SecMVX:Analysis on the Vulnerability of Multi-Variant Execution

As an active defenses technique,multivariant execution(MVX)can detect attacks by monitoring the consistency of heterogeneous variants with parallel execution.Compared with patch-style passive defense,MVX can defend against known and even unknown vulnerability-based attacks without relying on attack feature information.However,variants generated with software diversity technologies will introduce new vulnerabilities when they execute in parallel.First,we analyze the security of MVX theory from the perspective of formal description.Then we summarize the general forms and techniques for attacks against MVX,and analyze the new vulnerabilities arising from the combination of variant generation technologies.We propose SecMVX,a secure MVX architecture and variant generation technology.Experimental evaluations based on CVEs and SPEC 2006 benchmark show that SecMVX introduces 11.29%of the average time overhead,and avoids vulnerabilities caused by the improper combination of variant generation technologies while keeping the defensive ability of MVX.

Strategic Planning for Equitable RWIS Implementation:A Comprehensive Study Incorporating a Multi-variable Semivariogram Model

This paper extends the previously developed method of optimizing Road Weather Information Systems(RWIS)station placement by unveiling a sophisticated multi-variable semivariogram model that concurrently considers multiple vital road weather variables.Previous research primarily centered on single-variable analysis focusing on road surface temperature(RST).The study bridges this oversight by introducing a framework that integrates multiple critical weather variables into the RWIS location allocation framework.This novel approach ensures balanced and equitable RWIS distribution across zones and aligns the network with areas both prone to traffic accidents and areas of high uncertainty.To demonstrate the effectiveness of this refinement,the authors applied the framework to Maine’s existing RWIS network,conducted a gap analysis through varying planning scenarios and generated optimal solutions using a heuristic optimization algorithm.The analysis identified areas that would benefit most from additional RWIS stations and guided optimal resource utilization across different road types and priority locations.A sensitivity analysis was also performed to evaluate the effect of different weightings for weather and traffic factors on the selection of optimal locations.The location solutions generated have been adopted by MaineDOT for future implementations,attesting to the model’s practicality and signifying an important advancement for more effective management of road weather conditions.

CON-MVX:一种基于容器技术的多变体执行系统

多变体执行是一种网络安全防御技术,其利用软件多样性生成等价异构的执行体,将程序输入分发至多个执行体并行执行,通过监控和比较执行体的状态来达到攻击检测的目的。相较于传统的补丁式被动防御技术,多变体执行不依赖于具体的攻击威胁特征进行分析,而是通过构建系统的内生安全能力来对大多数已知、甚至未知的漏洞做出有效防御。近年来,多变体执行技术在不断改进和完善,但是误报问题是制约其发展的主要因素。本文针对多变体执行产生误报的原因进行了详细分析,并在此基础上提出利用容器技术实现多变体执行系统在解决误报问题上的优势。为提升多变体执行技术的可用性,本文设计并实现了一种基于容器技术的多变体执行系统CON-MVX,有效解决传统多变体执行系统的误报问题。CON-MVX利用多个经过运行时随机化技术构建的异构容器作为执行体,使用可重构的模块化组件和独立的容器管理工具对容器执行体进行编排管理,建立进程间监控器CGMon,在内核层级实现对多个执行体的输入同步和输出裁决。同时,为满足与客户端良好交互性,建立中继端口策略,保证系统运行状态的正常反馈。实验结果表明, CON-MVX在保证安全能力的前提下,能有效降低多变体执行系统的误报率,在双冗余度执行条件下使用SPEC CPU 2006测试集测试时,系统带来的平均额外性能损耗不超过15%。

面向容器级多变体的Mimicveth网卡设计与实现

聚焦于容器级多变体执行(MVX)过程,针对容器级多变体系统分发时存在容器不能一对多通信、报文信息不匹配和TCP协议握手失败的问题,以及表决时存在报文时序乱序和报文分段分片问题,提出一种基于Mimicveth网卡的多变体系统网络输入输出(I/O)分发表决方案。该Mimicveth网卡为分发代理、执行体、表决器之间建立一对多双向传输通道。实验验证,依托该Mimicveth网卡能够有效实现容器级多变体系统分发和表决,改善容器级多变体系统可用性,为后续面向容器的多变体系统研究发展提供了原型基础。

