2021 西北工业大学智能通信与安全国际研讨会将于 2021 年 6 月 23 日至 6 月 24 日在西北工业大学友谊校区爱生楼 401进行，具体议程及时间安排如下：
报告[1]：联邦学习在移动通信网络中的应用
时 间 ：2021年06月23日(星期三)14:00-14:45
报告[2]：分布式机器学习在无线信道研究中的应用
时 间 ：2021年06月23日(星期三)15:30-16:15
报告[3]：车联网安全问题与挑战
时 间 ：2021年06月23日(星期三)17:00-17:45
报告[4]：协同感知技术在智能网联汽车中的应用
时 间 ：2021年06月23日(星期三)17:45-18:30
报告[5]：智能无线电中信号检测方法研究
时 间 ：2021年06月23日(星期三)19:00-19:45
报告[6]：数据安全挑战及发展趋势研究
时 间 ：2021年06月23日(星期三)20:30-21:15
报告[7]：面向物联网服务的雾资源分配研究
时 间 ：2021年06月23日(星期三)22:00-22:45
报告[8]：基于车载通信的道路安全增强方法研究
时 间 ：2021年06月23日(星期三)22:45-23:30
报告[9]：Systematical Verification of Concurrent Trigger-action IoT Systems
报告人：于银菠
时 间 ：2021年06月23日(星期三)14:45-15:30
内容简介：Trigger-action programming (TAP) is a popular end-userprogramming framework that can simplify the Internet of Things (IoT) automation with simple trigger-action rules. However, it also introduces new security and safety threats. A lot of advanced techniques have been proposed to address this problem. Rigorously reasoning about the security of a TAP-based IoT system requires a well-defined model and verification method both against rule semantics and physical-world features, e.g., concurrency, rule latency, extended action, and connection-based rule interactions, which has been missing until now. In this talk, we present a novel system to detect vulnerabilities in the TAP-based concurrent IoT system using model checking. It automatically extracts TAP rules from IoT apps, translates them into a hybrid model with model slicing and state compression, and performs semantic analysis and model checking with various safety and liveness properties. Our experiments corroborate that our detection system is effective in the security analysis of IoT systems: it identifies 533 violations with 9 new types of vulnerability from 1108 real-world market IoT apps and its efficiency of vulnerability detection is 60000 times faster than the baseline without optimization at least.
报告人简介：Yinbo Yu received the B.Sc. and Ph.D. degrees in information and communication engineering from Wuhan University, China, in 2014 and 2020. He is currently an Associate Professor with the School of Cybersecurity, Northwestern Polytechnical University, China. He was a visiting Ph.D. student with Northwestern University, USA from 2017 to 2019. His research interests span on the area of networking, security, and software verification.
报告[10]：Research on Behavior Recognition Technology Based on Wearable Device
报告人：毕红亮
时 间 ：2021年06月23日(星期三)16:15-17:00
内容简介：In recent years, Intelligent perception devices widely exist in people's lives, and the research of behavior recognition based on Intelligent perception technology has been further developed. Contact IntelliSense technology is mainly based on wearable devices, which has the characteristics of low cost, convenient deployment and not easy to be interfered by the external environment. However, the signal collected wearable devices is often weak and difficult to detect. The traditional window function method can not extract the behavior signal effectively. Many behaviors are similar and it is difficult to use the machine learning method to build the accurate recognition model directly. To address these two challenges, given the universality of wearable devices and the importance of behavior recognition, four key issues, namely Chinese character and stroke order recognition, pen-holding posture recognition, rhythm-based tap authentication and head gesture recognition during walking are studied.
报告人简介：Hongliang Bi received his B.S., M.S. and Ph.D. degrees in Engineering from Xi'an University of Technology, Soochow University and Wuhan University in 2013, 2015 and 2020, respectively. He is currently an assistant professor in the School of Cybersecurity of Northwestern Polytechnical University. His research interests include machine learning, IntelliSense, privacy security and Internet of Things, etc.
