Reinforcement Learning-based Collaborative Willingness Network for Automobile Maintenance Service
Shengang Hao, Jun Zheng, Jie Yang, Ziwei Ni, Quanxin Zhang and Li Zhang
21 June 2022 (Local time in Italy, GMT+2)
09:10 - 09:20am
Welcome
Workshop chairs
09:20 - 10:10am
Keynote (Session Chair: Chunhua Su):
Towards Decentralized Privacy-Preserving Application Intelligence
- Sherman S. M. Chow, Department of Information Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
Abstract: Application intelligence gathers metadata of applications to benefit the applications in security and performance, e.g., sanitizing malicious content, managing multi-source data for efficient retrieval, or collaboratively filtering redundant information. One might envision an extended notion in which the application users contribute information useful for application intelligence beyond metadata, perhaps motivated by earning in-application credits in the form of cryptocurrency.
This talk quickly overviews some interesting results in cryptography (Financial Crypt. '15, IEEE ICDCS '21, IEEE S&P '21, Usenix Security '22) that can contribute to privacy-preserving application intelligence, ideally in a decentralized setting, to reduce the trust assumption over many potentially compromised or colluding users.
Bio: Sherman Chow is an Associate Professor at The Chinese University of Hong Kong, Shatin, N.T., Hong Kong. He received the Early Career Award 2013/14 from the Hong Kong Research Grants Council. He was a research fellow at the Department of Combinatorics and Optimization, University of Waterloo, Canada, a position he commenced after receiving his Ph.D. degree from the Courant Institute of Mathematical Sciences, New York University, United States. His main interests are Cryptography, Security, and Privacy, with publications in AsiaCrypt, CCS, EuroCrypt, ITCS, NDSS, S&P, and Usenix Security.
10:10 - 11:10am
Session I (Session Chair: Chunhua Su):
- Efficient Verifiable Boolean Range Query for Light Client on Blockchain Database
Jianpeng Gong, Jiaojiao Wu, Jianfeng Wang and Shichong Tan
- Hybrid Isolation Model for Device Application Sandboxing Deployment in Zero Trust Architecture
Jingci Zhang, Jun Zheng, Zheng Zhang, Tian Chen, Kefan Qiu, Quanxin Zhang and Yuanzhang Li
- Towards Interpreting Vulnerability of Object Detection Models via Adversarial Distillation
Yaoyuan Zhang, Yu-an Tan, Mingfeng Lu, Lu Liu, Quanxin Zhang, Yuanzhang Li and Dianxin Wang
11:10 - 11:20
Break
11:20 - 12:40
Session II (Session Chair: Allen Au):
- SuppliedTrust: A Trusted Blockchain Architecture for Supply Chains
Yong Zhi Lim, Jianying Zhou and Martin Saerbeck
- Vulnerability Dection for Smart Contract via Bakward Bayesian Active Learning
Jiale Zhang, Liangqiong Tu, Jie Cai, Xiaobing Sun, Bin Li, Weitong Chen and Yu Wang
- Universal Physical Adversarial Attack via Background Image
Dianxin Wang, Yidan Xu, Juan Wang, Yuanzhang Li, Yajie Wang and Zixuan Xu
- A Multi-Agent Deep Reinforcement Learning-based Collaborative Willingness Network for Automobile Maintenance Service
Shengang Hao, Jun Zheng, Jie Yang, Ziwei Ni, Quanxin Zhang and Li Zhang