高可靠信息系统非相似冗余架构中的执行体同步技术

非相似冗余架构被广泛使用到信息系统中,提高系统的安全性和可靠性。非相似冗余架构中的执行体之间存在差异,当系统正常工作时,执行体表现一致,但在面对恶意攻击行为时,执行体会表现出不一致。架构通过比较执行体的表现监控系统、感知威胁,从而提升系统安全可靠性。执行体的同步监控,是所有非相似冗余架构都需要解决的难题。目前没有针对同步技术比较系统性的描述和总结。该文首先对执行体同步问题进行了抽象建模,然后提出基于同步点的同步技术分类方法,并分别对每种技术的基本方式、流行度、优缺点进行了总结。该文还提出了影响同步效果的3个重要指标:同步点、误报率和性能,同时给出了同步技术的数学模型,可用于同步技术的设计评估。最后,结合网络弹性工程领域和软件定义晶上系统领域的发展,指出了同步技术未来的发展潜力和可能的发展方向。

Stability analysis for nonlinear multi-variable delay perturbation problems

This paper discusses the stability of theoretical solutions for nonlinear multi-variable delay perturbation problems (MVDPP) of the form x′(t)=f(x(t),x(t-τ 1(t)),...,x(t-τ m(t)),y(t),y(t-τ 1(t)),...,y(t-τ m(t))), and εy′(t)=g(x(t),x(t-τ 1(t)),...,x(t-τ m(t)),y(t),y(t-τ 1(t)),...,y(t-τ m(t))), where 0<ε1. A sufficient condition of stability for the systems is obtained. Additionally we prove the numerical solutions of the implicit Euler method are stable under this condition.

MLST技术分析中国烟草野火病菌遗传多样性

明确烟草野火病菌多位点序列分型(MLST)情况,能为制订有效防治措施和选育品种提供强力技术支撑,并为病菌的生物学特性研究提供新视角。从湖南、重庆等5个产烟省(市)烟草生产区采集烟草野火病样,组织分离并鉴定,应用MLST分型,筛选管家基因,分析供试菌株遗传多样性。结果表明,从湖南等5个产烟省(市)分离获得烟草野火病菌144株,筛选得到Pgi、Pfk和Gap 3个管家基因,共获得92个ST型。以Pgi基因为标准,供试菌株可分出亚群5个,单一群4个,亚群1和亚群2菌株数量较多,亚群1菌株来自5个产烟省(市),此亚群的ST43属于中国主要种群。说明中国烟草野火病菌遗传多态性丰富,烟草品种与病菌组群间不存在关联性。

基于多源异构数据的飞机总装集成测试

本文指出民机总装集成测试生产线集成了操作人员、工装设备、生产物料、工艺路径、生产环境等多源异构生产信息,是典型的复杂信息系统;对飞机生产线的建模仿真需要反映工程实际变量,综合考虑工艺技术和生产管理多个维度。为此,本文提出了基于5M1E的异构数据多层网络建模框架,将生产要素和生产实体分层解耦,工艺过程直接和生产要素相关联,生产要素再通过有向连边具象化为生产所需的实体。该模型建模方式更为直观,便于同时表达工艺过程对于人、机、料、环等因素的依赖。对于测试工艺过程,通过搭建DDS网络、解析飞机数据网络、获取飞机实时状态,保证了总装集成测试的有效。

Combined model based on optimized multi-variable grey model and multiple linear regression

The construction method of background value is improved in the original multi-variable grey model （MGM（1,m）） from its source of construction errors. The MGM（1,m） with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM（1,2） with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.

Prediction of rock mass rating using fuzzy logic and multi-variable RMR regression model

Rock mass rating system （RMR） is based on the six parameters which was defined by Bieniawski （1989） [1]. Experts frequently relate joint and discontinuities and ground water conditions in linguistic terms with rough calculation. As a result, there is a sharp transition between two modules which create doubts. So, in this paper the proposed weights technique was applied for linguistic criteria. Then by using the fuzzy inference system and the multi-variable regression analysis, the accurate RMR is predicted. Before the performing of regression analysis, sensitivity analysis was applied for each of Bieniawski parameters. In this process, the best function was selected among linear, logarithmic, exponential and inverse func- tions and finally it was applied in the regression analysis for construction of a predictive equation. From the constructed regression equation the relative importance of the input parameters can also be observed. It should be noted that joint condition was identified as the most important effective parameter upon RMR. Finally, fuzzy and regression models were validated with the test datasets and it was found that the fuzzy model predicts more accurately RMR than reression models.

