分布式软件故障注入及软件脆弱点检测方法研究
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摘要
在一些高可靠性领域,计算机系统的应用越来越广泛,如交通控制、医疗、核电站、银行、电讯系统和航空航天等。在这些领域中,计算机系统的失效可能造成巨大的人员伤亡和经济损失。另外,在高性能并行计算领域,计算机可靠性的重要性也越来越高。并行计算机通常用于一些高强度计算应用,如基础物理/化学、飞机/汽车建模等,这些应用不仅运行时间长,而且由于并行计算所带来的电子器件增多导致故障发生的可能性增大。特别是对于航天领域,由于宇宙射线的存在,会导致计算机系统经常发生各种故障。
可靠性计算机一般都采用容错机制来检测软件或硬件故障,定位故障源或可能从这些故障/错误中恢复。但如何在系统应用之前对这些容错机制的有效性、可用性进行评估和验证,检验它们是否和我们事先预想的情况相一致。这就需要一种有效的对容错机制进行评测的方法和工具。同时,在对软件系统装配容错机制之前,考虑到容错机制的效率因素,把容错机制放于何处及如何放置才能发挥它们的最大作用,这就需要了解软件系统中错误的产生与传播过程,以及找出软件系统中相对薄弱的环节或部分。最后在找到软件系统的薄弱环节以后,如何对之进行加固也是一个很重要的内容。
计算机系统的可靠性验证是一个复杂艰巨的任务,一般使用理论建模方法,但由于故障激活机制和错误传播过程非常复杂,在大多数情况下都是不完全可知的,所以很难对实际系统进行建模。故障注入技术作为一种实验评测方法被证明是一种高效的可靠性验证方法,他通过人为的在目标系统中产生故障,加速系统发生故障和失效的过程,通过对注入故障后系统的反应信息进行监测和分析,可获得对目标系统可靠性和容错性能的评测结果。与其它方法相比,故障注入具有应用范围广、结果精确度高、时间花费少等优点,已引起众多学者和研究人员的重视。
本文首先研究了进行故障注入的一些基本原理和方法,结合航天领域的特点设计了故障模型,然后提出了一种分布式的故障注入工具的架构,并在Linux系统上进行了开发与实现。经实验验证,该工具可在分布式系统或单机系统中注入多种故障,同时还拥有强大的数据回收功能,并具有很好的可移植性(可在所有类Unix操作系统平台上运行)和可扩展性。这为以后研究分布式系统的可靠性奠定了一定的基础。
以该故障注入工具为基础,本文又分别在信号和模块级别上研究了故障在软件中的生成与传播过程,并定义了描述此过程的参数及其计算方法,其中首次提出了模块泄漏率和活动率的概念,并给出了软件脆弱点的概念及确定原则,最后在一卫星光纤陀螺捷联航姿控制系统上对该框架的正确性和有效性进行了验证。这为从设计角度来减少软件系统模块间的错误传播提供了理论基础,同时也为评测软件系统可靠性提供了方法,并为如何放置容错机制才能使之达到效率最高提供了依据。
找到了软件系统中的脆弱点,但如何对它们进行加固处理,也是本文考虑的一个内容。本文针对航天领域强辐射的特点,分别从程序控制流和数据流角度提出了两种在线加固方法。控制流加固方法(RSCFC)可以检测程序中的控制流错误,该方法首先识别程序中的各个基本模块,然后把基本模块间的关系编码进模块标记中,最后在每个基本模块的首部和尾部分别加上测试和设置指令,通过一全局变量来检测程序的执行流程。该方法不仅可用于高级语言,也可在汇编语言级上实现。通过在几个C语言标准程序上使用该方法,并进而进行故障注入实验,结果表明该方法在对程序代码大小和性能影响不大的条件下可把未探测故障率从原始程序的20.7～68.8%降低到2.8～20.4%。
数据流加固方法(SBC)通过对程序中变量进行简单编码和解码操作后,可对发生在程序数据空间内的单“位”错误进行检测并进而纠正。故障注入的实验结果表明,对于程序数据段错误,该算法可把错误输出从原始程序的27%～49%降低到0.01%～0.02%,同时故障纠正率接近100%;对于程序堆栈段错误,该算法可把错误输出从原始程序的10%～70%降低到1%～3%,故障纠正率也在73%以上。
在软件系统实现上,我们把故障注入平台、错误传播和软件脆弱点检测集成到了一起,统称软件脆弱点识别环境SAVIE。本文在最后对SAVIE设计实现进行了描述,包括系统结构、各个模块的功能、使用流程和方法等。
Computer systems are used nowadays in an increasing number of applicationsthat require high levels of dependability. In some cases our lives depend on them,such as in traffic control, medical life support, or nuclear power station managementapplications. In other cases, such as banking, telecommunications and aerospace,failures can cause tremendous economic losses. Another novel area where depend-ability is increasingly important is high performance parallel computing. Parallelcomputers are used to run computation intensive applications such as fundamentalphysics/chemistry, and airplane/vehicle modeling, during large periods of time. De-pendability is important to enable those long runs in spite of the increased probabilityof fault occurrence caused by the larger number of electronic components in parallelcomputers. Especially, computer systems operating in space environment are subjectto different radiation phenomena,whose effects can be permanent or transient. Andthese effects may lead to all kinds of faults/errors.