报告[11]：UAV-enabled Internet of Things
报告人：王曲北剑
时 间 ：2021年06月23日(星期三)19:45-20:30
内容简介：We have seen the proliferation of the Internet of Things (IoT), which has been wildly used in the industry, agriculture, smart city and other fields. IoT is essentially connecting things (or objects) to the Internet. However, there are two critical challenges when IoT is practically deployed. The first challenge is constrained network coverage (how to conduct data transmission when IoT infrastructure is hardly or not available).The second challenge issecurity vulnerability (how to guarantee the security of data transmission in IoT). Unmanned aerial vehicles (UAVs) have been widely used in wireless communications, thanks to their mobility and flexibility. Therefore, in this presentation, we mainly focus on utilizing UAVs to overcome the above challenges in IoT.
报告人简介：Qubeijian Wang received the Ph.D. degree from Macau University of Science and Technology, Macau, China. He is currently an assistant professor with the School of Cybersecurity, Northwestern Polytechnical University, China. His research interests include UAV communications, physical-layer security, and larger-scale network performance analysis.
报告[12]：Disturbance rejection and tracking control for quadrotor UAVs based on equivalent-input-disturbance approach
报告人：蔡文静
时 间 ：2021年06月23日(星期三)21:15-22:00
内容简介：Quadrotor unmanned aerial vehicle (QUAV) has four cross-coupled propellers. This special mechanical structure enables it many distinct abilities such as perform vertical take-off and landing (VTOL), hovering, and cruising. Relying on those abilities, QUAVs are used to accomplish some practical missions, and thus they are widely used and studied in the world. The control of QUAVs is the key to accomplish missions. Thus, the research on the control scheme of QUAVs has important scientific research value and engineering application prospect. Our study focuses on three typical problems in the control of QUAVs: fixed-point tracking control, waypoint-tracking control, and trajectory-tracking control. Considering the influences of nonlinearities, uncertainties, and underactuation, we put forward three control methods to improve the robustness and accuracy of the controller, and dynamic and steady-state performance of the system.
报告人简介：Wenjing Cai, School of Cybersecurity, Northwestern Polytechnical University. Received her Ph.D. degree from China University of Geosciences at 2020, and her B.Sc. & M.Sc. degrees from China University of Geosciences. She has been an exchange Ph.D. student at Tokyo University of Technology from 2016 to 2018. Nowadays, she is a young teacher in the School of Cybersecurity at Northwestern Polytechnical University. Her research areas include UAV control, nonlinear system analysis, and robust control.
报告[13]：智能高铁中的5G新基建
报告人：艾渤
时 间 ：2021年06月24日(星期四)8:30-9:15
内容简介：第5代移动通信（5G）是当前国际学术界及工业界研究和关注热点。多场景、多目标、多技术融合是5G区别于其他几代移动通信系统的重要特征。国际电信联盟ITU、世界无线研究论坛WWRF、中国5G标准推进组IMT-2020、欧盟5G研究组织NGMN以及METIS等都将高速铁路或高速移动性作为5G重要场景，高速铁路是5G的典型垂直应用行业之一。本报告面向未来高速铁路发展的业务和应用需求，指出5G/B5G技术应用于智能高速铁路系统的必要性和科学意义，并从高速铁路业务模型、网络架构、信道模型、可靠传输关键技术几个方面来讨论5G/B5G技术在未来高速铁路通信系统中的应用，具体技术主要包括毫米波通信、大规模天线阵列、波束管理、超可靠低时延等关键技术。
报告人简介：艾渤，北京交通大学二级教授、博士生导师，轨道交通控制与安全国家重点实验室常务副主任。国家杰青、优青、英国皇家学会牛顿高级学者基金、国家中组部万人计划领军人才、中国科协“求是杰出青年奖”、詹天佑铁道科技奖青年奖获得者；中国工程院“中国工程前沿杰出青年学者”；获得北京市优秀教师荣誉称号。至今发表IEEE期刊论文150余篇，获IEEE VTS协会Neil Shepherd Memorial Best Propagation Award最佳期刊论文奖和IEEE Trans. on Commun.最佳期刊论文奖；获IEEE Globecom、IEEE VTC等国际会议论文奖励13项；获得27项授权发明专利；被ITU, 3GPP等采纳提案21项；获省部级科技奖励9项。研究成果写入国家行业标准4项，成果应用于京沪等高速铁路，上百条、3万多公里的铁路线路建设。英国工程师学会会士（IET Fellow），IEEE BTS西安分会主席，IEEE VTS北京分会副主席，IEEE VTS杰出讲师。中国电子学会会士，中国通信学会监事会监事，中国移动轨道交通联盟5G产业推动委员会主任，国家6G总体组专家。