Multi-Variable Flocking Control for Multi-Agent Systems via a Received Signal Strength Indicator

A novel flocking control approach is proposed for multi-agent systems by integrating the variables of velocities, motion directions, and positions of agents. A received signal strength indicator （RSSI） is applied as a variable to estimate the inter-distance between agents. A key parameter that contains the local information of agents is defined, and a multi-variable controller is proposed based on the parameter. For the position control of agents, the RSSI is introduced to substitute the distance as a control variable in the systems. The advantages of RSSI include that the relative distance between every two agents can be adjusted through the communication quality under different environments, and it can shun the shortage of the limit of sensors. Simulation studies demonstrate the effectiveness of the proposed control approach.

The Research and Application of Prediction Control in Multi-variable Control Process

The modern industrial control objects become more and more complicated,and higher control quality is required, so a series of new control strategies appear,applied,modified and develop quickly.This paper researches a new control strategy- prediction control-and its application in Multi-Variable Control Process.The research result is worthy for automatic control in pro- cess industry.

ENHANCING GROUND RESOLUTION OF TM6 BASED ON MULTI-VARIATE REGRESSION MODEL AND SEMI-VARIOGRAM FUNCTION

It is well known that Landsat TM images are the most widely used remote sensing data in various fields.Usually,it has 7 different electromagnetic spectrum bands,among which the sixth one has much lower ground resolution compared with the other six bands.Nevertheless,it is useful in the study of rock spectrum reflection,geothermal resources exploration,etc.To improve the ground resolution of TM6 to the level as that of the other six bands is a problem .This paper presents an algorithm based on the combination of multivariate regression model with semivariogram function which can improve the ground resolution of TM6 by "fusing" the data of other six bands.It includes the following main steps: （1） testing the correlation between TM6 and one of TM15,7.If the correlation coefficient between TM6 and another one is greater than a given threshold value,then select the band to the regression analysis as an argument.（2） calculating the size of the template window within which some parameters needed by the regression model will be calculated; （3） replacing the original pixel values of TM6 by those obtained by regression analysis; （4） using image entropy as a measurement to evaluate the quality of the fused image of TM6.The basic mechanism of the algorithm is discussed and the V C ++ program for implementing this algorithm is also presented.A simple application example is given in the last part of this paper,showing the effectiveness of the algorithm.

PRECISE INTEGRAL ALGORITHM BASED SOLUTION FORTRANSIENT INVERSE HEAT CONDUCTION PROBLEMSWITH MULTI-VARIABLES

By modeling direct transient heat conduction problems via finite element method (FEM) and precise integral algorithm, a new approach is presented to solve transient inverse heat conduction problems with multi-variables. Firstly, the spatial space and temporal domain are discretized by FEM and precise integral algorithm respectively. Then, the high accuracy semi-analytical solution of direct problem can be got. Finally, based on the solution, the computing model of inverse problem and expression of sensitivity analysis are established. Single variable and variables combined identifications including thermal parameters, boundary conditions and source-related terms etc. are given to validate the approach proposed in 1-D and 2-D cases. The effects of noise data and initial guess on the results are investigated. The numerical examples show the effectiveness of this approach.

Strong/weak limits and strong/weak differentials of multi-variable indeterminate forms. III: Transformations

Various transforms of the indeterminate forms are presented in this part, which include simplification in spherical coordinates, origin translation, axis alteration, transformation of limit conservation and application of Xh?K0. Fundamental factors for numerical simplification are provided respectively for bi-variable indeterminate forms, tri-variable indeterminate forms and the universal extending multiplier.

Strong/weak limits and strong/weak differentials of multi-variable indeterminate forms. I: Deduction and geometric illustration

Strong and weak limits as well as strong and weak differentials of multi-variable indeterminate forms are discussed based on the thorough exploration of differentiation to solve the strong and weak limits and differentials of unitary indeterminate forms. The fruit of this work is going to be reported in three parts. The first part presents the standard analysis on this subject which supplements, systematizes and advances L. Hospital抯 principles on differential calculus by applying special ,general, and limit guaranteeing theories together with K(t) and XhK0 theories. The combination of theoretical analysis and geometric signification makes the derivation intuitional, visual and easy to perceive.