Generally, a dependable computer should be able to detect software or hard-ware errors, locate their origin, and recover from those errors by using some kind offault tolerance mechanisms. One important problem is how to evaluate and validatethe effectiveness of the fault tolerance mechanisms embedded in these systems be-fore production in order to correct defects and/or provide feedback for improvements.Furthermore, if the efficiency of the fault tolerance mechanisms is taken into account,the other important problem is where to place and how to place these mechanisms inorder to make the most use of them. These demands ask for an effective method andtool to validate the fault tolerance mechanisms.
The validation of the dependability properties of a computer system is an intrin-sically complex task. The use of analytical modeling in actual systems is very difficultas the mechanisms involved in the fault activation and also in the error propagationprocess are highly complex; they are not completely understood in most cases. Ex-perimental evaluation by fault injection has become an attractive way of validating thedependability of system, which introduces some faults into target system artificially inorder to speed the occurrence of fault or failure in the system and can get the validation result of dependability and fault tolerance capability of the system through monitoringand analogizing the info gotten from the injected target system. Compared to othermethods, fault injection has the main advantage that the wide scope of application ,high result precision and much less time consuming, and attract the attention of moreand more scholars and researchers.
In this paper, the basic principle and method about fault injection are investigatedfirstly; then the fault models are designed according to the characteristic of space;thirdly, a distributed framework of the fault injection tool is proposed, furthermore, itis also developed and implemented on Linux operating system. Validated by the ex-periments, this tool can not only inject many types of fault in the distributed systems,but in a single computer. On the other hand, it also have power abilities to collect thedata generated in experiment and primely multi-platforms and expansibility. This toolestablishes some foundation for study the dependability of distributed system later.
Base on the fault injection tool, we study and characterize the error propagationprocess in software from the modular and signal level each, and define a set of metricsthat quantitatively represent the inter-modular software interactions and their calculatemethods. In this process, the modula leak rate and activation rate are first proposed.As a result, the concept and the principles of confirming software vulnerabilities areproposed. Furthermore, we use a real embedded target system used in a navigation-pose control system of a satellite to perform fault-injection experiments to validate thecorrectness and effectiveness of this framework. The work provides theory founda-tion from the design aspect for how to decrease the error propagation among modulesin software system, simultaneously, gives the method of how to testing the depend-ability of software system and shows the ground of how to place the fault tolerancemechanisms in order to make the most use of them.
After the software vulnerabilities have been found, the next problem is how toharden them. According to the strong radiation characteristic of space environment,we propose two on-line harden methods of software from control-?ow and data-?owrespectively.
The control-?ow harden technique proposed is called RSCFC(Relationship Sig-natures for Control Flow Checking) that assigns a relationship signature and insertssome special assertions to each basic block to detect control ?ow faults through ANDoperation between the run-time signature and the basic block’s location info. A fault injection experiment was performed with several C benchmark programs. The resultsuggests that about 20.7～68.8% of the injected branching faults produced unde-tected incorrect outputs without RSCFC; however,with RSCFC, the above numberdeclines to 2.8～20.4%.
