基于微机噪音产生随机序列的方法研究

在进行微机电路噪声分析和研究小波分析在提取弱信号中的作用的基础上,研制了一种基于微机电路中的噪声信号工作的随机数发生器,对其进行了相关分析,并对一些关键实现技术作了介绍,采用NIST标准对其进行了测试,测试结果符合实验结果。满足信息安全技术的要求。     

A Novel Ensemble Learning Algorithm Based on D-S Evidence Theory for IoT Security

In the last decade, IoT has been widely used in smart cities, autonomous driving and Industry 4.0, which lead to improve efficiency, reliability, security and economic benefits. However, with the rapid development of new technologies, such as cognitive communication, cloud computing, quantum computing and big data, the IoT security is being confronted with a series of new threats and challenges. IoT device identification via Radio Frequency Fingerprinting (RFF) extracting from radio signals is a physical-layer method for IoT security. In physical-layer, RFF is a unique characteristic of IoT device themselves, which can difficultly be tampered. Just as people’s unique fingerprinting, different IoT devices exhibit different RFF which can be used for identification and authentication. In this paper, the structure of IoT device identification is proposed, the key technologies such as signal detection, RFF extraction, and classification model is discussed. Especially, based on the random forest and Dempster-Shafer evidence algorithm, a novel ensemble learning algorithm is proposed. Through theoretical modeling and experimental verification, the reliability and differentiability of RFF are extracted and verified, the classification result is shown under the real IoT device environments.     

新颖的音频信息隐藏算法

基于混沌映射和改进Patchwork算法的DWT（discrete wavelet transform）域音频信息隐藏技术,实现保密语音在音频信号中的隐藏与恢复。利用混沌序列保密性高和容易再生的特性,保证了算法的安全性;新颖的Patchwork算法,修改部分小波系数,使其统计特征产生相反方向偏移,实现保密语音码流的隐藏。混沌序列的使用与小波系数修改的隐蔽性,加强了算法的安全性;在保证隐藏量的同时,实现了隐藏信息的盲提取。实验表明,隐藏信息后载体音频SNR在50dB左右;在载体音频失真可容忍的情况下,提取的保密语音码流BER均小于0．1％,能够保证隐藏音频的听觉质量和隐藏信息的安全。     

Full-signature real-time corrosion detection of underground casingpipes

Corrosion monitoring and early detection of pits and wall thinning for casing pipes are considerably important to gas and petroleum industries since the frequently occurring corrosion at the internal or external parts of those steel casing pipes used in underground gas storage or oil fields causes production and environmental protection problems. In this paper, a new version of the direct current (dc) electromagnetic induction system is introduced in which a sensor system, based on the dc electromagnetic induction instrument, is coupled with an updated data acquisition system. Unlike the conventional dc induction instrument, the new system can achieve a full-signature logging response by providing all the measured flux leakage (FL) signals and eddy current (EC) signals to the computer logging system (CLS) on the surface. To transmit the information represented by large amounts of data acquired by downhole instruments to the CLS on the surface, a wavelet data compression technique has been incorporated. A VLSI integrated circuit (IC) which realizes the wavelet transform has been designed so that the real-time mode can be achieved during the logging operation. The circuit has been designed using CMOS n-well 2-μm technology and has been fabricated by MOSIS     

浅谈密码学与网络信息安全技术

当今社会,信息网络国际化、社会化、开放化和个人化的特点决定了它在给人们提供高效率、高效益、高质量的信息共享的同时,也投下了不安全的阴影。随着政府和人民对网络环境和网络资源依赖程度的不断加深,信息泄露、黑客入侵、计算机病毒传播甚至于威胁国家安全的问题会出现得越来越多。作为信息网络安全的关键技术——密码技术,近年来空前活跃,由于计算机运算速度的不断提高,各种密钥算法也面临着新的密码体制,众多密码新技术正处于不断探索中。     