Strong/weak limits and strong/weak differentials of multi-variable indeterminate forms. II: Supplementary annotations and analysis

Supplementary annotations on special forms 1to 4, discussion on the general characteristics of K(t) and K(t, t), and analyses on two noticeable limits are presented in this part. It is demonstrated that strong and weak parabolic transforms can be employed to change the standard form of a multi-variable indeterminate form into xmK type, hence to derive the standard formulae of the limit and the differential.

基于多头卷积和差分自注意力的小样本故障诊断方法

轴承是工业设备中使用最广泛的旋转部件之一,如果轴承在故障状况下运行较长时间,将会造成巨大的经济损失并威胁人身安全,因此,对轴承故障诊断进行研究具有十分重要的意义。基于深度学习的故障诊断技术目前日趋成熟,但在小样本情况下存在过拟合、效果不稳定、准确率不高等问题。为了解决这类问题,文中提出了一种融合多头卷积(Multi-Head Convolution,MC)的数据嵌入新算法和差分自注意力(Differential Self-Attention,DSA)机制的Transformer变种模型MDT(Multi-Head Convolu⁃tion and Differential Self-Attention Transformer),以实现端到端的小样本故障诊断。MC算法对样本进行多路径一维卷积,由多通道输出将样本从一维扩展到二维,通过多个卷积核尺寸提取出原样本中各个频域的丰富故障信息。相较于Transformer中原有的点积自注意力机制,DSA机制通过差分为每个特征求得对应的注意力权重向量,从而可从样本中提取出更为深层次的故障特征。MDT继承了Transformer对于处理序列数据的强大能力,可从时域信号中提取更为丰富的故障信息,同时避免了小样本模型中常见的过拟合问题。实验结果表明,该方法在每个故障种类仅有100个训练样本的轴承故障诊断任务中能稳定获得99%以上的测试准确率,具有强抗过拟合性和强鲁棒性。

编译支持的多线程程序多变体执行方法

多变体执行(multi-variant execution, MVX)是目前最流行的主动防御技术之一。理想情况下,当未受到攻击时,多变体执行架构提供正常的程序功能。但不幸的是,当多线程程序在多变体执行架构下运行时,由于各个程序变体中共享资源操作的线程执行顺序不一致,不同变体将会产生状态不一致,从而产生攻击误报,该问题导致了多线程程序难以以多变体执行方式运行。基于多变体执行环境,提出了一种编译支持的多线程程序对共享资源操作的同步编译模型,该模型以共享资源操作为同步点,分析确定多线程程序中对共享资源的操作时机和操作方式,保证各程序变体在运行时多线程对共享资源操作的一致性,从而消除了由此而引起的攻击误报。以LLVM 12.0编译框架为基础,设计实现了基于该同步编译模型的原型系统,并对该原型系统进行了仿真实验测试。实验结果显示,经过原型系统处理的多线程程序在多变体执行架构中的误报率显著降低,表明该同步编译模型作为一种通用性的方法,可有效消除多线程程序在多变体执行架构下运行时的攻击误报,提高了多变体执行的可用性。

多变体系统服务质量及损耗评估方法

多变体系统利用多样化技术和动态冗余策略从架构层面实现系统的高安全性和高可靠性,然而现有研究很少涉及多变体系统服务质量(QoS)的量化评估。针对以上问题,提出一种多变体系统QoS及损耗评估方法。首先,在多变体系统架构形式化建模的基础上,基于QoS属性及权重矩阵提出QoS评估模型和流程,并使用信息熵法则评估QoS属性的重要程度;然后,构造典型的多变体系统测试实例,设计并选取影响系统性能和安全性的QoS属性;最后,量化评估系统的QoS属性权重、QoS值、QoS差异和损耗,其中,性能属性平均损耗15.86个百分点,安全属性增益4.98个百分点。评估结果表明多变体机制存在QoS损耗,但它的安全属性带来了一定程度的QoS增益,可为构造高QoS以及低QoS损耗的多变体系统提供一些参考。