报告[14]：MetaEverything: Intelligent MetaMaterial aided Sensing and Communications
报告人：宋令阳
时 间 ：2021年06月24日(星期四)9:15-10:00
内容简介：Intelligent MetaMaterial recently stands out as a novel approach to improve the quality of communication links.The talk will provide the state-of-the-art of research on meta-surface assisted sensing and communications from the perspectives of physical, MAC, network, and application layers. It focuses on two main types of meta-surface based applications, i.e., cellular communications and RF sensing. It will discuss the meta-surface hardware design as well as machine learning techniques for different sensing applications. Technical issues related to communications will also be addressed including beamforming scheme design, phase shift optimization, and MAC layer protocol design.
报告人简介：宋令阳，英国约克大学博士、挪威奥斯陆大学博士后、美国哈佛大学博士后、英国飞利浦研究院高级研究员，现为北京大学博雅特聘教授、学科建设办公室副主任、电子学系副主任、信息与通信研究所所长。主要研究方向是无线通信网络、信号处理和机器学习。获得教育部自然科学一等奖、国家自然基金委杰出青年科学基金、首届国家973计划青年专题项目首席科学家、首届国家自然基金委优秀青年科学基金、中组部青年拔尖人才、中国青年科技奖、北京市五四青年奖章、IEEE通信协会亚太地区杰出青年研究奖、IEEE Communication Society Leonard G. Abraham Prize、IEEE Communications Society Heinrich Hertz Award等。曾被评为IEEE Fellow、Clarivate Analytics高被引科学家等。
报告[15]：Edge Learning: Theory, Algorithm and System Design
报告人：郭嵩
时 间 ：2021年06月24日(星期四)10:00-10:45
内容简介：Driving by flourishing of both distributed machine learning and mobile edge computing, there is a stringent need to combine the advantages of these technologies so as to provide the learning tasks with high performance. Edge Learning, as an emerging learning concept, is complementary to the cloud-based methods for big data analytics by enabling distributed edge nodes to cooperatively train models and conduct inferences with their local data. This talk will focus on learning paradigms, fundamental theories, and enabling technologies for Edge Learning. We will first explain the background and motivation for AI running at the network edge. Then, we will review the challenge issues existing in Edge Learning. Furthermore, we will provide an overview of the overarching architectures, frameworks, and emerging key technologies for learning performance, security, privacy, and incentive issues toward training/inference at the network edge. Finally, we will discuss future research opportunities on Edge Learning.
报告人简介：Song Guo is a Full Professor at Department of Computing, The Hong Kong Polytechnic University. He also holds a Changjiang Chair Professorship awarded by the Ministry of Education of China. Prof. Guo is a Fellow of the Canadian Academy of Engineering and a Fellow of the IEEE (Computer Society). His research interests are mainly in big data, edge AI, mobile computing, and distributed systems. He published many papers in top venues with wide impact in these areas and was recognized as a Highly Cited Researcher (Clarivate Web of Science). He is the recipient of over a dozen Best Paper Awards from IEEE/ACM conferences, journals, and technical committees. Prof. Guo is the Editor-in-Chief of IEEE Open Journal of the Computer Society and the Chair of IEEE Communications Society (ComSoc) Space and Satellite Communications Technical Committee. He was an IEEE ComSoc Distinguished Lecturer and a member of IEEE ComSoc Board of Governors. He has also served for IEEE Computer Society on Fellow Evaluation Committee, and been named on editorial board of a number of prestigious international journals like IEEE TPDS, IEEE TCC, IEEE TETC, etc. He has also served as chairs of organizing and technical committees of many international conferences.
