密码协议的一种安全模型

将密码协议与密码算法视为一个系统,建立了密码协议系统的一种安全模型.基于假设/保证的组合推理技术提出了新的假设/保证推理规则和假设/保证推理算法,证明了该规则的完备性,实现了密码协议系统的模型检查,并重点解决了系统分解问题、假设函数的设定问题、进程+逻辑的系统特性描述问题等难题.以kerberos密码协议系统为例,利用该安全模型和假设/保证推理技术对密码协议系统进行了安全验证.

基于基因规划的主机异常入侵检测模型

异常检测技术假设所有的入侵行为都会偏离正常行为模式.尝试寻找一种新的异常入侵检测模型改善准确性和效率.模型利用应用程序的系统调用序列,通过基因规划建立了正常行为模式.模型的一个例程管理一个进程.当它发现进程的实际系统调用序列模式偏离正常的行为模式时,会将进程设标记为入侵,并采取应急措施.还给出了基因规划的适应度计算方法以及两个生成下一代的基本算子.通过与现有一些模型的比较,该模型具有更好的准确性和更高的效率.

基于模糊行为分析的移动自组网入侵检测

移动自组网络是一种不需要基础设施的网络．在这种网络中，移动节点是自组织的，并且需要互相提供网络路由服务．自组网络非常容易受到攻击，特别是内部攻击．提出了一个基于模糊行为分析的入侵检测方案，以检测网络内部的路由攻击．利用邻接节点监测，通过分析节点路由行为与路由规范的偏差，发现恶意行为．在数据分析的过程中引入了模糊路由行为分析的方法，大大降低了误报率．仿真实验表明，该方案能有效地检测出路由入侵行为，而将误报率控制在一个较低的水平．

一种基于移动代理自动优化的分布式入侵检测系统

随着网络技术的飞速发展，网络入侵检测系统需要处理大量的数据，处理能力的缺乏会引起入侵事件的漏报或误报，提高入侵检测系统的处理能力是目前急需解决的关键问题．AODIDS是一个由移动代理作为优化组件、多个分析结点及探测结点组成的可自动进行优化的分布式网络入侵检测系统．AODIDS的优化组件执行系统的性能评估，制定相应的优化策略，在规定的系统检测正确率的前提下平衡分配网络流量，从而尽可能地发挥整个系统的处理能力．

基于进程行为的异常检测模型

利用系统漏洞实施攻击是目前计算机安全面临的主要威胁.本文提出了一种基于进程行为的异常检测模型.该模型引入了基于向量空间的相似度计算算法和反向进程频率等概念,区分了不同系统调用对定义正常行为的不同作用,提高了正常行为定义的准确性;该模型的检测算法针对入侵造成异常的局部性特点,采用了局部分析算法,降低了误报率.

一种基于Agent的自适应的分布式入侵检测系统

针对传统分布式入侵检测系统组件之间依赖程度大、系统不够健壮且入侵检测系统自身结构固定不能适应入侵的变化的问题,提出了一种基于Agent的自适应的分布式入侵检测系统(简称AAA-DIDS)·AAADIDS采用Agent概念重新构造系统的组件,改进了分布式入侵检测系统由于高层节点单一无冗余而产生的可靠性差的缺陷,从构造上克服了分布式入侵检测系统的脆弱性·同时,AAADIDS系统采用智能技术构建了自适应的入侵检测系统模型,增加了系统应对入侵行为变化的智能性·AAA-DIDS系统相对于传统的分布式入侵检测系统有效地提高了系统自身的可靠性和针对外界变化的适应能力·

Effects of Noise and Detection Error in a Dynamic Adaptive Optics System

It is well known that noise and detection error can affect the performances of an adaptive optics (AO) system. Effects of noise and detection error on the phase compensation effectiveness in a dynamic AO system are investigated by means of a pure numerical simulation in this paper. A theoretical model for numerically simulating effects of noise and detection error in a static AO system and a corresponding computer program were presented in a previous article. A numerical simulation of effects of noise and detection error is combined with our previous numeral simulation of a dynamic AO system in this paper and a corresponding computer program has been compiled. Effects of detection error, readout noise and photon noise are included and investigated by a numerical simulation for finding the preferred working conditions and the best performances in a practical dynamic AO system. An approximate model is presented as well. Under many practical conditions such approximate model is a good alternative to the more accurate one. A simple algorithm which can be used for reducing the effect of noise is presented as well. When signal to noise ratio is very low, such method can be used to improve the performances of a dynamic AO system.

Novel approach for region merging and image segmentation for human-computer interaction

For the purpose of human-computer interaction (HCI), a vision-based gesture segmentation approach is proposed. The technique essentially includes skin color detection and gesture segmentation. The skin color detection employs a skin-color artificial neural network (ANN). To merge and segment the region of interest, we propose a novel mountain algorithm. The details of the approach and experiment results are provided. The experimental segmentation accuracy is 96.25%. (C) 2003 Society of Photo-Optical Instrumentation Engineers.

Detection of potential positive regulatory motifs of transcription in yeast introns by comparative analysis of oligonucleotide frequencies

We conducted a comparative statistical analysis of tetra- through hexanucleotide frequencies in two sets of introns of yeast genes. The first set consisted of introns of genes that have transcription rates higher than 30 mRNAs/h while the second set contained introns of genes whose transcription rates were lower than or equal to 10 mRNAs/h. Some oligonucleotides whose occurrence frequencies in the first set of introns are significantly higher than those in the second set of introns were detected. The frequencies of occurrence of most of these detected oligonucleotides are also significantly higher than those in the exons flanking the introns of the first set. Interestingly some of these detected oligonucleotides are the same as well known "signature" sequences of transcriptional regulatory elements. This could imply the existence of potential positive regulatory motifs of transcription in yeast introns. (C) 2003 Elsevier Ltd. All rights reserved.

Wavelet denoising and feature extraction of seismic signal for footstep detection

Seismic sensors are widely used to detect moving target in ground sensor networks. Footstep detection is very important for security surveillance and other applications. Because of non-stationary characteristic of seismic signal and complex environment conditions, footstep detection is a very challenging problem. A novel wavelet denoising method based on singular value decomposition is used to solve these problems. The signal-to-noise ratio (SNR) of raw footstep signal is greatly improved using this strategy. The feature extraction method is also discussed after denosing procedure. Comparing, with kurtosis statistic feature, the wavelet energy feature is more promising for seismic footstep detection, especially in a long distance surveillance.