The data-?ow harden method SBC(Single Bit Correction), a software-based ap-proach for soft error correction, is put forward. The technique is based on the codingand decoding of variables in programs to detect and correct the errors in them. Resultsissued from fault injection experiments suggests that the method can decline the unde-tected incorrect output from the original programs’s 27%～49% to 0.01%～0.02%for programs’s data section faults, with almost 100% correction rate; furthermore, forstack section faults, the undetected incorrect output is decreased from 10%～70% to1%～3%, with more than 82% correction rate. Compared with previous techniques,the SBC method has the characteristics of both easy implementation and low memoryoverhead with a very high fault detection and correction capability.
In the software implementation, we integrated the fault injection tool, error prop-agation framework and software vulnerability identifying into one platform, generallycalled SoftwAre Vulnerabilities Identifying Environment (SAVIE). In the last of thisdissertation, a detailed description on the design and implementation of SAVIE isgiven, including the system structure, the function of each module, work progress andmethods et.ec.
可靠性计算机一般都采用容错机制来检测软件或硬件故障,定位故障源或可能从这些故障/错误中恢复。但如何在系统应用之前对这些容错机制的有效性、可用性进行评估和验证,检验它们是否和我们事先预想的情况相一致。这就需要一种有效的对容错机制进行评测的方法和工具。同时,在对软件系统装配容错机制之前,考虑到容错机制的效率因素,把容错机制放于何处及如何放置才能发挥它们的最大作用,这就需要了解软件系统中错误的产生与传播过程,以及找出软件系统中相对薄弱的环节或部分。最后在找到软件系统的薄弱环节以后,如何对之进行加固也是一个很重要的内容。
计算机系统的可靠性验证是一个复杂艰巨的任务,一般使用理论建模方法,但由于故障激活机制和错误传播过程非常复杂,在大多数情况下都是不完全可知的,所以很难对实际系统进行建模。故障注入技术作为一种实验评测方法被证明是一种高效的可靠性验证方法,他通过人为的在目标系统中产生故障,加速系统发生故障和失效的过程,通过对注入故障后系统的反应信息进行监测和分析,可获得对目标系统可靠性和容错性能的评测结果。与其它方法相比,故障注入具有应用范围广、结果精确度高、时间花费少等优点,已引起众多学者和研究人员的重视。
本文首先研究了进行故障注入的一些基本原理和方法,结合航天领域的特点设计了故障模型,然后提出了一种分布式的故障注入工具的架构,并在Linux系统上进行了开发与实现。经实验验证,该工具可在分布式系统或单机系统中注入多种故障,同时还拥有强大的数据回收功能,并具有很好的可移植性(可在所有类Unix操作系统平台上运行)和可扩展性。这为以后研究分布式系统的可靠性奠定了一定的基础。
以该故障注入工具为基础,本文又分别在信号和模块级别上研究了故障在软件中的生成与传播过程,并定义了描述此过程的参数及其计算方法,其中首次提出了模块泄漏率和活动率的概念,并给出了软件脆弱点的概念及确定原则,最后在一卫星光纤陀螺捷联航姿控制系统上对该框架的正确性和有效性进行了验证。这为从设计角度来减少软件系统模块间的错误传播提供了理论基础,同时也为评测软件系统可靠性提供了方法,并为如何放置容错机制才能使之达到效率最高提供了依据。
找到了软件系统中的脆弱点,但如何对它们进行加固处理,也是本文考虑的一个内容。本文针对航天领域强辐射的特点,分别从程序控制流和数据流角度提出了两种在线加固方法。控制流加固方法(RSCFC)可以检测程序中的控制流错误,该方法首先识别程序中的各个基本模块,然后把基本模块间的关系编码进模块标记中,最后在每个基本模块的首部和尾部分别加上测试和设置指令,通过一全局变量来检测程序的执行流程。该方法不仅可用于高级语言,也可在汇编语言级上实现。通过在几个C语言标准程序上使用该方法,并进而进行故障注入实验,结果表明该方法在对程序代码大小和性能影响不大的条件下可把未探测故障率从原始程序的20.7～68.8%降低到2.8～20.4%。
数据流加固方法(SBC)通过对程序中变量进行简单编码和解码操作后,可对发生在程序数据空间内的单“位”错误进行检测并进而纠正。故障注入的实验结果表明,对于程序数据段错误,该算法可把错误输出从原始程序的27%～49%降低到0.01%～0.02%,同时故障纠正率接近100%;对于程序堆栈段错误,该算法可把错误输出从原始程序的10%～70%降低到1%～3%,故障纠正率也在73%以上。
在软件系统实现上,我们把故障注入平台、错误传播和软件脆弱点检测集成到了一起,统称软件脆弱点识别环境SAVIE。本文在最后对SAVIE设计实现进行了描述,包括系统结构、各个模块的功能、使用流程和方法等。
Computer systems are used nowadays in an increasing number of applicationsthat require high levels of dependability. In some cases our lives depend on them,such as in traffic control, medical life support, or nuclear power station managementapplications. In other cases, such as banking, telecommunications and aerospace,failures can cause tremendous economic losses. Another novel area where depend-ability is increasingly important is high performance parallel computing. Parallelcomputers are used to run computation intensive applications such as fundamentalphysics/chemistry, and airplane/vehicle modeling, during large periods of time. De-pendability is important to enable those long runs in spite of the increased probabilityof fault occurrence caused by the larger number of electronic components in parallelcomputers. Especially, computer systems operating in space environment are subjectto different radiation phenomena,whose effects can be permanent or transient. Andthese effects may lead to all kinds of faults/errors.
