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关键词： 无线射频识别   通信安全   身份认证协议   单标签场景   群组标签场景   安全性   认证效率  

摘要： 无线射频识别(RadioFrequencyIdentification,RFID)是一种自动识别技术，它能够利用无线射频信号实现非物理接触式的双向数据通信。由于其良好的抗污染性和较强的渗透性,在贸易、交通、医药等场景中均得到了广泛的应用。然而，非接触通信模式带来便捷性的同时，也给RFID系统带来多种安全隐患。在RFID系统中，身份认证协议被广泛用于保证通信数据的安全性，但是当涉及无源电子标签时，现有的身份认证协议很难适应低成本标签中计算和存储资源受限的情况。因此，本文在现有协议基础上提出了新的单标签RFID身份认证协议和群组RFID身份认证协议。在满足标签的低资源消耗条件下，提高RFID系统的安全性和认证效率。本文主要工作包括:　　针对低成本标签难以容纳复杂加密算法和通信过程易被截取篡改的问题，本文提出了一种新的高效RFID身份认证协议。该协议在不同通信实体间采用不同的运算方式，在阅读器和云服务器之间采用复杂度高的哈希函数，在标签和云服务器之间采用异或、位旋转和交换再交叉等复杂度低的操作。既保证了移动通信过程的安全性，同时降低了标签端的运算成本。协议在云服务器端采用索引数据表的存储方式，进一步提升了云服务器对标签和阅读器认证的检索效率，降低了敏感信息泄露的风险。最后通过理论分析、BAN逻辑分析和proverif软件分析证明了协议能够抵抗攻击者发起的去同步攻击、重放攻击、追踪攻击等攻击方式，并将各协议的通信开销、标签存储成本和运算成本进行了对比，结果表明所提协议的通信开销和标签成本较低。　　针对群组ID无法动态高效地分配给组内标签和多标签下单独的身份验证效率较低的问题，本文提出了一种标签动态分组、生成群组证明认证标签的轻量级RFID认证协议。首先，本协议根据标签的响应信息采用动态分组方式进行分组，分组后通过构建布隆向量、标记标签状态来分配群组标识，降低了轮询和单播传输组标识时消息的高重复率。认证过程中，同组内标签应用组ID构造信息在阅读器端进行群组认证，阅读器计算标签的群组证明在服务器端进行群组认证，提高了多标签认证协议的效率。最后通过形式化和非形式化分析证明了该协议的安全性，通过性能分析证明了多标签下协议的高认证效率。　　本文重点研究了RFID系统身份过程中存在的问题，针对单标签场景和群组标签场景提出了两种身份认证协议，采用非形式化分析对攻击者模型之外的攻击方式进行综合分析,借助BAN逻辑、proverif、随机语言模型形式化分析工具推理协议安全目标、构建攻击者模型多方面验证协议的安全性，最后进行性能对比验证了论文所设计协议的高效率和低成本。

关键词： DNN   Pruning   RFID   TEE   User verification  

摘要： User authentication, which verifies the identity of a user attempting to gain access to credentials resources, has become increasingly vital and is broadly deployed at almost every corner (e.g., facilities, airports, apartment buildings, and smart homes) on mobile devices. Although the mobile sensing community continues to evolve with the advancements of user verification approaches, some bottlenecks still exist in securely deploying user verification systems in real-world resource-constraint mobile application scenarios. 1) Traditional one-time verification methods request a user to provide his/her credentials (e.g., password or fingerprint) during each verification process. Such practices are inconvenient and flawed from security perspectives. Moreover, existing behavioral-based continuous verifications leverage specific human physical behaviors (e.g., gait pattern, keystroke, and hand gestures) to identify the user and existing physiological-based approaches leverage always-exist vital signs (e.g., cardiac biometrics, speech characteristics, and respiratory patterns) to perform non-intrusive user verification continuously. However, all these existing approaches require dedicated devices or users’ active participation, which are not applicable in many practical scenarios. 2) Inferring user identities from mobile sensor data under real-world conditions remains brittle and unreliable (e.g., environmental dynamics, body movements and emotions, and diverse users), preventing user authentication applications from being ready for use – especially those that require more difficult (but also powerful) forms of user profile modeling. Benefiting from the recent advancement of Deep Neural Networks (DNNs), DNN-based approaches have achieved state-of-the-art performance in solving a variety of application problems, such as object recognition, face recognition, video classification, and AR/VR. Thus, more mobile applications (i.e., user authentication) should benefit from using

关键词： Radio frequency identification   animal tracking   RFID tag   RFID applications  

