Prioritizing the multi-criterial features based on comparative approaches for enhancing security of IoT devices

The Internet of Things (IoT) technologies continuously expand with time due to the advances in automated, connected device technology, mobility, and wide access to information. IoT is the collection of many linked devices due to their unique features, such as scalability, maintainability, fault tolerance, reliability, accuracy, and much more. With the growing number of hybrid devices in large organizations, security and privacy concerns are becoming more challenging. Security is essential for protecting the hardware, network aspects of devices, and information access from unauthorized entities. Most of the security methods and procedures provided by researchers are based on existing Internet security practices. The top-ranking authentication feature categories included the most compatible and common authentication feature for all types of IoT-based devices as an elementary security requirement for protection from unauthorized access. The future challenge is to address the incompatibility of the authentication feature with IoT devices based on appropriate technologies. AI and machine learning are also implementable in order to detect the vulnerability of IoT devices and inform the concerned operator or administration for protection. This research highlights the authentication feature of IoT devices from literature studies and evaluates the significant feature using COPRAS approach to assist organization in enhancing security of IoT devices.     

Joint beamforming and phase-shifting design for energy efficiency in RIS-assisted MISO communication with statistical CSI

The emergence of more and more computation-intensive applications has imposed higher requirements in spectrum and energy efficiency (EE) for internet of things (IoT) wireless networks. Massive multiple-input multiple-output (MIMO) is utilized to gain spectral efficiency as an important part of wireless systems. However, the power expansion from hardware lowers the massive MIMO performance remarkably. Reconfigurable intelligent surface (RIS) technology can solve this problem well since it can not only provide higher array gain but also reduce energy depletion and hardware expense. In this article, we study joint optimization about beam-forming, RIS phase shift, and energy harvesting of IoT devices for maximizing EE of the multiple-input single-input downlink system with multiple IoT devices and an energy harvesting device. Different from existing works focusing on ergodic capacity with known statistic channel information of BS-RIS-device, we suppose that statistics information of RIS-device is known. Mathematically, the joint optimization problem is cast into a challenging non-convex one. To this end, based on successive convex approximation, we convert the original problem into two parts and then provide two heuristic schemes to tackle them, respectively. Next, an iterative scheme integrated by two heuristic algorithms is proposed to earn feasible solution in polynomial time. Finally, the proposed scheme is verified to be effective by simulations.     

Computation bits maximization in backscatter-aided wireless powered MEC using binary offloading

This article considers a backscatter-aided wireless powered mobile edge computing (BC-aided WPMEC) network, in which the tasks data of each Internet of Things (IoT) device can be computed locally or offloaded to the MEC server via backscatter communications, and design a resource allocation scheme regarding the weighted sum computation bits (WSCB) maximization of all the IoT devices. Towards this end, by optimizing the mobile edge computing (MEC) server’s transmit power, IoT devices’ power reflection coefficients, local computing frequencies and time, the time allocation between the energy harvesting and task offloading, as well as the binary offloading decision at each IoT device, we built a WSCB maximization problem, which belongs to a non-convex mixed integer programming problem. For solving this, the proof by contradiction and the objective function’s monotonicity are considered to determine the optimal local computing time of each IoT device and the optimal transmit power of the MEC server, and the time-sharing relaxation (TSR) is adopted to tackle the integer variables, which are used to simplify the original problem. Then, we decouple the simplified problem into two sub-problems by means of the block coordinate decent (BCD) technology, and each of the sub-problems is transformed to a convex one by introducing auxiliary variables. Based on this, we design a two-stage alternative (TSA) optimization algorithm to solve the formulated WSCB problem. Computer simulations validate that the TSA algorithm has a fast convergent rate and also demonstrate that the proposed scheme achieves a higher WSCB than the existing schemes.     

