温度/机械载荷作用下高强度刨链裂纹扩展的随机化分析

为了描述温度/机械载荷作用下裂纹扩展速率,基于疲劳和蠕变裂纹扩展的线形叠加模型,提取圆环链的材料参数,引入对数正态随机过程,建立温度/机械交变载荷共同作用下高强度圆环链的裂纹扩展随机模型,采用泰勒级数法获得指定裂纹长度下寿命分布和指定寿命下裂纹长度分析的表达式,并进行刨链裂纹扩展的实验测试研究.结果表明,建立的圆环链随机化模型与试验结果一致.     

Basic Concepts of Probability and Statistics

In multiple regression it is shown that parameter estimates based on minimum residual sum of squares have a high probability of being unsatisfactory, if not incorrect, if the prediction vectors are not orthogonal. Proposed is an estimation procedure based on adding small positive quantities to the diagonal of X′X. Introduced is the ridge trace, a method for showing in two dimensions the effects of nonorthogonality. It is then shown how to augment X′X to obtain biased estimates with smaller mean square error.     

数据挖掘中隐私保护的随机化处理方法

数据挖掘中主要的任务就是针对聚集数据的建模问题。目前数据挖掘中的个人隐私保护问题受到越来越多的重视和研究。为了保护个人隐私,我们首先对一些私有数据进行随机化处理,在此基础上再进行建模。本文介绍了隐私保护课题的发展、随机化处理方法的一般算法及隐私保护技术的发展前景。     

SQLMVED:基于多变体执行的SQL注入运行时防御系统

SQL解析过程中利用随机化进行SQL注入攻击(SQLIA)防御的有效性是建立在攻击者不了解当前系统采用的具体随机化方法的基础上,因此,攻击者一旦掌握了当前系统的随机化形式,便能够实施有效的SQLIA.为了解决该问题,基于多变体执行设计出一种SQL注入运行时防御系统,多变体间采用互不相同的随机化方法,攻击者注入的非法SQ...     

基于博弈论抗共谋攻击的全局随机化共识算法

随着区块链技术的不断发展,作为区块链技术基石的共识技术受到更多关注,共识技术的发展越发迅速,但依旧存在相关难题。容错类共识算法作为区块链共识技术的代表性之一,依然存在诸多难题待研究,针对容错类共识算法中节点随机性和节点共谋攻击问题进行了研究,提出基于博弈论抗共谋攻击的全局随机化共识算法,通过实现节点的随机化和解决相关安全问题提高区块链网络的安全性和吞吐量。在选择参与容错类共识算法的节点过程中,利用映射函数和加权随机函数实现发起者和验证者节点的全局随机化,从而保证发起者和验证者节点的身份匿名,提高区块链网络的安全性。利用信誉更新模型实现信誉动态更新的同时利用博弈论分析容错类共识算法的安全问题,构造更加正确和高效的算法模型以提高算法的吞吐量并分析发现这类算法中存在超过1/3节点的共谋攻击问题,利用精炼贝叶斯博弈构造共谋合约,分析求得共谋者之间的纳什均衡点,从而解决超过1/3节点的共谋攻击问题。通过安全性分析和实验表明,基于博弈论抗共谋攻击的全局随机化共识算法相对工作量证明（Po W,proof of work）、权益证明（Po S,proof of stake）和实用拜占庭容错（PBFT,...     

基于Return-Oriented Programming的程序攻击与防护

随着w⊕x等技术的引入,传统的代码注入攻击几乎被消除,return-to-lib攻击受到很大程度的抑制。在此 背景下,Hovav Shacham提出了Return-Oriented Programming(ROP)的思想,该思想基于栈溢出的原理,通过使用程 序库中有效的以ret指令结尾的短指令序列构建gadget集合,使之具有图灵完备特性,来完成计算和攻击。讲述ROP 思想自提出以来的一些研究成果和其实际的攻击能力,阐述ROP自动化的当前成果与未来可能的发展方向,进而分 析和预测ROP自动化的下一步的研究方向。同时,也将从ROP的几个特征分析消除这种攻击的策略和方法,并介绍 目前已有的防护思想和成果,论述这些方法的优缺点和改进方向。综合阐述ROP攻击与ROP防护这一矛与盾的问 题,力争使读者理解ROP的思想,知悉当前的发展状态,并在此基础上能够进一步推进ROP攻击及其防范的研究。     

Pleiotropic Effects of APOB Variants on Lipid Profiles,Metabolic Syndrome,and the Risk of Diabetes Mellitus