拟态防御技术结合软件多样化在软件安全产业中的应用

随着互联网的飞速发展,计算机软件全球化的进程不断推进。大量相同软件安装在数以万计的计算机中,容易导致黑客利用软件的漏洞,攻击安装了该软件的所有计算机。传统的软件安全措施是依靠对漏洞进行修补,其只能起到亡羊补牢的作用。软件多样化技术可以使这种情况得到缓解,但其并没有从根本上消除漏洞带来的威胁。本文提出将拟态防御技术与软件多样化技术相结合应用于软件安全产业,可以消除漏洞带来的威胁。     

Review of superconducting electronics

This review will sketch the present state of affairs in applications of Josephson junctions and SQUIDs to: magnetometry, DC and RF metrology, detection and amplification of electromagnetic signals, frequency metrology, noise thermometry and computers. It will also mention recent progress in super-stable oscillators using superconducting resonant circuits, pulse transmission lines, and thin-film deviees to detect radiation or charged particles. Many of these topics are maturing nicely.     

Effect of external periodic signals and electromagnetic radiation on autaptic regulation of neuronal firing

An improved Hindmarsh–Rose (HR) neuron model, where the memristor is a bridge between membrane potential and magnetic flux, can be used to investigate the effect of periodic signals on autaptic regulation of neurons under electromagnetic radiation. Based on the improved HR model driven by periodic high–low‐frequency current and electromagnetic radiation, the responses of electrical autaptic regulation with diverse high–low‐frequency signals are investigated using bifurcation analysis. It is found that the electrical modes of neurons are determined by the selecting parameters of both periodic high and low‐frequency current and electromagnetic radiation, and the Hamiltonian energy depends on the neuronal firing modes. The effects of Gaussian white noise on the membrane potential are discussed using numerical simulations. It is demonstrated that external high–low‐frequency stimulus plays a significant role in the autaptic regulation of neural firing mode, and the electrical mode of neurons can be affected by the angular frequency of both high–low‐frequency forcing current and electromagnetic radiation. The mechanism of neuronal firing regulated by high–low‐frequency signal and electromagnetic radiation discussed here could be applied to research neuronal networks and synchronisation modes.Inspec keywords: bioelectric potentials, neural nets, bifurcation, synchronisation, memristors, neurophysiology, numerical analysis, white noiseOther keywords: synchronisation modes, external periodic signals, electromagnetic radiation, improved Hindmarsh–Rose neuron model, membrane potential, periodic high–low‐frequency current, electrical autaptic regulation, diverse high–low‐frequency signals, neuronal firing modes, external high–low‐frequency stimulus, high–low‐frequency forcing current, high–low‐frequency signal, research neuronal networks     

Heuristic algorithms for maximising the total profit of end-of-life computer remanufacturing

Recently the optimisation of end-of-life (EOL) computer remanufacturing has been highlighted since a big amount of used computers have been disposed of every year. Each part inspected after disassembling EOL computers can have various EOL options such as reuse, repair, reconditioning and so on. Depending on EOL options, recovered values and costs of parts will be different. Hence, in order to maximise the profit of remanufactured computers, it is important to develop the method as to how to decide the EOL options of computer parts. To this end, this study deals with a decision-making problem to select the best EOL option policy of the computer parts for maximising the total profit of computer remanufacturing considering its incurred costs and demand of remanufactured computers during multiple production periods. In particular, to maximise the total profit, the conditional repair option is newly proposed. To resolve the problem, a genetic search algorithm and an ant colony search algorithm have been developed. Computational experiments have carried out to evaluate the algorithms and the proposed conditional repair option.     

