PRESENT密码代数故障攻击

提出了一种新的PRESENT密码故障分析方法——代数故障攻击。将代数攻击和故障攻击相结合,首先利用代数攻击方法建立密码算法等效布尔代数方程组;然后通过故障攻击手段获取错误密文信息,并将故障差分和密文差分转化为额外的布尔代数方程组;最后使用CryptoMiniSAT解析器求解方程组恢复密钥。结果表明:在PRESENT-80的第29轮注入宽度为4的故障,故障位置和值未知时,2次故障注入可在50s内恢复64bit后期白化密钥,将PRESENT-80密钥搜索空间降低为216,经1min暴力破解恢复完整主密钥;和现有PRESENT故障攻击相比,该攻击所需样本量是最小的;此外该代数故障分析方法也可为其他分组密码故障分析提供一定思路。     

MIBS深度差分故障分析研究

给出了MIBS算法及故障分析原理,基于不同深度的故障模型,提出了3种针对MIBS差分故障分析方法,并进行实验验证.实验结果表明,由于其Feistel结构和S盒差分特性,MIBS易遭受深度差分故障攻击,最好的结果为在第30轮左寄存器导入1次4bit故障,故障位置和故障差分值未知,可将64bit主密钥搜索空间降低到224,经1min暴力破解恢复完整主密钥.此外,该故障分析方法也可为其他使用S盒的分组密码差分故障分析提供一定思路.     

PRESENT代数故障攻击的改进与评估

提出了一种基于代数分析的PRESENT故障攻击改进方法,将代数分析用于密码和故障方程构建,通过逆向构建加密方程来加快求解速度;提出了一种故障注入后的密钥剩余熵评估方法,可评估不同故障模型下的PRESENT抗故障攻击安全性;最后对智能卡上的8位智能卡上的PRESENT实现进行了时钟毛刺故障注入,最好情况下1次故障注入即可恢复主密钥,这是PRESENT故障攻击在数据复杂度上的最好结果。     

Saturnin-Short轻量级认证加密算法的统计无效故障分析

面向随机单字节故障模型和唯密文攻击假设,提出了一种针对Saturnin-Short算法的统计无效故障分析方法。该方法基于统计分布和无效状态分析,通过结合故障注入前后中间状态的变化,设计并采用了概率对称卡方-极大似然估计和调和中项-汉明重量新型区分器,最少仅需1 097个无效故障并以不低于99%的成功率恢复Saturnin-Short算法的256bit原始密钥。实验分析表明,所提区分器不仅降低了故障注入数,而且减少了攻击时间和复杂度。因此,Saturnin-Short算法不能抵抗统计无效故障分析的攻击。研究结果为其他轻量级认证加密算法的安全性分析提供了重要参考。     

基于密钥编排故障的SMS4算法的差分故障分析

提出并讨论了一种针对SMS4密钥编排方案的差分故障攻击方法.该方法采用面向字节的随机故障模型,通过在SMS4算法的密钥编排方案中导入故障,仅需要8个错误密文即可恢复SMS4算法的128bit原始密钥.数学分析和实验结果表明,该方法不仅扩展了故障诱导的攻击范围,而且提高了故障诱导的攻击成功率,减少了错误密文数,为故障攻击其他分组密码提供了一种通用的分析手段.     

KeeLoq密码Courtois攻击方法的分析和修正

KeeLoq密码是由Willem Smit设计的分组密码算法,广泛应用于汽车的无线门锁装置。Courtois等人在2007年提出了破译KeeLoq的4种滑动-代数攻击方法,其中第4种滑动-代数攻击方法的计算复杂性最小。本文证明了Courtois的第4种滑动-代数攻击方法的攻击原理是错误的,因而无法实现对KeeLoq的破译。此外,本文还对该方法进行了修正,提出了改进的攻击方法,利用232个已知明文能够以O(248) 次加密的计算复杂性求出KeeLoq密码的密钥,成功率为1。对于KeeLoq密码26％的密钥,其连续64圈圈函数形成的复合函数至少具有两个不动点,此时改进的攻击方法的计算复杂性还可降至O(248) 次加密。     

针对RSA-CRT数字签名的光故障攻击研究

通过研究密码芯片SRAM存储单元构造,利用激光改变进行运算的SRAM存储单元的逻辑状态,分析光注入对SRAM存储单元的影响。以Montgomery乘的 RSA－CRT数字签名算法为攻击对象,分析其算法的实现过程和故障注入机理。针对密码芯片实现的8位RSA－CRT签名算法,使用半导体激光作为注入光源,搭建光注入实验平台,在计算Sq时刻进行故障注入,从而得到故障签名,通过分析故障签名与N的关系,成功的获得了大素数q,验证了光故障攻击的有效性。     

