A Secure Hardware Implementation for Elliptic Curve Digital Signature Algorithm

Since the end of the 1990s,cryptosystems implemented on smart cards have had to deal with two main categories of attacks:side-channel attacks and fault injection attacks.Countermeasures have been developed and validated against these two types of attacks,taking into account a well-defined attacker model.This work focuses on small vulnerabilities and countermeasures related to the Elliptic Curve Digital Signature Algorithm(ECDSA)algorithm.The work done in this paper focuses on protecting the ECDSA algorithm against fault-injection attacks.More precisely,we are interested in the countermeasures of scalar multiplication in the body of the elliptic curves to protect against attacks concerning only a few bits of secret may be sufficient to recover the private key.ECDSA can be implemented in different ways,in software or via dedicated hardware or a mix of both.Many different architectures are therefore possible to implement an ECDSA-based system.For this reason,this work focuses mainly on the hardware implementation of the digital signature ECDSA.In addition,the proposed ECDSA architecture with and without fault detection for the scalar multiplication have been implemented on Xilinxfield programmable gate arrays(FPGA)platform(Virtex-5).Our implementation results have been compared and discussed.Our area,frequency,area overhead and frequency degradation have been compared and it is shown that the proposed architecture of ECDSA with fault detection for the scalar multiplication allows a trade-off between the hardware overhead and the security of the ECDSA.

Fault Pattern Diagnosis and Classification in Sensor Nodes Using Fall Curve

The rapid expansion of Internet of Things(IoT)devices deploys various sensors in different applications like homes,cities and offices.IoT applications depend upon the accuracy of sensor data.So,it is necessary to predict faults in the sensor and isolate their cause.A novel primitive technique named fall curve is presented in this paper which characterizes sensor faults.This technique identifies the faulty sensor and determines the correct working of the sensor.Different sources of sensor faults are explained in detail whereas various faults that occurred in sensor nodes available in IoT devices are also presented in tabular form.Fault prediction in digital and analog sensors along with methods of sensor fault prediction are described.There are several advantages and disadvantages of sensor fault prediction methods and the fall curve technique.So,some solutions are provided to overcome the limitations of the fall curve technique.In this paper,a bibliometric analysis is carried out to visually analyze 63 papers fetched from the Scopus database for the past five years.Its novelty is to predict a fault before its occurrence by looking at the fall curve.The sensing of current flow in devices is important to prevent a major loss.So,the fall curves of ACS712 current sensors configured on different devices are drawn for predicting faulty or non-faulty devices.The analysis result proved that if any of the current sensors gets faulty,then the fall curve will differ and the value will immediately drop to zero.Various evaluation metrics for fault prediction are also described in this paper.At last,this paper also addresses some possible open research issues which are important to deal with false IoT sensor data.

Optical Fibre Communication Feature Analysis and Small Sample Fault Diagnosis Based on VMD-FE and Fuzzy Clustering

To solve the problems of a few optical fibre line fault samples and the inefficiency of manual communication optical fibre fault diagnosis,this paper proposes a communication optical fibre fault diagnosis model based on variational modal decomposition(VMD),fuzzy entropy(FE)and fuzzy clustering(FC).Firstly,based on the OTDR curve data collected in the field,VMD is used to extract the different modal components(IMF)of the original signal and calculate the fuzzy entropy(FE)values of different components to characterize the subtle differences between them.The fuzzy entropy of each curve is used as the feature vector,which in turn constructs the communication optical fibre feature vector matrix,and the fuzzy clustering algorithm is used to achieve fault diagnosis of faulty optical fibre.The VMD-FE combination can extract subtle differences in features,and the fuzzy clustering algorithm does not require sample training.The experimental results show that the model in this paper has high accuracy and is relevant to the maintenance of communication optical fibre when compared with existing feature extraction models and traditional machine learning models.

A fault recognition method based on clustering linear regression

Aiming at the problems of low accuracy,long time consumption,and failure to obtain quantita-tive fault identification results of existing automatic fault identification technic,a fault recognition method based on clustering linear regression is proposed.Firstly,Hough transform is used to detect the line segment of the enhanced image obtained by the coherence cube algorithm.Secondly,the endpoint of the line segment detected by Hough transform is taken as the key point,and the adaptive clustering linear regression algorithm is used to cluster the key points adaptively according to the lin-ear relationship between them.Finally,a fault is generated from each category of key points based on least squares curve fitting method to realize fault identification.To verify the feasibility and pro-gressiveness of the proposed method,it is compared with the traditional method and the latest meth-od on the actual seismic data through experiments,and the effectiveness of the proposed method is verified by the experimental results on the actual seismic data.