报告[16]：Intelligent Reflecting Surface Empowered Space-Air-Ground Integrated Network
报告人：徐赛
时 间 ：2021年06月24日(星期四)10:45-11:30
内容简介：With cooperative transmission of different access ways and unified resource management, the integration of space-air-ground network has become a historic tendency because of its distinctive superiority in the global coverage, massive connectivity, high capacity and low latency, etc. Intelligent reflecting surface (IRS) techniques rising recently are positioned as a vital enabler for facilitating wireless communication networks. In view of these, this article attempts to give an overview of space-air-ground integrated network (SAGIN) and IRS, as well as to provide a new perspective of how to apply IRS into SAGIN. Based on these, some important research agendas are identified. Then, we present two examples of IRS-based vehicle-to-vehicle (V2V) backscatter communication in integrated space-ground network and IRS-assisted SAT and HAP integrated network. Finally, preliminary simulations verify the feasibility of the proposed strategy and evidence the benefit of integrating IRS into SAGIN.
报告人简介：Sai Xu [S'17, M'20] received the Ph.D. degree from the Harbin Institute of Technology, Harbin, China, in 2020. He was also a joint Ph.D. student with the Electrical Engineering Department, University of California, Los Angeles, CA, USA, from October 2017 to April 2019. He is currently an AssociateProfessor with the School of Cybersecurity, Northwestern Polytechnical University. His research interests include intelligent reflecting surface, physical layer security, 5G and 6G communications, and satellite communications.
报告[17]：A Study on Deep Learning-based Routing for Intelligent Traffic Control
报告人：毛伯敏
时 间 ：2021年06月24日(星期四)11:30-12:15
内容简介：Recent years, the global networks are challenged by the surging traffic demand since a growing number of devices are connected to offer users various kinds of services. The traffic control algorithms are becoming more important to avoid the congestion and ensure the satisfying end-to-end transmissions. Inspired by the development of Artificial Intelligence and computation platform, researchers are exploring new opportunities in packet processing and transmissions with deep learning to realize communication intelligentization. In this presentation, I will introduce our research on intelligent routing to reduce the end-to-end latency and improve network throughput. The talk will begin with the supervised learning-based routing model for a fixed backbone network. Then, the network dynamics including changing traffic and topology are considered and analyzed in the development of corresponding deep learning-based routing models. In the talk, we can find different deep learning strategies, such as supervised learning, online learning, and reinforcement learning, can be adopted to improve the throughput for different network scenarios.
报告人简介：Bomin Mao (S'15, M'9) is currently a full professor with the School of Cybersecurity, Northwestern Polytechnical University. He was an associate professor at the Graduate School of Information Sciences (GSIS), Tohoku University, Japan, from 2020 to 2021. He also served as an assistant professor from 2019 to 2020. His research interests are involving intelligent wireless networks, software defined networking, IoT, particularly with applications of machine intelligence and deep learning. He received several Best Paper Awards from IEEE conferences, such as IEEE Global Communications Conference in 2017 (GLOBECOM'17), GLOBECOM'18, and IEEE International Conference on Network Infrastructure and Digital Content in 2018 (IC-NIDC 2018). He was a recipient of the prestigious 2020 Niwa Yasujiro Outstanding Paper Award and 2020 IEEE Computer Society Tokyo/Japan Joint Local Chapters Young Author Award.
报告[18]：Aerial Computing: Enhancing Air-to-Ground Coverage for Next Generation Wireless Networks
报告人：盛敏
时 间 ：2021年06月24日(星期四)14:00-14:45
内容简介：Aerial base stations (ABSs) are promising to provide ubiquitous coverage in next-generation wireless networks due to the agility. However, trajectory planning and resource allocation (TPRA) for multiple ABSs is challenging since 1) ABSs fail to simultaneously cover all users due to the high mobility and energy limitation, and 2) the trajectory planning and resource allocation of ABSs are coupled. In this talk, we will discuss TPRA for multiple high-mobility ABSs to provide energy-efficient coverage, which is aided by efficient aerial computing. Especially, we focus on how to design decentralized trajectory planning algorithm based on decentralized reinforcement learning. Moreover,a transfer learning-based resource allocation algorithm is also presented to cater to the high mobility characteristics of ABSs.