HIRFL-CSR前端总线控制器的改进设计

论述了用于兰州重离子加速器冷却存储环(HIRFL CSR)控制系统的前端总线系统控制器的改进。 改进了控制器的嵌入式操作系统和应用程序, 开发了控制器和数据库交换数据的应用程序。 该控制器基于BGA封装的ARM920T(ARM9)处理器和嵌入式的LINUX操作系统, 可以连接标准的VGA显示器、 键盘、 鼠标, 采用了现场可编程的FPGA器件进行背板接口设计, 并具有64 mA高驱动能力的总线驱动器, 以及拥有灵活的接口信号定义可编程能力, 是HIRFL CSR控制系统的关键部件。 The EVME bus controller which is a key component of the HIRFL CSR control system was improved . Besides reconfiguring the embedded Linux, a utility program was developed for data exchange between the controller and the database. The bus controller is based on ARM920T(ARM9) micro processor which is BGA packaged. The bus controller has the universal interface of VGA display, keyboard, and mouse. The backboard interface logic is programmed in an in system configurable FPGA device. The bus can drive high current up to 64 mA, with the flexibility of the programmable signal definitions. All the improved performance helped the EVME bus controller play a crucial role in HIRFL CSR control system.     

Acousto-optic device-based high-speed high-isolation photonic switching fabric for signal processing

A high-speed, switched, binary photonic switching fabric based on two acousto-optic devices arranged in a compact self-aligning (by acousto-optic device-based Bragg matching) optical geometry is introduced for photonic signal processing and control. This fabric has the unique capability to provide simultaneously both high switching speeds and high optical isolation, a critical need for advanced low-noise high-speed signal-processing applications. The proof-of-concept experimental fabric demonstrated nearly 60% light throughput, a 39-dB optical isolation level for both states of the switching fabric, and a 138-ns switching time.     

Blockchain-based group authentication scheme for 6G communication network

The ultimate objective in this period is to turn present technology into intelligent global habitats that ease daily interactions. The emerging Industry 4.0 has provided exciting potential technologies that have sped up the transition from the Internet of Things (IoT) to the Internet of Everything using advancements in artificial intelligence (IoE). A secure data transmission method and much higher networking rates are required by the exponential increase in the development and implementation of various 4.0-related industries, even if a blockchain currently employs a fast network like 5G. This highlights how 6G is required to meet the requirements of real-time applications. This research suggests a group-based handover authentication strategy for 6G heterogeneous networks, taking into account the handover of group users in real-world scenarios, to increase the efficiency and guarantee the security of the authentication process. The system consists of four components: the user UE, the access points gNB and eNB, the servers AAA and AAA*, and the widely used blockchain. Additionally, it is split into the EPC (evolved packet core) and 6GC domains by various network topologies (6G core network). To access network services, the UE must first carry out initial authentication and key negotiation with the local server. The system then performs handover authentication as well as batch authentication for individual and group users in handover scenarios, depending on the user count. The suggested scheme accomplished global switching authentication without making the switching process more difficult, accomplished group switching authentication by utilizing blockchain and aggregated signature technologies, and decreased the one-by-one authentication time by Yan using the D–H key exchange idea to accomplish known randomness security. Through formal examination and additional security analysis of the suggested protocol using the AVISPA tool, the results demonstrate that the protocol is secure.     

Wavy channel thin film transistor architecture for area efficient,high performance and low power displays

We demonstrate a new thin film transistor (TFT) architecture that allows expansion of the device width using continuous fin features – termed as wavy channel (WC) architecture. This architecture allows expansion of transistor width in a direction perpendicular to the substrate, thus not consuming extra chip area, achieving area efficiency. The devices have shown for a 13% increase in the device width resulting in a maximum 2.5× increase in ‘ON’ current value of the WCTFT, when compared to planar devices consuming the same chip area, while using atomic layer deposition based zinc oxide (ZnO) as the channel material. The WCTFT devices also maintain similar ‘OFF’ current value, ～100 pA, when compared to planar devices, thus not compromising on power consumption for performance which usually happens with larger width devices. This work offers an interesting opportunity to use WCTFTs as backplane circuitry for large‐area high‐resolution display applications. (© 2014 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Recent development of studies on the mechanism of resistive memories in several metal oxides

Resistive switching random access memories(RRAM)have been considered to be promising for future information technology with applications for non-volatile memory,logic circuits and neuromorphic computing.Key performances of those resistive devices are approaching the realistic levels for production.In this paper,we review the progress of valence change type memories,including relevant work reported by our group.Both electrode engineering and in-situ transmission electron microscopy(TEM)high-resolution observation have been implemented to reveal the influence of migration of oxygen anions/vacancies on the resistive switching effect.The understanding of resistive memory mechanism is significantly important for device applications.     