近断层脉冲型地震动下调谐黏滞质量阻尼器减震结构易损性分析

选择典型脉冲型近断层地震动记录分别对一安装有调谐黏滞质量阻尼器(tuned viscous mass damper,TVMD)、黏滞阻尼器(viscous damper, VD)和无阻尼器的6层3跨钢框架结构进行增量动力分析,进而基于增量动力分析结果得到3种结构不同损伤状态的易损性曲线。易损性分析结果对比表明:随着惯容单元的引入,减震结构可靠性显著提升;相较于相同阻尼的VD,TVMD可以更有效地提升结构的抗震性能,减小结构在不同损伤状态下的失效概率。随着质量比的增加,TVMD减震结构在不同损伤状态下的失效概率减小,TVMD对结构性能状态的提升不会随非线性的增加而减小,且在结构经历弹性、弹塑性直至倒塌的整个过程中减震控制性能发挥稳定。进一步选取3组不同脉冲周期的近断层地震动记录对三种结构进行时程分析,讨论TVMD在不同脉冲周期近断层地震动下的减震控制效果。结果表明,在近断层脉冲型地震动作用下,TVMD并不都会实现阻尼单元“阻尼增效”,阻尼器的性能发挥与地震动的特性有关。相较于VD,当T_1/T_p≥2时,TVMD可以更好地减少结构能量输入但其能量耗散效率低于VD,不能实现“阻尼增效”;当T_1/T_p <2时,TVMD可以减小结构残余位移,具有更优的减少能量输入和增大能量耗散效率的双重效应,体现了惯容的“阻尼增效”。

库车坳陷大北地区巴什基奇克组隐性断层特征与发育模式

库车坳陷作为塔里木盆地新生代再生前陆盆地,盐下叠瓦状构造楔发育,多个断片在巴什基奇克组发现了天然气藏。随着气藏的不断开发,多个气藏发生不同程度水侵,前人研究表明,隐性断层作为沟通底水或边水的高渗透通道,是导致水侵的主要原因,能否有效识别隐性断层直接影响气藏开发效果。然而,由于膏盐岩层的影响,盐下构造的地震分辨率较低,使用地震属性方法识别隐性断层难度较大。本次以大北地区为例,采用地质与地球物理相结合的思路,在钻井与地震属性方法识别的3条隐性断层基础上,通过断距—距离曲线分析主干逆冲断裂的分段性,并结合应力分析,建立了两种隐性断层发育模式。结果表明隐性断层的形成受局部应力场和区域应力场的共同控制。主干逆冲断层构造转换带是隐性断层优势发育位置,随着断层发生分段生长连接,构造转换带将由挤压应力状态逐渐变为走滑应力状态,形成的隐性断层走向也将发生变化。区域应力的走滑分量则是控制北东向隐性断层远离主干边界断层后走向,维持稳定的另一重要因素。本次研究成果将为库车坳陷隐性断层的识别和预测提供重要的地质约束。

考虑电容投切扰动的配电网高阻接地故障检测方法

高阻接地故障的准确、可靠检测是配电网故障处理的难点,正常的电容投切操作可对其产生干扰。针对这一问题,文中提出了一种基于零序李萨如曲线分析的高阻接地故障抗扰检测方法。首先,理论推导了高阻接地故障与电容投切扰动的零序电气量,二者在传统时频域特征角度无规律性差异,从而明确了干扰原因;进一步,将零序电流、电压波形重构为零序李萨如曲线,提出了基于数学形态学理论的李萨如曲线轨迹形状畸变复杂度量化指标,并结合零序李萨如曲线面积概率分布规律设计自适应启动判据,给出了噪声场景下高阻接地故障的抗扰检测方法;最后,利用配电网电磁暂态仿真算例和真型故障试验验证了所提方法的有效性和可靠性。

中低速磁浮车辆悬浮故障工况动力学分析

为研究中低速磁浮车辆电磁铁失效失去悬浮力时的故障工况对磁浮车辆动力学性能的影响,建立三悬浮架中低速磁浮车辆动力学模型,对直线运行和曲线通过性能的各项动态指标进行仿真分析。结果表明:电磁铁失效故障对平稳性指标和导向间隙影响较小,对悬浮间隙、悬浮模块点头角和通过速度影响较大;发生电磁铁失效故障时,直线路段需要限速60 km/h运行,R100曲线路段需要限速38 km/h运行。