报告人简介：盛敏，西安电子科技大学教授、博士生导师。教育部长江学者特聘教授，国家自然科学基金委杰出青年基金获得者，中国青年女科学家团队负责人，中国电子学会会士，中国通信学会会士。现为西安电子科技大学综合业务网理论及关键技术国家重点实验室主任，主要从事天地一体异构网络融合、无线自组织网络、空间信息网络等领域的研究工作；现任科技部6G总体专家组成员、中国电子学会青年科学家俱乐部副主席。主持包括国家重点研发计划、国家自然科学基金杰出青年科学基金、载人航天重点项目、科技部973项目等在内多项研究课题，获国家技术发明二等奖2项。
报告[19]：数据安全的现状与展望
报告人：李洪伟
时 间 ：2021年06月24日(星期四)14:45-15:30
内容简介：在数字经济中，数据已成为重要的生成要素。然而，数据在采集、传输、存储、使用等过程中还存在诸多安全问题。本报告将从国家需求、学术前沿、产业应用等多个维度来分析数据安全的现状，并展望数据安全未来的发展方向。
报告人简介：李洪伟，教育部长江学者特聘教授（2019），电子科技大学网络空间安全研究院副院长，科技部十四五“网络空间安全治理”重点专项专家组成员、国家自然科学基金委员会会议评审专家、四川省学术和技术带头人。IEEE通信学会安全分会Secretary（中国大陆首位任职该分会的学者）、IEEE Vehicular Technology Society Distinguished Lecturer、《IEEE Internet of Things Journal》Associate Editor、ACM China SIGSAC 2019 TPC Co-chair。长期从事数据安全领域的基础和应用研究，主持国家重点研发计划课题和国家自然科学基金重点项目。发表学术论文100余篇，其中中科院JCR-1区/CCF-A类论文36篇，获得了包括麻省理工学院Srinivas Devadas教授在内的数十位ACM/IEEE Fellow的引用和正面评价；获IEEE ICPADS 2020、IEEE MASS 2018和IEEE Healthcom 2015的最佳论文奖。研究成果已应用于金融、医疗等领域，获2019年国家科技进步一等奖、2019年四川省科技进步二等奖、2018年中国网络安全与信息产业“金智奖-十大人物奖”、2018年和2017年中国银行业信息科技风险管理课题成果奖。
报告[20]：工业网络系统的分布式感知与协同传输：机制设计与实现
报告人：陈彩莲
时 间 ：2021年06月24日(星期四)15:30-16:15
内容简介：随着信息通信技术的不断发展，无线技术在工业自动化监控中得到越来越广泛的应用。然而，与有线通信相比，无线通信面临着诸多新挑战。复杂严重的电磁干扰、动态多变的无线链路、大型设备的移动遮挡，导致监控系统的感知信息传输实时性和可靠性难以保证。通过充分利用时-频-空多域多维度资源设计协同传输机制，能够有效地抵抗衰落、抑制干扰，显著地提高端到端的信息传输性能。本报告将以工业生产过程监控系统为对象，研究网络系统的分布式动态感知方法与实时可靠传输机制设计，提出匹配工艺的关联特征学习机制和资源预分配策略，避免传统动态接入机制下的复杂握手开销，从而降低接入时延，提高资源利用效率。开发了确保传输性能的时间敏感网络(TSN)网关等设备，实现灵活配置和动态组网，为提升工业网络系统的感知和监控能力提供通信基础设施保障。
报告人简介：陈彩莲，上海交通大学自动化系教授，国家杰出青年科学基金获得者。主要从事工业网络系统的感知、传输与控制研究工作。主持科技部重点研发计划项目、NSFC重点项目等国家级和省部级项目20余项，在IEEE Transactions及其他国际期刊发表SCI论文100余篇，研究成果获2018年国家自然科学二等奖1项（排名第3），“教育部自然科学一等奖”2项，“上海市技术发明一等奖”1项。曾获得“IEEE模糊系统汇刊杰出论文奖”及最佳会议论文奖4项，中国自动化学会青年科学家奖等。先后担任IEEE Trans. Vehicular Technology, IET Cyber-Physical Systems: Theory and Applications等多个英文期刊编委，担任IASA19的TPC主席, IEEE Globecom'16和IEEE VTC 2016-Fall, 2020-Fall等旗舰会议的Symposium TPC共同主席。
报告[21]：卫星物联网随机接入技术
报告人：赵波
时 间 ：2021年06月24日(星期四)16:15-17:00
内容简介：The satellite Internet-of-Things (IoT) is one of the important application scenarios in the field of wireless communications, and it is also an important part of the B5G and airspace-ground integrated networks. Random access (RA) has become a typical multiple access method in the satellite IoT because it does not require resource allocation and central scheduling, and it has also received extensive attention. However, with the increase in the number of satellite IoT devices and the intelligent and energy-efficient development of satellite IoT, RA is also constantly facing new challenges. On the one hand, the massive number of satellite IoT devices puts huge pressure on the RA of the satellite IoT, which will lead