基于持续性故障的分组密码算法S盒表逆向分析

基于故障注入的逆向分析技术通过向运行保密算法的设备中注入故障,诱导异常加密结果产生,进而恢复保密算法内部结构和参数.在除S盒表外其他运算结构已知的前提下,本文基于持续性故障提出了一种分组密码算法S盒表逆向分析方法.我们利用算法中使用故障元素的S盒运算将产生错误中间状态并导致密文出错这一特点,构造特殊的明文和密钥,诱导保密算法第二轮S盒运算取到故障值,从而逆向推导出第一轮S盒运算的输出,进而恢复出保密算法S盒表的全部元素.以类AES-128(Advanced Encryption Standard-128)算法为例,我们的方法以1 441 792次加密运算成功恢复出完整S盒表,与现有的其他逆向分析方法进行对比,新方法在故障注入次数和计算复杂度上有明显优势.进一步,我们将该方法应用于类SM4算法,并以1 900 544次加密运算恢复出保密S盒表.最后,我们综合考虑了分组密码算法的两种典型结构Feistel和SPN(Substitution Permutation Network)的特点,对新方法的普适性进行了讨论,总结出适用算法需具备的条件.     

分组密码的选择密钥攻击

本文介绍丁对分组密码的一种新型攻击,它比以前考虑的所有攻击都强。这种“选择密钥攻击”是已被普遍接受的选择明文攻击的一种推广。我们给出了一个例子,说明在选择明文攻击下不可破的分组密码,却立刻为选择密钥攻击所破。一般选择密钥攻击在2~(n/2)次运算内可破n比特密钥。黑箱理论证明对于通常的攻击,这个结果是最好的。     

积分攻击改进——随机线性区分与密钥恢复攻击

在4轮AES的积分攻击和碰撞攻击的基础上，提出了一种利用明文和中间状态的某些分组之间线性偏差分布的不均匀性的针对4轮SP结构分组密码的随机线性区分攻击。进一步结合预计算，提出了对4轮AES类分组密码的密钥恢复攻击。对LED-64算法给出了具体区分攻击和密钥恢复攻击的结果。其中，对于1-Step的LED-64算法，在数据复杂度为2⁸，计算复杂度为2¹⁶次基本运算的条件下，区分成功的概率是85%；对于2-Step的LED-64算法，相关密钥条件下的密钥恢复攻击的计算复杂度为2¹⁴次基本运算，数据复杂度为2⁸，预计算存储复杂度为2³⁸个半字节。     

基于自适应滑窗递归稀疏主成分分析的工业过程故障监测

本文提出一种自适应滑窗递归稀疏主成分分析方法,用于时变工业过程的在线故障监测.首先,通过滑窗提取正常过程数据空间的特征信息,并对当前窗口数据块矩阵进行稀疏主成分分析,构建稀疏主成分分析故障监测模型;然后,根据相邻窗口的相似度实时调整遗忘因子以自适应更新滑窗大小,使得所建立的稀疏主成分故障监测模型可以有效追踪复杂的时变过程;最后,通过递归更新滑窗稀疏载荷矩阵来动态更新故障监测模型.非线性数值仿真系统与田纳西-伊斯曼过程的故障监测结果表明,所提方法可以有效提高故障检测的准确率,适应于长流程时变工业过程在线故障监测.     

空时自适应处理的滑窗递推QR算法

在局部平稳的杂波环境下,滑窗样本选取方法可以比较准确地估计检测单元的杂波统计特性。该文提出基于滑窗选取样本的递推QR算法,它采用双曲Householder变换实现QR分解的递推,能有效地抑制局部平稳杂波,且具有数值稳定性好,计算量小的优点。仿真数据处理和实测数据处理验证了该方法的有效性。     

Using instruction result locality and re-execution to mitigate silent data corruptions

In this paper, a method to mitigate silent data corruptions (SDCs) is proposed. This paper, first, shows and characterizes instruction result locality based on several simulation results and next, proposes an architecture called instruction value history table (VHT) to detect SDCs. In the case of fault detection, extra instruction redundant execution is utilized to assure fault existence. If outcome of the new redundant execution is different from that of previous one, a fault occurred, otherwise the first execution will be correct. In order to correct any detected faults, third redundant execution of the instruction is performed. Having three values from three redundant instruction executions, makes the correction of the fault feasible. The main advantage of this method is to detect any error which is not detectable by traditional protection codes like parity and SEC-DED. In other words, this method detects SDCs or any multiple faults which are not detectable by protection codes. Various soft error injections have been applied on Alpha processor for several PARSEC benchmarks. Experimental results show that the method can detect up to 70% of injected SDCs.     