摘要： The application of animal tracking holds significant importance across diverse economic domains, encompassing sectors including livestock husbandry, agricultural practices, and the conservation of wildlife populations. It aims to track and understand animal behavior, movement patterns, and health status. The predominant use of RFID technology is observed within the domains of logistics, localization, and the tracking of goods. Notably, the application of this technology in the field of animal tracking has experienced a significant surge in popularity in recent years. This paper conducts a systematic literature review focused on understanding how RFID technology is being applied in the field of animal tracking. We have conducted a state-of-the-art research regarding animal tracking solutions in the scientific literature and patents. We have analyzed these solutions targeting which animals are being tracked, which problems are addressed, operating frequency, and whether other technologies are combined with RFID for animal tracking purposes. Among the categories of problems addressed, livestock management emerged as the main area, followed by animal tracking and traceability. Mammals, especially cattle, are the most common type of animal monitored. Considering RFID technology, passive UHF tags appeared more often. Moreover, many works also employed cameras and GPS together with RFID. Finally, this work can significantly contribute to this field by systematically presenting a state-of-the-art application of RFID for animal tracking.

关键词： Gesture recognition   Costs   Character recognition   radio frequency identification (RFID)   tag  

摘要： Gesture recognition is the basis of human-computer interaction (HCI), and radio frequency identification (RFID) has attracted wide attention for its advantages of lightweight, low cost, and universality. We propose a Chinese gesture recognition system based on RFID (RF-CGR), which implements cross-domain Chinese character gesture recognition intuitively and effectively. The fundamental concept of RF-CGR is to extract hand motion patterns from RFID phase information and display distinctive gesture features. Firstly, we build a signal sensing model to capture gesture information effectively. Secondly, we innovatively convert the Chinese character phase signal into an intuitive picture representation and use the gesture movement change pattern as input through data preprocessing operations. Finally, modify-visual geometry group network (M-VGG) model is used for cross-domain gesture recognition. The M-VGG network learns high-level semantic features of gestures through spatiotemporal convolutions to extract cross-domain gesture features. Compared with other models, M-VGG has fewer parameters, and shorter training time, while still achieving high-accuracy gesture recognition. We evaluate its performance in three scenarios. The accuracy is 98.75% and 98% for new users and new scenarios, respectively, significantly outperforming existing wireless signal-based gesture recognition methods.

关键词： Radiofrequency identification   Printing   Ink   Substrates   Impedance   Sensors   Textiles   UHF communication   Wearable sensors   Medical conditions   Moisture control   Diaper   printing   received signal strength indicator (RSSI)   RFID sensor   textile based-sensor   ultra high frequency (UHF)   urinary incontinence   wearable   wetness detection  

摘要： The use of wearable textile Radio Frequency Identification (RFID) sensors is becoming widespread in many different application areas because of their technical utilization advantages. In this study, a textile-based Ultra High Frequency (UHF) RFID sensor that can be used to detect wetness has been developed and fabricated with a pad printing machine using silver conductive ink. The overall physical dimension of the proposed sensor structure is 75.0 mm x 38.0mm x 0.12mm. Two different types of Received Signal Strength Indicator (RSSI) measurement setups in near field region and at practical separation distances emulating more realistic environmental conditions have been carried out to test and validate the applicability of the proposed sensor. Water, saline and urine solutions have been used to evaluate different wetting conditions in the near field RSSI measurements by dropping different solutions on the RFID sensor integrated diaper. A permissible signal difference of at least 17 dBm has been detected between the wet and dry states of the proposed wetness detection sensor. The performance of the proposed RFID sensor has been evaluated using different separation distances of 32 cm, 40 cm and 50 cm with the practical result of maximum reading range to be 50 cm for the reliable determination of the binary wetness states. In addition, the performance of the RFID wetness sensor against different bending and deformation conditions is almost robust. It is concluded that the proposed sensor structure can be integrated onto the patient's diapers to facilitate the reliable detection of wetness states in cases such as urinary incontinence in remote health monitoring systems.

关键词： 煤矿机电设备   RFID   无线检测系统   数据库  

摘要： 本文主要探究了煤矿机电设备维护无线检测系统的设计要点与实现情况。该系统的硬件部分由无线网络子系统、设备识别子系统构成，在设计时选择MIMO天线提高数据传输速率，增强信道抗干扰能力，使用RFID系统配合防碰撞算法保证该系统可以精准识别煤矿机电设备。该系统的软件部分基于C++和VS2018平台开发，包含维护人员管理、机电设备管理、维护数据提交等多个功能模块，采用SQL Server 2022数据库。从调试情况来看，本文设计的煤矿机电设备维护无线检测系统的维护数据提交、短消息发送与数据库记录等主要功能均可正常实现，符合设计预期。