Generally, a dependable computer should be able to detect software or hard-ware errors, locate their origin, and recover from those errors by using some kind offault tolerance mechanisms. One important problem is how to evaluate and validatethe effectiveness of the fault tolerance mechanisms embedded in these systems be-fore production in order to correct defects and/or provide feedback for improvements.Furthermore, if the efficiency of the fault tolerance mechanisms is taken into account,the other important problem is where to place and how to place these mechanisms inorder to make the most use of them. These demands ask for an effective method andtool to validate the fault tolerance mechanisms.
The validation of the dependability properties of a computer system is an intrin-sically complex task. The use of analytical modeling in actual systems is very difficultas the mechanisms involved in the fault activation and also in the error propagationprocess are highly complex; they are not completely understood in most cases. Ex-perimental evaluation by fault injection has become an attractive way of validating thedependability of system, which introduces some faults into target system artificially inorder to speed the occurrence of fault or failure in the system and can get the validation result of dependability and fault tolerance capability of the system through monitoringand analogizing the info gotten from the injected target system. Compared to othermethods, fault injection has the main advantage that the wide scope of application ,high result precision and much less time consuming, and attract the attention of moreand more scholars and researchers.
In this paper, the basic principle and method about fault injection are investigatedfirstly; then the fault models are designed according to the characteristic of space;thirdly, a distributed framework of the fault injection tool is proposed, furthermore, itis also developed and implemented on Linux operating system. Validated by the ex-periments, this tool can not only inject many types of fault in the distributed systems,but in a single computer. On the other hand, it also have power abilities to collect thedata generated in experiment and primely multi-platforms and expansibility. This toolestablishes some foundation for study the dependability of distributed system later.
Base on the fault injection tool, we study and characterize the error propagationprocess in software from the modular and signal level each, and define a set of metricsthat quantitatively represent the inter-modular software interactions and their calculatemethods. In this process, the modula leak rate and activation rate are first proposed.As a result, the concept and the principles of confirming software vulnerabilities areproposed. Furthermore, we use a real embedded target system used in a navigation-pose control system of a satellite to perform fault-injection experiments to validate thecorrectness and effectiveness of this framework. The work provides theory founda-tion from the design aspect for how to decrease the error propagation among modulesin software system, simultaneously, gives the method of how to testing the depend-ability of software system and shows the ground of how to place the fault tolerancemechanisms in order to make the most use of them.
After the software vulnerabilities have been found, the next problem is how toharden them. According to the strong radiation characteristic of space environment,we propose two on-line harden methods of software from control-?ow and data-?owrespectively.
The control-?ow harden technique proposed is called RSCFC(Relationship Sig-natures for Control Flow Checking) that assigns a relationship signature and insertssome special assertions to each basic block to detect control ?ow faults through ANDoperation between the run-time signature and the basic block’s location info. A fault injection experiment was performed with several C benchmark programs. The resultsuggests that about 20.7～68.8% of the injected branching faults produced unde-tected incorrect outputs without RSCFC; however,with RSCFC, the above numberdeclines to 2.8～20.4%.