Apolipoprotein B (ApoB) plays a crucial role in lipid and lipoprotein metabolism. The effects of APOB locus variants on lipid profiles, metabolic syndrome, and the risk of diabetes mellitus (DM) in Asian populations are unclear. We included 1478 Taiwan Biobank participants with whole-genome sequence (WGS) data and 115,088 TWB participants with Axiom genome-wide CHB array data and subjected them to genotype–phenotype analyses using APOB locus variants. Five APOB nonsynonymous mutations, including Asian-specific rs144467873 and rs13306194 variants, were selected from participants with the WGS data. Using a combination of regional association studies, a linkage disequilibrium map, and multivariate analysis, we revealed that the APOB locus variants rs144467873, rs13306194, and rs1367117 were independently associated with total, low-density lipoprotein (LDL), and non-high-density lipoprotein (non-HDL) cholesterol levels; rs1318006 was associated with HDL cholesterol levels; rs13306194 and rs35131127 were associated with serum triglyceride levels; rs144467873, rs13306194, rs56213756, and rs679899 were associated with remnant cholesterol levels; and rs144467873 and rs4665709 were associated with metabolic syndrome. Mendelian randomization (MR) analyses conducted using weighted genetic risk scores from three or two LDL-cholesterol-level-associated APOB variants revealed significant association with prevalent DM (p = 0.0029 and 8.2 × 10⁻⁵, respectively), which became insignificant after adjustment for LDL-C levels. In conclusion, these results indicate that common and rare APOB variants are independently associated with various lipid levels and metabolic syndrome in Taiwanese individuals. MR analyses supported APOB variants associated with the risk of DM through their associations with LDL cholesterol levels.     

A reactive simheuristic using online data for a real‐life inventory routing problem with stochastic demands

In the context of a supply chain for the animal‐feed industry, this paper focuses on optimizing replenishment strategies for silos in multiple farms. Assuming that a supply chain is essentially a value chain, our work aims at narrowing this chasm and putting analytics into practice by identifying and quantifying improvements on specific stages of an animal‐feed supply chain. Motivated by a real‐life case, the paper analyses a rich multi‐period inventory routing problem with homogeneous fleet, stochastic demands, and maximum route length. After describing the problem and reviewing the related literature, we introduce a reactive heuristic, which is then extended into a biased‐randomized simheuristic. Our reactive approach is validated and tested using a series of adapted instances to explore the gap between the solutions it provides and the ones generated by existing nonreactive approaches.     

基于指令集随机化的抗代码注入攻击方法

代码注入攻击是应用程序面临的一种主要安全威胁,尤其是Web应用程序,该种攻击源于攻击者能够利用应用程序存在的漏洞/后门,向服务器端注入恶意程序并执行,或者利用应用程序对用户输入的参数缺乏验证和过滤,造成输入作为恶意程序执行,从而达到攻击目的。源程序分析和输入规则匹配等现有防御方法在面对代码注入攻击时都存在着固有缺陷,为了提高Web应用程序对于代码注入攻击的防御性,提出一种基于指令集随机化的抗代码注入方法,该防御方法不依赖于攻击者采用何种攻击方式,能够抵御未知的代码注入攻击。基于该技术及动态、冗余构造方法,设计一套原型系统,采用广义随机Petri网（Generalized Stochastic Petri Net,GSPN）建模计算,攻击者即使在获得随机化方法先验知识的情况下也极难突破系统的防御机制。尽管该方法需要对应用程序源代码进行随机化变换,但处理过程是完全自动化和具有普适性的,通过实验和现网测试表明该方法能够有效抵御大部分代码注入攻击,实现了对攻击的主动防御。     

A biased‐randomized metaheuristic for the capacitated location routing problem

The location routing problem (LRP) involves the three key decision levels in supply chain design, that is, strategic, tactical, and operational levels. It deals with the simultaneous decisions of (a) locating facilities (e.g., depots or warehouses), (b) assigning customers to facilities, and (c) defining routes of vehicles departing from and finishing at each facility to serve the associated customers’ demands. In this paper, a two‐phase metaheuristic procedure is proposed to deal with the capacitated version of the LRP (CLRP). Here, decisions must be made taking into account limited capacities of both facilities and vehicles. In the first phase (selection of promising solutions), we determine the depots to be opened, perform a fast allocation of customers to open depots, and generate a complete CLRP solution using a fast routing heuristic. This phase is executed several times in order to keep the most promising solutions. In the second phase (solution refinement), for each of the selected solutions we apply a perturbation procedure to the customer allocation followed by a more intensive routing heuristic. Computational experiments are carried out using well‐known instances from the literature. Results show that our approach is quite competitive since it offers average gaps below 0.4% with respect to the best‐known solutions (BKSs) for all tested sets in short computational times.