关键词： 排酸作业   数字化车间   射频识别   OPC UA   状态监控  

摘要： 肉类排酸是指严格执行检疫制度,在排酸车间内对屠宰后的畜胴体进行冷却排酸24小时左右,使胴体温度降至0-4℃。这种肉被称为冷鲜肉、排酸肉,符合现代营养学的理念,肉质更加成熟、鲜嫩、营养、安全,更易人体消化吸收。目前,国内中小型肉类加工企业通常采取人工手推畜胴体进入排酸车间进行排酸,生产方式落后,且由于排酸车间环境非常恶劣、人力成本不断提高,已出现了“用工荒”难题;同时,由于国内肉类加工设备制造企业缺乏能力、人才和经验开发性能优异的排酸车间管控系统,大型肉类加工企业不得不采购国外的设备和工业软件来提高排酸车间生产环节的效率,因此受制于国外,价格和维护成本高,行业面临“卡脖子”难题。故本文开展了面向肉类加工的全数字化排酸车间管控系统的研究,对解决肉类加工企业用工难题、打破排酸自动生产线控制系统被国外垄断的困局、推动国内肉类加工和设备制造行业转型升级都具有重要借鉴和指导意义。具体研究内容如下:(1)在充分调研了肉类加工企业排酸车间运作原理的基础上,提出了全数字化排酸车间管控系统的总体架构,基于三菱R系列PLC与上位工控机的控制方式设计了排酸自动生产线的机电系统结构,完成了系统设计、选型和安装集成,并给出了管控软件的总体实现方案。(2)在分析比较了目前主流的射频识别技术原理基础上,完成了排酸车间生产线畜胴体分类分级和入库自动识别的RFID读写器和电子标签的选型。对超高频电子标签读写性能参数和金属环境下电磁波传播理论进行了分析,并通过实验对读取距离、功率、标签在金属挂钩中镶嵌深度和封装方式对读取性能的影响进行了测试验证,确保畜胴体的可靠识别分类,以及金属挂钩在自动流水线上的识别成功率。同时对自动流水线上RFID读写器识别异常情况进行了分析,并给出解决方案。(3)基于CC-Link现场总线对分布式传感器和电控执行元件等监控信号进行了地址分配,研发PLC控制程序实现了排酸车间出入库调度监控。设计了基于OPC UA的监控信号访问方式和信息模型,并通过KEPServer EX6创建了OPC UA的服务器,供全数字化排酸车间管控系统人机交互界面进行显示、处理和监控。(4)综合利用.NET Framework框架、SQL SERVER数据库、PLC控制器和OPC UA等技术工具,完成了全数字化排酸车间管控系统各功能模块的开发,实现了产品分类分级、自动识别、出入库流水线作业的高效、可靠管控。在产学研合作企业搭建了排酸车间实验平台,实现了管控作业的无人化自动运行,验证了系统可行性与可靠性,为实现肉类加工业的全流程管控和数字化转型升级奠定了重要基础。

关键词： Anticounterfeiting   cognitive risk control (CRC)   physical-layer identification   radio-frequency identification (RFID)   tag  

摘要： Physical-layer counterfeit tag identification is a widely adopted technology for detecting clone tags in radio-frequency identification (RFID) systems. It has gained significant attention in recent years owing to its affordability and ease of implementation. However, the effectiveness of physical-layer identification technology is highly dependent on the tag identification environment. When the reading distance is far or signal power is low, the signal-to-noise ratio (SNR) of the tag signal may be low, leading to a degradation in classification accuracy. To address the issue, this article explores the application of cognitive risk control (CRC) in tag classification, aiming to enhance the SNR and improve classification accuracy. Additionally, this article introduces more time- and frequency-domain features, resulting in a total of 104 features, to further enhance the classification performance. The experiment utilizes a software radio device to classify tags from three manufacturers across seven popular types. The results indicate that the implementation of CRC has, on average, improved the classification accuracy of the tags by approximately eight percentage points. Moreover, when compared to traditional 28 and seven features, the use of 104 features has shown an average increase in classification accuracy of about two and four percentage points, respectively.

关键词： Temperature sensors   Sensors   Helical antennas   Thermistors   Yarn   Temperature measurement   Impedance   Radio frequency identification (RFID)   temperature sensing   textile-based sensors   wearable   wireless sensing technology  

摘要： Existing radio frequency identification (RFID) temperature sensors in the wearable field involve issues such as poor comfort level, high costs, low flexibility, and concealment. There is an urgent need to develop flexible wireless temperature sensors with yarn-like structure, low cost, and good reading performance. In this work, an ultrahigh-frequency (UHF) RFID temperature sensing yarn was designed by the principle of impedance mismatch between antenna and RFID chip as well as an incorporation of a miniature thermistor, and then, the prototype was prepared and evaluated on its sensing performance. The receive signal strength indication (RSSI) of the developed sensing yarn with the right helix structure exponentially varied with temperature, and it showed excellent capability in wireless sensing temperature. It has great potential for application in intelligent health monitoring such as body temperature and respiration monitoring.