一种基于CatBoost优化的光伏阵列故障诊断模型

大部分光伏电站地处偏僻、地形复杂的区域,受到外界环境的影响,易发生各种故障.而传统的光伏阵列故障诊断方法存在精度不高以及光伏数据利用率低等问题.针对以上问题,本文先是通过引入Levy飞行策略和步长因子动态调整策略改进麻雀搜索算法(Sparrow Search Algorithm,SSA),降低SSA算法陷入局部最优的风险,提升SSA算法的寻优能力.然后采用改进的Levy步长调整麻雀搜索算法(Levy Adjustment Sparrow Search Algorithm,LASSA)对CatBoost模型关键超参数进行寻优,提出了一种基于CatBoost并以LASSA为优化策略的光伏阵列故障诊断模型LASSA-CatBoost,以实现光伏阵列的短路、开路、老化和阴影遮挡故障的精确诊断.实验结果表明,LASSA-CatBoost模型的故障诊断准确率为99.7%,相较于优化前的CatBoost模型,准确率提高了3.6%.与现有的光伏阵列故障诊断模型相比,LASSA-CatBoost模型的准确性和稳定性更高.

基于杂散磁场信号螺旋曲线投影变换与ResNeXt-18的永磁直线电机偏心故障诊断

该文提出一种基于杂散磁通密度信号立体螺旋曲线投影面变换与ResNeXt-18深度学习框架相结合的方法,以实现永磁同步直线电机(PMSLM)偏心故障的非侵入式诊断。首先,建立PMSLM有限元模型,分析静态和动态偏心故障下的电机内部与杂散磁场分布。采用隧道磁阻效应(TMR)传感器并设计连接件,实现传感器与电机动子一体化设计,对电机外部杂散磁通密度信号进行实时非接触式测量。其次,引入立体螺旋曲线变换(TDSCT)信号处理算法,对电机偏心故障下的外部杂散磁通密度一维信号进行三维调制,并通过对多视角下二维投影面图像的拼接融合,实现故障特征的可视化增强。然后,引用深度学习ResNeXt-18分类框架,通过对杂散磁通密度信号二维投影面数据集的训练学习,实现偏心故障的定量精细化诊断,精度高达99.4%。与Xception,ResNet-18,GoogLeNet和CNN的对比实验表明,ResNeXt-18具有更高的诊断精度和鲁棒性。最后,搭建PMSLM样机实验平台,验证了该文所提方法的有效性。

潍坊地区地层频散特征与分析研究

潍坊市南部山区第四系厚度较薄,北部地区为冲洪积平原,第四系厚度较大,由南向北逐渐增厚,且潍坊市北部为滨海咸水入侵区,传统的物探方法,尤其是电法、电磁法,在该区开展工作效果欠佳。本次研究借鉴地震勘探多次覆盖观测系统的思路,利用线形台阵多次覆盖的高效微动探测技术,对潍坊市不同地层的面波频散特征进行分析研究,并根据频散特征差异对地层结构进行了划分。研究结果表明:潍坊市南部浅覆盖区频散曲线频点范围较广,整体呈表层低速中深层迅速升高型;潍坊市北部厚覆盖区频散曲线频点范围相对较窄,整体呈表中深缓慢升高低速型;古河道发育地层频散曲线出现无规律的跳动或“之”字形拐点,整体为深层波速最高中部低速型。

接触网坠砣补偿器运维特性研究

坠砣补偿器是电气化铁路接触网系统中的关键设备,对现有接触网坠砣补偿器进行简要介绍,进一步对坠砣补偿器安装曲线绘制方法进行分析,在此基础上,对坠砣补偿器b值背后所可能反映出的故障现象进行思考和反思,并对坠砣补偿器b值调整方法进行总结,得出一套完备且科学的作业方法,以提高修后质量,降低维修人员的工作量。

基于承载分析的液压支架故障处理

基于综采工作面液压支架工作状态曲线分析,提出通过电液控制系统生成变化曲线,分析液压支架在对顶板承载过程中出现的故障种类,为液压支架故障处理及检修维护提供支持。研究表明:液压支架工作状态曲线能够很好地反映出支架故障信息,通过对立柱压力变化曲线分析,得出故障信息,使液压支架故障处理更高效。

基于迁移学习的光伏阵列复合故障诊断研究

针对户外运行的光伏阵列常见的复合故障问题,提出了一种融合残差网络与视觉Transformer的混合网络模型,并使用迁移学习方法对其优化,以提高故障诊断模型在复合故障场景下的可靠性。首先,从光伏阵列的静态I-V曲线和环境参数中提取有效特征作为输入,然后,利用仿真数据进行预训练,最后,通过迁移学习验证模型在诊断真实实验数据时的可靠性。实验结果表明,该混合模型在应对复合故障场景时具有较高的收敛速度和准确率。