基于故障树的计算机安全性分析模型

提出了通过分析计算机系统的资源实体、访问者权限、安全需求和弱点等安全属性,按照不同的安全需求构造出安全故障树来直观地反映攻击者可能选取的攻击手段的安全状况评价方法;分析安全故障树,使用潜在攻击路径和系统安全失效概率从定性和定量两个方面表达计算机系统的安全状况,为系统的安全改进提供指导和建议。     

Blockchain Technology Based Information Classification Management Service

Hyper-connectivity in Industry 4.0 has resulted in not only a rapid increase in the amount of information, but also the expansion of areas and assets to be protected. In terms of information security, it has led to an enormous economic cost due to the various and numerous security solutions used in protecting the increased assets. Also, it has caused difficulties in managing those issues due to reasons such as mutual interference, countless security events and logs’ data, etc. Within this security environment, an organization should identify and classify assets based on the value of data and their security perspective, and then apply appropriate protection measures according to the assets’ security classification for effective security management. But there are still difficulties stemming from the need to manage numerous security solutions in order to protect the classified assets. In this paper, we propose an information classification management service based on blockchain, which presents and uses a model of the value of data and the security perspective. It records transactions of classifying assets and managing assets by each class in a distributed ledger of blockchain. The proposed service reduces assets to be protected and security solutions to be applied, and provides security measures at the platform level rather than individual security solutions, by using blockchain. In the rapidly changing security environment of Industry 4.0, this proposed service enables economic security, provides a new integrated security platform, and demonstrates service value.     

A Weighted Threshold Secret Sharing Scheme for Remote Sensing Images Based on Chinese Remainder Theorem

The recent advances in remote sensing and computer techniques give birth to the explosive growth of remote sensing images. The emergence of cloud storage has brought new opportunities for storage and management of massive remote sensing images with its large storage space, cost savings. However, the openness of cloud brings challenges for image data security. In this paper, we propose a weighted image sharing scheme to ensure the security of remote sensing in cloud environment, which takes the weights of participants (i.e., cloud service providers) into consideration. An extended Mignotte sequence is constructed according to the weights of participants, and we can generate image shadow shares based on the hash value which can be obtained from gray value of remote sensing images. Then we store the shadows in every cloud service provider, respectively. At last, we restore the remote sensing image based on the Chinese Remainder Theorem. Experimental results show the proposed scheme can effectively realize the secure storage of remote sensing images in the cloud. The experiment also shows that no matter weight values, each service providers only needs to save one share, which simplifies the management and usage, it also reduces the transmission of secret information, strengthens the security and practicality of this scheme.     

Optical image encryption based on compressive sensing and chaos in the fractional Fourier domain

We propose a novel image encryption algorithm based on compressive sensing (CS) and chaos in the fractional Fourier domain. The original image is dimensionality reduction measured using CS. The measured values are then encrypted using chaotic-based double-random-phase encoding technique in the fractional Fourier transform domain. The measurement matrix and the random-phase masks used in the encryption process are formed from pseudo-random sequences generated by the chaotic map. In this proposed algorithm, the final result is compressed and encrypted. The proposed cryptosystem decreases the volume of data to be transmitted and simplifies the keys for distribution simultaneously. Numerical experiments verify the validity and security of the proposed algorithm.     

Performance estimation for maximum-likelihood detection forchannels with transition noise

Transition noise is known to be a major cause of errors for high density magnetic recording. This noise is signal dependent and can be modeled as multiplicative noise in a linear channel model. A maximum-likelihood algorithm was considered for detection of signals in such noise. In this work, the performance of the detector, based on this algorithm, is compared to the traditional Viterbi algorithm (VA) and a modified Viterbi algorithm (MVA) by computer simulations. Results show an improvement of up to 5 dB In signal-to-noise-ratio (SNR) under typical conditions with a reasonable complexity     

岩石破裂电磁辐射监测系统研制

为满足有关岩石破裂电磁辐射研究的需要,研制一套电磁辐射监测系统。该系统由电磁感应探头、信号调理电路和数据采集系统组成,可对频率在1kHz~1MHz内的微弱电磁场进行监测。电磁感应探头可感应空间中某一方向的电磁场变化,并将其转换成电信号;信号调理电路对探头输出的电信号进行放大、滤波,并实现放大滤波电路与计算机的电气隔离;数据采集软件基于LabVIEW编写,用于对监测到的信号进行记录和显示。实验结果表明：该系统性能稳定,操作简便,能够有效地监测岩石破裂所产生的电磁辐射,对岩石、混凝土等材料的力-电-磁研究具有重要意义。     