Recent progress on two-dimensional neuromorphic devices and artificial neural network

Mimicking biological synapses with microelectronic devices is widely considered as the first step in hardware building artificial neuromorphic networks, which is also the basis of brain-inspired neuromorphic computing. Numerous artificial neurons and synapses making up an artificial neuromorphic network have been gained wide attention due to their powerful and efficient data processing capabilities. Recently, artificial synapses, especially memristor-type and transistor-type synapses based on multifarious two-dimensional (2D) materials have been paid much attention. The unique properties of 2D materials make devices perform well in learning ability and power efficiency when mimicking synaptic behaviors, which highlights the feasibility of 2D neuromorphic devices in constructing artificial neuromorphic networks. Herein, the basic structures and principles of biological synapses are introduced, and the definitions of synaptic behaviors in synaptic electronic devices are discussed. Then, the progress of 2D memristor-type and transistor-type neuromorphic devices involving their device architecture, neuromorphic operational mechanism, and promising applications is reviewed. Finally, the future challenges of artificial synaptic devices based on 2D materials are discussed briefly.     

Blockchain based Scalable model for Secure Dynamic Spectrum Access

Conventional Cooperative spectrum sensing techniques either suffer from single point of failure attack or lack in providing incentives to users which makes them incompatible for Wireless Service Provider (WSP). We propose a dynamic spectrum access framework for WSP which gives prominence to automated sensing and sharing with the use of blockchain. In this system, the opportunity of spectrum access is first examined by sensor nodes and the access right is then allocated to the users when their transactions to WSP are authenticated in a decentralized manner. Apart from using blockchain as a reliable platform for automatic enforcement of spectrum sensing, we propose a novel mechanism for securing our network from the threats designed primarily for Cognitive Radio Networks. In addition to this, our proposed approach enhances the scalability of blockchain networks by using the sidechains for storing data and checkpointing it onto main chain after periodic intervals of time. Extensive simulations in Octave indicate superior performance offered by our proposed model.     

Self-Adaptive Learning of Task Offloading in Mobile Edge Computing Systems

Mobile edge computing (MEC) focuses on transferring computing resources close to the user’s device, and it provides high-performance and low-delay services for mobile devices. It is an effective method to deal with computationally intensive and delay-sensitive tasks. Given the large number of underutilized computing resources for mobile devices in urban areas, leveraging these underutilized resources offers tremendous opportunities and value. Considering the spatiotemporal dynamics of user devices, the uncertainty of rich computing resources and the state of network channels in the MEC system, computing resource allocation in mobile devices with idle computing resources will affect the response time of task requesting. To solve these problems, this paper considers the case in which a mobile device can learn from a neighboring IoT device when offloading a computing request. On this basis, a novel self-adaptive learning of task offloading algorithm (SAda) is designed to minimize the average offloading delay in the MEC system. SAda adopts a distributed working mode and has a perception function to adapt to the dynamic environment in reality; it does not require frequent access to equipment information. Extensive simulations demonstrate that SAda achieves preferable latency performance and low learning error compared to the existing upper bound algorithms.     