to severe collision between accessing devices and even network congestion; On the other hand, the satellite IoT devices are gradually miniaturized and intelligentized, which poses huge challenges to device's computational complexity, transmission power, and energy consumption. In order to cope with these issues, research on key techniques of the RA for satellite IoT has been carried out from three scenarios: RA for inter-satellite non-cooperative satellites, RA for inter-satellite cooperative satellites, and RA for relay-assisted satellites, and many effective satellite RA protocols are proposed in terms of different metrics. This talk presents the proposed effective RA protocols.
报告人简介：赵波于2020年毕业于西安电子科技大学并取得博士学位，2021年加入西北工业大学网络空间安全学院，一直从事卫星物联网、卫星地面中继网随机多址接入技术研究，利用传统的最优化算法以及智能学习算法解决多址接入中的问题。
报告[22]：Trajectory Optimization and Resource Allocation in Air-Ground Integrated Networks
报告人：郭鸿志
时 间 ：2021年06月24日(星期四)17:00-17:45
内容简介：Due to the outstanding characteristics of unmanned aerial vehicles (UAV), i.e., maneuverability and flexibility, UAV enabled mobile edge computing (MEC) has become a widely attractive research direction. However, single UAV cannot be qualified for numerous tasks and applications scenarios in view of its limited computing capacity, while multi-UAV enabled MEC is still in the initial stage, and most existing work transformed the problem of multi-UAV enabled MEC into multiplied single UAV. The UAV swarm can make UAVs cooperate intelligently, and accomplish diversified tasks in complex environments at low cost, which is regarded as a promising development direction of UAV technology. In this talk, we present some of our works on UAV enabled air-ground edge computing, with special emphasis on trajactory optimization and resource allocation. Besides, our recent thinkings of UAV swarm-based edge computing, including air-air cooperation, role division, etc., are also shared.
报告人简介：Hongzhi Guo received his B.S., M.S., and Ph.D. degrees in Computer Science and Technology from Harbin Institute of Technology in 2004, 2006, and 2011, respectively. He is currently an associate professor with the School of Cybersecurity, Northwestern Polytechnical University. He was the recipient of WiMob Best Paper Award 2019. His research interests cover MEC, AI, FiWi, IoT, 5G, smart grid, etc. He has published more than 30 peer-reviewed papers in many prestigious IEEE journals and conferences, and currently serves as an editor for IEEE Transactions on Vehicular Technology, Int. J. of Multimedia Intelligence and Security, and Frontiers in Communications and Network.
西北工业大学网络空间安全学院
西安市国际科技合作基地（I型）——无人系统安全与智能通信
2021年6月22日