A Framework for Systematic Classification of Assets for Security Testing

Over the last decade, a significant increase has been observed in the use of web-based Information systems that process sensitive information, e.g., personal, financial, medical. With this increased use, the security of such systems became a crucial aspect to ensure safety, integrity and authenticity of the data. To achieve the objectives of data safety, security testing is performed. However, with growth and diversity of information systems, it is challenging to apply security testing for each and every system. Therefore, it is important to classify the assets based on their required level of security using an appropriate technique. In this paper, we propose an asset security classification technique to classify the System Under Test (SUT) based on various factors such as system exposure, data criticality and security requirements. We perform an extensive evaluation of our technique on a sample of 451 information systems. Further, we use security testing on a sample extracted from the resulting prioritized systems to investigate the presence of vulnerabilities. Our technique achieved promising results of successfully assigning security levels to various assets in the tested environments and also found several vulnerabilities in them.     

Enhancing Blockchain Security Using Ripple Consensus Algorithm

In the development of technology in various fields like big data analysis, data mining, big data, cloud computing, and blockchain technology, security become more constrained. Blockchain is used in providing security by encrypting the sharing of information. Blockchain is applied in the peer-to-peer (P2P) network and it has a decentralized ledger. Providing security against unauthorized breaches in the distributed network is required. To detect unauthorized breaches, there are numerous techniques were developed and those techniques are inefficient and have poor data integrity. Hence, a novel technique needs to be implemented to tackle the new breaches in the distributed network. This paper, proposed a hybrid technique of two fish with a ripple consensus algorithm (TF-RC). To improve the detection time and security, this paper uses efficient transmission of data in the distributed network. The experimental analysis of TF-RC by using the metric measures of performance in terms of latency, throughput, energy efficiency and it produced better performance.     

计算机电磁辐射的测量

目的 介绍计算机系统电磁辐射测量的条件要求和测试方法。方法 给出计算机系统辐射发射的理论模型。详细论述了测量条件要求和测试方法，并按美国联邦通信委员会（简称FCC）规定测试。结果与结论 测试结果的真实性和可重复性得到了有效保证，这些要求和方法适用于计算机系统，计算机以及与计算机主机连用的外部设备的试验，对其他电子设备辐射测量，本文的原理和方法同样具有借鉴意义。     

区域环境电磁监测与信号识别系统方案研究

针对侦察活动中大量使用类似通信信号的伪信号和进行科学实验时各种信号存在的电磁泄漏问题,为满足电磁环境监测的实际需要,运用LabWindows/CVI设计一种新型的区域环境电磁监测与识别系统。系统通过最新的信号混合域分析方法,对一定范围内的区域进行监测,实现仪器控制、数据采集、系统校准、信号识别、结果处理与保存等功能,具有准确性、易用性、便携性及可扩展性,可以高效科学地完成电磁环境监测工作,具有一定的实用性和推广价值。     

超声声表面波检测信号时差的倒频谱分析

采用超声表面波检测激光熔覆层残余应力时, 表面波检测信号声时差的精确读取非常关键。传统的相关法无法精确地辨别表面超声波的声时差。文中提出基于复数倒频谱的表面超声波声时差辨别算法,采用该算法对计算机模拟信号和实际检测信号做了声时差分析,并与相关法的时间分析结果做了对比。计算机模拟和实验结果均表明,倒频谱分析方法是一种精度高,具有一定抗干扰能力的声时差估计算法。最后结合表面超声波检测信号的特点,从理论上分析了倒频谱分析方法优于相关法的原因。