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224 results on '"Liu, Hongbo"'

25. Fast and Secure Key Generation with Channel Obfuscation in Slowly Varying Environments

Author

Li, Guyue, Yang, Haiyu, Zhang, Junqing, Liu, Hongbo, and Hu, Aiqun

Subjects
FOS: Computer and information sciences, Computer Science - Cryptography and Security, Information Theory (cs.IT), Computer Science - Information Theory, Cryptography and Security (cs.CR)
Abstract

The physical-layer secret key generation has emerged as a promising solution for establishing cryptographic keys by leveraging reciprocal and time-varying wireless channels. However, existing approaches suffer from low key generation rates and vulnerabilities under various attacks in slowly varying environments. We propose a new physical-layer secret key generation approach with channel obfuscation, which improves the dynamic property of channel parameters based on random filtering and random antenna scheduling. Our approach makes one party obfuscate the channel to allow the legitimate party to obtain similar dynamic channel parameters yet prevents a third party from inferring the obfuscation information. Our approach allows more random bits to be extracted from the obfuscated channel parameters by a joint design of the K-L transform and adaptive quantization. A testbed implementation shows that our approach, compared to the existing ones that we evaluate, performs the best in generating high entropy bits at a fast rate and a high-security level in slowly varying environments. Specifically, our approach can achieve a significantly faster secret bit generation rate at about $67$ bit/pkt, and the key sequences can pass the randomness tests of the NIST test suite.

Published
2022

36. Enabling Secret Key Distribution Over Screen-to-Camera Channel Leveraging Color Shift Property.

Author

Liu, Hongbo, Shi, Cong, and Chen, Yingying

Subjects
ELECTRONIC equipment, VISIBLE spectra, ADAPTIVE optics, IMAGE color analysis, OPTICAL transmitters
Abstract

Recent years witnessed the emergence of visible light communication (VLC) over screen-to-camera channel, such as barcode and unobtrusive optical pattern, due to the widely adoption of screen and camera in plenty of electronic devices. The prevalence of wide viewing angle screen and high standard cameras also imposes great threat for visible light communication, and the information leakage over screen-to-camera channel has been rarely explored. In this paper, we propose a secret key distribution system leveraging the unique color shift property over screen-to-camera channel. To facilitate such design, two practical secret key distribution methods, key matching-based and nearest next hop-based, are developed to map the secret key into a unique optical pattern on screen, which can only be correctly decoded by the legitimate user situated at an accessible region. We also provide theoretical analysis on the security of both methods. The performance of the proposed system is implemented with off-the-shelf devices and validated under various experimental scenarios. The results demonstrate that our system can achieve high bit-decoding accuracy for the legitimate users while maintaining low recovery accuracy for the attackers. [ABSTRACT FROM AUTHOR]

Published
2022
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40. Exploration and practice of the golden course construction of principles of chemical engineering based on 'online and offline learning'

Author

Peng Lin, Li Qingyun, Zhou Yufang, and Liu Hongbo

Subjects
Formative assessment, Online and offline, Class (computer programming), Resource (project management), Computer science, Knowledge engineering, Offline learning, Distance education, ComputingMilieux_COMPUTERSANDEDUCATION, Mathematics education, Curriculum
Abstract

Principles of chemical engineering is a very important basic course for chemical engineering and related major students. Several problems are existing in the traditional course teaching. The golden course construction of principles of chemical engineering were explored and practiced, and some achievements were obtained. “Online and offline learning” combination curriculum was constructed. “Online and offline learning” is a hybrid teaching model, which uses superstar online learning platform to build online teaching resource database. Online learning is for students to preview before class and review after class. Offline learning is mainly classroom teaching activities. The organic combination of the two can effectively improve the depth of students' learning. Ideological and political education was strengthened. Micro video based on knowledge points was recorded. Diversified formative assessment was established. The course won higher students' evaluation. Excellent students' competition results were got and their innovation ability was improved.

Published
2021

41. Exploration and Application of Closed Loop Online Teaching Mode

Author

Zhang Jian-ge, Hou Xuemei, and Liu Hongbo

Subjects
Mode (computer interface), Multimedia, Computer science, Teaching effect, Process (engineering), Distance education, ComputingMilieux_COMPUTERSANDEDUCATION, Online teaching, Teaching mode, computer.software_genre, Closed loop, computer
Abstract

In order to ensure the suspension of classes and schools during the outbreak of the new epidemic, the online teaching mode was explored and studied. The paper puts forward the teaching objectives and teaching requirements of the closed loop online teaching mode, discusses the problems that need to be considered in the closed loop online teaching mode, and carefully designs the closed loop online teaching mode in view of these problems, explores and forms a relatively perfect closed loop online teaching mode. According to the course of C language programming, the specific implementation process of the closed loop online teaching mode is given. After a semester of exploration and implementation, it ensured that the online teaching not only could be carried out in an orderly manner, but also had been well received by students and the supervisions. It has been agreed that the teaching effect of this teaching mode is good, and it is worth promoting in the future.

Published
2021

47. SpoVis: Decision Support System for Site Selection of Sports Facilities in Digital Twinning Cities.

Author

Zhang, Ke, Chen, Hao, Dai, Hong-Ning, Liu, Hongbo, and Lin, Zhongrui

Abstract

The site selection of sports facilities is a pivotal link in the construction of city livable environment and the development of sports business in digital-twinning cities. Recent years have witnessed data mining and visualization technologies bringing the convenience as well as opportunities for intelligent site selection. However, the lack of effective and reliable systematic analysis leads to difficulties in developing sports facilities planning schemes and constructing the site-selection system. In this article, we design Sport facility Visual analysis system (SpoVis), an interactive visual analysis system for planning sports facilities as well as site selection. SpoVis provides users with the distribution status and statistical analysis of various sports facilities. Based on a comprehensive consideration of city population distribution, construction cost, existing sports facilities, traffic situation, and development potential, SpoVis provides users with a reasonable site-selection scheme of sports facilities from both macro and microperspectives and recommends results through topology and map. Meanwhile, based on the distribution of existing sports facilities and city influencing factors, a set of visual analysis components are designed to facilitate users to evaluate the status and information of existing sports facilities. We have carried out extensive experiments on a real platform with real-world data. The experimental results show that the proposed site-selection models and algorithms have excellent accuracy and operation efficiency. [ABSTRACT FROM AUTHOR]

Published
2022
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50. Novel Fast Networking Approaches Mining Underlying Structures From Investment Big Data.

Author

Yang, Liping, Yang, Yu, Mgaya, Gervas Batister, Zhang, Bo, Chen, Long, and Liu, Hongbo

Subjects
CLASSIFICATION algorithms, CRYPTOCURRENCY mining, ALGORITHMS, DATA mining, DATA structures, BIG data
Abstract

Mining the relationship structures among the investors plays a vital role in promoting economic development as well as preventing financial risks, especially in the context of big data. This article proposes fast networking approaches from investment big data to explore three underlying structures, namely, investment pedigrees, investment groups, and structural holes. Inspired by disjoint sets and path compression, we first present a pedigree classification algorithm to identify investment pedigrees. Second, through introducing a pruning strategy and a data structure termed as “2-tuple list,” we develop a novel linear-time structure mining algorithm in network (SMAN) for investigating investment groups and structural holes from the investment pedigree. Finally, we show that our SMAN has higher clustering accuracy and efficiency than other existing algorithms on a variety of real-world tasks in terms of normalized mutual information (NMI) values. Our method is particularly well suited for mining the underlying structures from investment big data. [ABSTRACT FROM AUTHOR]

Published
2021
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