The data-?ow harden method SBC(Single Bit Correction), a software-based ap-proach for soft error correction, is put forward. The technique is based on the codingand decoding of variables in programs to detect and correct the errors in them. Resultsissued from fault injection experiments suggests that the method can decline the unde-tected incorrect output from the original programs’s 27%～49% to 0.01%～0.02%for programs’s data section faults, with almost 100% correction rate; furthermore, forstack section faults, the undetected incorrect output is decreased from 10%～70% to1%～3%, with more than 82% correction rate. Compared with previous techniques,the SBC method has the characteristics of both easy implementation and low memoryoverhead with a very high fault detection and correction capability.
In the software implementation, we integrated the fault injection tool, error prop-agation framework and software vulnerability identifying into one platform, generallycalled SoftwAre Vulnerabilities Identifying Environment (SAVIE). In the last of thisdissertation, a detailed description on the design and implementation of SAVIE isgiven, including the system structure, the function of each module, work progress andmethods et.ec.
引文
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34 J. Aidemark, J. Vinter, P. Folkesson, et al. Goofi: Generic Object-oriented FaultInjection Tool. DSN 2001. Gothenburg,Sweden, 2001:1–6
35 G. Jacques-Silva, R. J. Drebes, J. Gerchman, et al. Fiona: A Fault Injectorfor Dependability Evaluation of Java-based Network Applications. Proc. of 3rdIEEE International Symposium on Network Computing and Applications (NCA2004). Cambridge, MA, USA, 2004:303–308
36 刘宏泰. 基于软件实现的故障注入系统设计与仿真. Master’s thesis, 哈尔滨工业大学硕士学位论文. 2003
37 王胜文. 基于软件的故障注入方法的研究. 哈尔滨工业大学博士学位论文Ph.D. thesis. 2004
38 彭俊杰. 基于软件故障注入的星载系统可靠性评测. 哈尔滨工业大学博士学位论文Ph.D. thesis. 2005
39 朱鹏, 张平. 基于单片机的故障注入系统. 计算机测量与控制. 2004,12(10):996–998
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41 陈显峰, 裘丽华, 王占林. 分布式系统故障注入研究. 系统仿真学报. 1999,11(6):473–476
42 A. Jhumka, M. Hiller, N. Suri. Assessing Inter-modular Error Propagation inDistributed Software. nternational Symposium on Reliable and Distributed Sys-tems (SRDS). 2001:152–161
43 J. P. Roth. Computer Logic. Testing and Verification, Computer Science Press,1980
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45 H. Fujiwara, T. Shimono. On the Acceleration of Test Generation Algorithms.IEEE Transactions on Computers. 1983, C-32:265–272
46 K. G. Shin, T.-H. Lin. Modeling and Measurement of Error Propagation ina Multimodule Computing System. IEEE Transactions on Computers. 1988,37(9):1053–1066
47 G. Csertán, A. Pataricza, E. Selényi. Dependability Analysis in Hw-sw Code-sign. Proceedings of the International Computer Performance and Dependabil-ity Symposium (IPDS’95). 1995:306-315
48 J. Voas, L. J. Morell. Propagation and Infection Analysis (pia) Applied to De-bugging. Proceedings of Southeastcon’90. 1990:379–383
49 J. Voas. Pie: A Dynamic Failure-based Technique. IEEE Trans. on SoftwareEngineering. 1992, 18(8):717–727
50 L. Morell, B. Murrill, R. Rand. Perturbation Analysis of Computer Pro-grams. Proceedings of the International Conference on Computer Assur-ance(COMPASS’97). 1997:77–87
51 J. Voas, F. Charron, L. Beltracchi. Error Propagation Analysis Studies in aNuclear Research Code. Aerospace Conf. 1998, 4:115–121
52 C. C. Michael, R. C. Jones. On the Uniformity of Error Propagation in Software.Proc. Int’l Conf. Computer Assurace (COMPASS’97). 1997:68–76
53 D. M. Nassar, W. A. Rabie, M. Shereshevsky, et al. Estimating Error Prop-agation Probabilities in Software Architectures. Tech. rep., College of Com-puter Science. New Jersey Institute of Technology, 2002. http://www.ccs.njit.edu/swarch/ep.pdf
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