基于分类修正的多证据合成方法

鉴于传统冲突量参数无法有效地衡量证据间的相似程度, 提出一种基于分类修正的多证据合成方法, 以解决证据合成中的高冲突悖论和“0”悖论. 首先, 利用证据距离参数、冲突量参数和方向角度参数共同衡量各证据间的相似程度, 将证据分为一致证据、不冲突证据、低冲突证据以及高冲突证据4 类; 然后, 利用3 个参数赋予各类证据不同的修正系数; 最后, 利用Dempster 规则对修正后的证据进行合成. 算例分析表明, 所提出的方法能够较好地解决高冲突悖论和“0”悖论, 而且保留了证据理论优良的数学性质.     

云计算支持下的协作式数字取证技术

为解决网络环境下电子证据分散、取证分析效率低、协作难度大等问题,在分析计算机犯罪特点以及当前数字取证所面临的相关问题基础上,针对数字取证与分析的协同需求,设计了一种具有正循环反馈机制的云计算支持下的协作式数字取证模型,并详细论述了其设计思想和体系架构.最后,研究了模型的系统实现方法、电子证据云存储调度策略、基于封锁机制的并发分析任务调度.实验表明,协作式数字取证技术可有效提高数字取证工作效率和分析结果的准确性.     

局部证据RBF人体行为高层特征自相似融合识别研究

针对传统人体动作识别算法,往往重点解决某一类行为识别,不具有通用性的问题,提出一种局部证据RBF人体行为高层特征自相似融合识别算法。首先,借用随时间变化的广义自相似性概念,利用时空兴趣点光流场局部特征提取方法,构建基于自相似矩阵的人体行为局部特征描述;其次,在使用SVM算法进行独立个体行为识别后,利用所提出的证据理论RBF（Radial Basis Function）高层特征融合,实现分类结构优化,从而提高分类准确度;仿真实验表明,所提方案能够明显提高人体行为识别算法效率和识别准确率。     

基于改进的无量纲指标信息融合故障诊断方法

针对无量纲指标信息的不确定会产生冲突证据的问题,提出一种基于改进证据理论的无量纲指标信息融合故障诊断方法.采用人工免疫算法构建原始证据;通过计算无量纲免疫检测器证据之间的相似度找出相似证据和冲突证据.保留相似证据,并利用可信度修正冲突证据,从而降低冲突证据对证据理论合成结果的影响.组合式旋转机械故障诊断试验验证本文方法有效.该方法能够明显提高故障诊断准确率.     

An Approach for Validation of Digital Anti-Forensic Evidence

ABSTRACT

e-crime is increasing and e-criminals are becoming better at masking their activities. The task of forensic data analysis is becoming more difficult and a systematic approach towards evidence validation is necessary. With no standard validation framework, the skills and interpretation of forensic examiners are unchecked. Standard practices in forensics have emerged in recent years, but none has addressed the development of a model of valid digital evidence. Various security and forensic models exist, but they do not address the validity of the digital evidence collected. Research has addressed the issues of validation and verification of forensic software tools but failed to address the validation of forensic evidence. The forensic evidence collected using forensic software tools can be questioned using an anti-forensic approach. The research presented in this paper is not intended to question the skills of forensic examiners in using forensic software tools but rather to guide forensic examiners to look at evidence in an anti-forensic way. This paper proposes a formal procedure to validate evidence of computer crime.     

数据挖掘技术在信息安全证据处理中的应用

为了有效解决信息安全证据获取和证据规范化等难题,文章从数据挖掘的角度,阐述了如何搜集、处理信息安全在搜索潜在威胁时的证据,给出了如何获取证据以及证据的规范化表示的基本思路,从而增强了信息网络的安全信任属性。     

Bayesian network models for environmental flow decision‐making: 1. Latrobe River Australia

Current methods underpinning environmental flow (eFlow) decisions often lack transparency, do not adequately consider uncertainties and rarely include adaptive management principles. We report the development and application of an eFlow Bayesian Network (BN) model that links four flow components with an ecological model to predict the spawning and recruitment of two important native fish species, the Australian Grayling and River Blackfish, in the highly regulated and flow‐stressed lower Latrobe River in Victoria, Australia. Autumn high flows, in conjunction with low stream temperature, are critical for Grayling spawning. The BN model was used to predict the probability of spawning and recruitment of these two native fish species for four flow scenarios. Quantitative data, flow simulation models and expert judgement were used to parameterize the BN model. The model results showed clearly that currently, and into the future, there is a very low likelihood of spawning and recruitment of Australian Grayling in the lower Latrobe. River Blackfish are minimally affected by the predicted reductions in flow and increased stream temperatures. Management scenarios aimed at modifying flows and stream temperatures to increase the likelihood of successful spawning and recruitment of Australian Grayling were assessed. Self‐sustaining populations of Australian Grayling could conceivably be achieved in the upper reaches of this river if fish passage was provided through an on‐stream reservoir. A major benefit in building and applying an eFlow BN model is that it can facilitate meaningful analysis and discussion of the ecological effects of particular eFlow regimes. Copyright © 2010 John Wiley & Sons, Ltd.     

基于模糊和证据理论的行为建模

针对人类行为模型系统中存在大量的复杂任务关系和过程,系统输出的概率不确定性等问题,提出了基于Mamdani-Zadeh推理范式和D-S证据理论的建模方法.这种方法把输入空间分割成人们比较容易理解和表达问题的小区域,使用Mamdani-Zadeh和模糊D-S规则控制信度函数的输出值,从而得到了用户预期焦化元的清晰值,实现了模型系统关系、过程简单化;并通过具体例子证实了此方法的精确性和有效性。     

证据理论加权决策树在外包维修中的应用

外包维修过程中产生的数据通常是模糊的,传统上很少按重要性分类,从这些数据仅仅能搜索到相关的不确定信息。将证据理论作为处理不确定数据的有力工具,提出用证据理论加权决策树算法对外包维修过程产生的不确定数据进行分类并挖掘出规则。实验结果表明本算法可有效的对外包维修数据进行分类,并可以生成可指导产品研发的规则。     

一种改进的计算机取证领域的分流过程模型

随着计算机的广泛应用,计算机犯罪越来越多,由此产生了一门新的学科——计算机取证学。文章在计算机取证领域的分流过程模型CFFTPM（Computer Forensics Field Triage Process Model）的基础上,提出了一种改进的计算机取证领域的分流过程模型ICFFTPM（an Improved CFFTPM）。与CFFTPM模型相比,该模型更完整、更具体,并且可以方便地运用于实际的数字取证调查中,适用于多种计算机犯罪案件的侦破。