A second order sliding mode strategy for fault detection and fault-tolerant-control of a MEMS optical switch

Optical switches are widely used in telecommunication industry due to their many desirable characteristics. In this paper, robust fault detection and fault-tolerant-control (FTC) system for an uncertain nonlinear MEMS optical switch are presented. The design strategy is based on the second order sliding mode approach. A robust second order nonlinear sliding mode observer capable of filtering unwanted high frequencies due to unmodeled dynamics is used to generate quantities called the the residuals. The residuals are then used for the purpose of fault detection and alarm generation. Once an alarm is registered, a fault tolerant control strategy is employed. Two different fault-tolerant control strategies for the unhealthy system are considered. The first strategy is based on conventional sliding mode, while the second is based on a second order sliding mode theory. Robustness and convergence of the proposed schemes are proved using the second method of Lyapunov and the super-twisting algorithm. A comparative study is then performed to demonstrate the superior capability of second order sliding mode control strategy in fault accommodation. Finally, the effectiveness of the proposed strategy for detection of faults, and subsequent control of the MEMS optical switch is illustrated through simulation studies.     

Sliding Mode Observer-Based Fault Detection of Distributed Networked Control Systems with Time Delay

This paper considers the fault detection problem of distributed networked control systems (DNCS) with time delay. A sliding mode observer-based fault detection method for a two-level DNCS is presented and two different situations are considered. When all the states of the system are available for measurement, we convert the fault detection problem to a sliding motion stable and reachable problem. When some states of system are not available for measurement, we design a transformation matrix to separate the measurable states and the unknown states, and then different sliding mode observers for those unknown states are developed to achieve fault detection. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method with simulation results.     

基于电压暂降测量的配电网故障自动定位

文中提出了一种结合电力系统分析程序、数据库检索方法和模式识别技术自动识别的11kV配电网故障定位方法。该方法采用三相不平衡潮流和故障分析程序,对配电网各节点的故障进行分析生成电压暂降数据库,设计了数据库搜索和模式识别算法,以便配电网在发生实际故障时识别故障位置。利用电力系统EMTDC模拟器对该方法进行了评估和测试。实验结果表明,提出的线性模式识别算法能够识别所研究的11kV配电网的大部分故障区段。     

LDDoS attack detection method based on wavelet decomposition and sliding windows

As a special type of distributed denial of service (DDoS) attacks, the low-rate DDoS (LDDoS) attacks have characteristics of low average rate and strong concealment, thus, it is hard to detect such attacks by traditional approaches. Through signal analysis, a new identification approach based on wavelet decomposition and sliding detecting window is proposed. Wavelet decomposition extracted from the traffic are used for multifractal analysis of traffic over different time scale. The sliding window from flow control technology is designed to identify the normal and abnormal traffic in real-time. Experiment results show that the proposed approach has advantages on detection accuracy and timeliness.     

Functional fault models for non-scan sequential circuits

The paper presents two functional fault models that are applied for functional delay test generation for non-scan synchronous sequential circuits: the pin pair state (PPS) fault model and the pin pair full state (PPFS) fault model. The PPS fault model deals with the pairs of stuck-at faults on the primary inputs and the primary outputs, as well as, with the pairs of stuck-at faults on the previous state bits and the primary outputs. The PPFS fault model encompasses the PPS model, and additionally deals with the pairs of stuck-at faults on the primary inputs and the next state bits, as well as, with the pairs of stuck-at faults on the previous state bits and the next state bits. The main factor in assessing the quality of obtained test sequences was the transition fault coverage at the gate level of the selected according to the appropriate fault model test sequences from the generated randomly ones. The experimental results demonstrate that the implementation using presented functional fault models allow selecting the test sequences from the initial test set without the loss of transition fault coverage in many cases, and the number of the selected test sequences is much lesser than that of the initial test set. This result demonstrates that the functional delay test can be generated using the presented functional delay fault models before structural synthesis of the circuit.     

Fault clustering: modeling and observation on experimental LSI chips

Occurrence of fault clustering on large-scale integrated (LSI) MOS product was verified with optical microscopes on experimental chips that failed electrical testing. Two methods were used for determining clustering: analysis of the fault density derived from collected fault data, and separation of faults into two populations, one representing solitary faults, the other clusters. A model for the first method is presented and its effectiveness examined on a simulated fault set. The method is then applied to fault data representing two samples of MOS LSI experimental product. Population separation is finally carried out on one of the data samples, and the clustering data developed from this process are expressed by two factors. One factor can be used for refined yield estimates, the other was applied to quality measure calculations.     

Automatic generation and compaction of March tests for memoryarrays

Given a set of memory array faults, the problem of computing a compact March test that detects all specified memory array faults is addressed. In this paper, we propose a novel approach in which every memory array fault is modeled by a set of primitive memory faults. A primitive March test is defined for each primitive memory fault. We show that March tests that detect the specified memory array faults are composed of primitive March tests. A method to compact the March tests for the specified memory array faults is described. A set of examples to illustrate the approach is presented. Experimental results demonstrate the productivity gained using the proposed framework