Blockchain aware proxy re-encryption algorithm-based data sharing scheme

The blockchain stores transaction data in a distributed shared global ledger. It is challenging to strike a balance between privacy protection and usefulness while sharing data. Moreover, the dynamic adjustment of blockchain data access rights is a challenging problem. To this end, this paper suggests a blockchain data-controlled sharing scheme based on proxy re-encryption. First, a proxy re-encryption algorithm is constructed based on SM2 and the blockchain. Blockchain data sharing can give businesses a secure way to store and share data. Since this network is decentralized, and data is transmitted across a peer-to-peer network under the protection of an unchangeable cryptographic signature. Blockchain makes it more difficult to alter or hack the data. The data-controlled sharing scheme uses proxy re-encryption to protect transaction data privacy and realize data security sharing. Secondly, a dynamic adjustment mechanism for user rights is proposed. Blockchain nodes divide labor and manage re-encryption key parameters separately to achieve user access rights determinism Update, the visibility of transaction data is dynamically adjusted. Finally, the performance and security evaluation demonstrate that this scheme can realize the dynamic sharing of blockchain data while protecting transaction privacy and has advantages in computing overhead, which is better applicable to the Controlled sharing of blockchain data. This research suggests a regulated blockchain-based data-sharing system that makes use of proxy re-encryption. They are developing a proxy re-encryption algorithm with SM2 in order to fully safeguard the privacy of transaction data and to achieve data access authority determination by controlling proxy re-encryption key parameters. It is suggested to employ a hybrid attribute-based proxy re-encryption method that enables the proxy server to change attribute-encrypted cypher texts into identity-based encrypted cypher texts so that users with limited resources can access the previously encrypted material.     

基于PXI Express总线的多通道数字化仪软件技术研究

针对各种数字化设备高采样率和高分辨率的测试需求,设计一种基于PXI Express总线的多通道数字化仪。该数字化仪开放性高,灵活性好,模块化强,广泛应用于测控领域中。结合数字化仪开发过程中所面临的关键问题及解决方案,重点从设备驱动程序、接口封装和应用软件三个方面进行分析阐述。首先,深入研究了KMDF设备驱动开发过程中几个关键问题,如配置空间访问、中断处理、DMA数据传输等的运行机制及实现方法;然后,以数字化仪应用需求为背景,阐述了采用.Net平台下三层体系架构的软件总体设计;最后,大量实验测试和结果分析表明,该数字化仪具有较强的可靠性和稳定性,达到预期技术要求和性能指标。     

Injection attack detection using machine learning for smart IoT applications

Smart cities are a rapidly growing IoT application. These smart cities mainly rely on wireless sensors to connect their different components (smart devices) together. Smart cities rely on the integration of IoT and 5G technologies, and this has created a demand for a massive IoT network of connected devices. The data traffic coming from indoor wireless networks (e.g., smart homes, smart hospitals, smart factories , or smart school buildings) contributes to over 80% of the total data traffic of the current IoT network. As smart cities and their applications grow, security and privacy challenges have become a major concern for billions of IoT smart devices. One reason for this could be the oversight of handling security issues of IoT devices by their manufacturers, which enables attackers to exploit the vulnerabilities in these devices by performing different types of attacks, e.g., DDoS and injection attacks. Intrusion detection is one way to detect and mitigate the risk of such attacks. In this paper, an intrusion detection method was proposed to detect injection attacks in IoT applications (e.g. smart cities). In this method, two types of feature selection techniques (constant removal and recursive feature elimination) were used and tested by a number of machine learning classifiers (i.e., SVM, Random Forest, and Decision Tree). The T-Test was conducted to evaluate the quality of this proposed feature selection method. Using the public dataset, AWID, the evaluation results showed that the decision tree classifier can be used to detect injection attacks with an accuracy of 99% using only 8 features, which were selected using the proposed feature selection method. Also, the comparison with the most related work showed the advantages of the proposed intrusion detection method.     