Crustal structure and accurate hypocenter determination along the Longmenshan fault zone

A P and S wave velocity model is obtained for the crust in the region along the Longmenshan fault zone, Sichuan Province, China, by using data from a refraction profiling survey carried out in this region and those from local earthquakes. 202 local earthquakes along the fault zone are based on this velocity model, location errors being estimated to be about 1.5 km. The present relocations fairly improved the accuracy of hypocenter locations for earthquakes in this area, which is recognized from small scatter of data in the arrival time distance diagram compared with that for the original locations in the Earthquake Catalogue of Sichuan Seismic Network. The obtained hypocenter distribution shows that shallow earthquakes, confined to the upper crust in the depth range from 3 km to 22 km, are actively occurring along the main fault of the Longmenshan fault zone. The velocity model and the location method are presently used quite effective for precisely locating local earthquakes such as those in Sichuan Province. Installation of these with the real time processing system developed by Tohoku University in the Sichuan Telemetered Seismic Network would help to improve the location accuracy of events beneath the network.

Concealed fault analysis based on the CT projection matrix

This paper proposes the concept of projection curves based on the theory of CT image reconstruction to probe the internal structure of the working panel prior to formal mining of the working panel.As well as reducing costs,this method provides safe and efficient excavation of the working panel.According to the results of the numerical model and the actual working panel,the new method has been proven to be accurate in detecting the location of the fault that extends into the face.Concealed faults of the internal working panel,as well as the start and end points of the fault,can be detected by this method.Engineering practice has proven that the method is highly reliable,has a highly decisive impact on faults for coal mining,and can be used to guide the safe mining of the working panel.

Fault Tolerant Approach for Data Encryption and Digital Signature Based on ECC System

An integrated fault tolerant approach for data encryption and digitalsignature based on elliptic curve cryptography is proposed. Phis approach allows the receiver toverify the sender's identity and can simultaneously deal with error detection and data correction.Up to three errors in our approach can be detected and corrected. This approach has at least thesame security as that based on RSA system, but smaller keys to achieve the same level of security.Our approach is more efficient than the known ones and more suited for limited environments likepersonal digital assistants (PDAs), mobile phones and smart cards without RSA co-processors.

Compatibility of the Support System Consisting of Yielding Elements and Shotcrete Lining in Highly Faulted Grounds

The design procedure is made for a mine shaft where permanent underground facilities are interconnected. The highly faulted grounds were identified using empirical and semi-empirical theories. Furthermore, the behavior types are presented. This paper presents excavation and support methods in such ground conditions and the calculations results show that the installation of the yielding elements have an effect on support elements and prevent shotcrete damage during the curing stage. Different numerical analyses carried out showed that, with the yielding elements installed, the total displacements increase but the final axial force reduces, and therefore, the characteristic compressive strength of shotcrete is not exceeded. The calculation results of ground loads and displacements on the designed support system are presented with a 3D numerical geo-mechanical model adopted for highly faulted ground surrounding deeper complex underground structures.

基于改进层次分析法的多级电压暂降严重程度评估

准确评估多级电压暂降的严重程度对敏感设备的稳定运行及电压暂降治理具有重要意义。提出了一种基于改进层次分析法的多级电压暂降严重程度评估方法。首先,分析了瞬时性故障和永久性故障下重合闸相应动作过程的多级电压暂降波形。然后,运用权值函数法求出各级暂降的严重程度。基于过程免疫时间的特性,刻画出敏感设备的多级电压暂降过程免疫时间(process immunity time,PIT)特性曲线。利用各级暂降的关联性和严重程度指标值对层次分析法进行改进,确定了各级暂降的权重,实现了多级电压暂降严重程度的量化评估。最后,采用改造后的IEEE30节点系统进行仿真验证。结果表明,所提方法合理且有效,减少了评估结果的主观性,为敏感设备多级电压暂降的评估和治理提供依据。

ZDJ9型道岔转辙机故障分析处理

道岔转辙机是信号系统关键设备,对行车安全起着至关重要的作用。转辙机故障造成列车晚点,影响正常行车、客运组织,其故障处理效率直接影响运营效率。以ZDJ9型道岔转辙机故障处理为例,分析监测曲线形成、故障判断方法及处理步骤。