热定型过程织物无线温度记录仪研制

为了准确记录定型机热定型过程中的织物的实际温度及其变化情况,设计了一种基于无线数据传输热定型过程织物温度检测记录仪。该记录仪以PT100为温度检测传感器,以铁电存储器FM24V05为存储芯片,以STM8L152为主控芯片,实现了温度数据的读取及存储,选用SI4463为无线收发芯片,实现了数据的传输,并设计了无线充电模块,主体电路部分采用密闭隔热材料封装。经实验测定,该装置可以准确的采集热定型过程中移动织物温度的数据,并进行无线导出.解决了定型过程布匹温度数据不准确的问题,该数据还可用于定型过程的建模、分析及优化,具有较高的工程应用价值。     

New device architecture of a thermoelectric energy conversion for recovering low-quality heat

Low-quality heat is generally discarded for economic reasons; a low-cost energy conversion device considering price per watt, $/W, is required to recover this waste heat. Thin-film based thermoelectric devices could be a superior alternative for this purpose, based on their low material consumption; however, power generated in conventional thermoelectric device architecture is negligible due to the small temperature drop across the thin film. To overcome this challenge, we propose new device architecture, and demonstrate approximately 60 Kelvin temperature differences using a thick polymer nanocomposite. The temperature differences were achieved by separating the thermal path from the electrical path; whereas in conventional device architecture, both electrical charges and thermal energy share same path. We also applied this device to harvest body heat and confirmed its usability as an energy conversion device for recovering low-quality heat.     

基于串口转WiFi的物联网终端远程控制实现方法

随着物联网技术的高速发展,对同一无线局域网内的设备进行控制时,存在传输距离短、可移动性差等缺点。针对此问题,提出了一种物联网终端远程控制的实现方法,采用串口转WiFi模块,通过Socket模式下的透传机制,传统的串口设备能够无线接入到互网络中基于MQTT消息传输协议的服务器上,完成数据的接收和发送,从而使终端设备突破无线通信距离的限制,达到数据交互和远程控制的目的。实验结果表明该方法正确、可靠,可广泛应用于智能家居、工业控制等领域。     

超长周期慢引出主环磁铁电源控制系统设计

介绍了兰州重离子加速器冷却储存环（HIRFL-CSR）超长周期慢引出主环（CSRm）磁铁电源控制系统的设计。该系统采用基于高速以太网的分布式控制系统,选用了ARM+DSP结构的前端智能控制器,对整个运行周期的控制采用了分段处理的机制,解决了波形数据量过大而无法在前端控制器进行全波形存储的问题。该系统已经在加速器冷却储存环中通过了调试,满足了物理实验的要求。     

Memristor-based vector neural network architecture

Vector neural network(VNN) is one of the most important methods to process interval data.However,the VNN,which contains a great number of multiply-accumulate(MAC) operations,often adopts pure numerical calculation method,and thus is difficult to be miniaturized for the embedded applications.In this paper,we propose a memristor based vector-type backpropagation(MVTBP) architecture which utilizes memristive arrays to accelerate the MAC operations of interval data.Owing to the unique brain-like synaptic characteristics of memristive devices,e.g.,small size,low power consumption,and high integration density,the proposed architecture can be implemented with low area and power consumption cost and easily applied to embedded systems.The simulation results indicate that the proposed architecture has better identification performance and noise tolerance.When the device precision is 6 bits and the error deviation level(EDL) is 20%,the proposed architecture can achieve an identification rate,which is about 92% higher than that for interval-value testing sample and 81% higher than that for scalar-value testing sample.     

Emerging of two-dimensional materials in novel memristor

The rapid development of big-data analytics (BDA), internet of things (IoT) and artificial intelligent Technology (AI) demand outstanding electronic devices and systems with faster processing speed, lower power consumption, and smarter computer architecture. Memristor, as a promising Non-Volatile Memory (NVM) device, can effectively mimic biological synapse, and has been widely studied in recent years. The appearance and development of two-dimensional materials (2D material) accelerate and boost the progress of memristor systems owing to a bunch of the particularity of 2D material compared to conventional transition metal oxides (TMOs), therefore, 2D material-based memristors are called as new-generation intelligent memristors. In this review, the memristive (resistive switching) phenomena and the development of new-generation memristors are demonstrated involving grapheme (GR), transition-metal dichalcogenides (TMDs) and hexagonal boron nitride (h-BN) based memristors. Moreover, the related progress of memristive mechanisms is remarked.