基于启发式行为监测的手机病毒防治研究

快速发展的移动通信技术给人们带来新的应用和服务的同时,也吸引了手机病毒的攻击。本文总结了手机病毒的传播途径和共有特性,比较现有的防毒技术,结合手机的特点,提出一种基于启发式行为监测的手机病毒防治技术,采用隐马尔科夫模型启发式分析程序的行为,以阻止病毒的恶意行为,保护手机安全。     

A new approach based on a discrete hidden Markov model using the Rocchio algorithm for the diagnosis of heart valve diseases

Abstract: Application of the Doppler ultrasound technique in the diagnosis of heart diseases has been increasing in the last decade since it is non‐invasive, practicable and reliable. In this study, a new approach based on the discrete hidden Markov model (DHMM) is proposed for the diagnosis of heart valve disorders. For the calculation of hidden Markov model (HMM) parameters according to the maximum likelihood approach, HMM parameters belonging to each class are calculated by using training samples that only belong to their own classes. In order to calculate the parameters of DHMMs, not only training samples of the related class but also training samples of other classes are included in the calculation. Therefore HMM parameters that reflect a class's characteristics are more represented than other class parameters. For this aim, the approach was to use a hybrid method by adapting the Rocchio algorithm. The proposed system was used in the classification of the Doppler signals obtained from aortic and mitral heart valves of 215 subjects. The performance of this classification approach was compared with the classification performances in previous studies which used the same data set and the efficiency of the new approach was tested. The total classification accuracy of the proposed approach (95.12%) is higher than the total accuracy rate of standard DHMM (94.31%), continuous HMM (93.5%) and support vector machine (92.67%) classifiers employed in our previous studies and comparable with the performance levels of classifications using artificial neural networks (95.12%) and fuzzy‐C‐means/CHMM (95.12%).     

面向移动节点定位的传感器网络动态休眠调度机制

由于能量受限的传感器节点一般多采用低功耗的工作方式,即在休眠状态和唤醒状态之间切换,因此,当对移动节点进行定位时,锚节点可能会因为处于休眠状态而没有响应移动节点的定位请求,从而导致定位失败.提出一种基于预唤醒的动态休眠调度机制P-SWIM,该机制提前通知移动节点周边的锚节点进入全勤的工作方式,而网络内其他锚节点则仍然处于低功耗的工作方式.通过P-SWIM,目标节点能够有效地维持足够高的锚节点连通度,从而保证了定位的成功率和精度.实验结果表明,移动节点定位方法采用P-SWIM相比于采用静态休眠调度机制(如RIS和GAF)能够显著地提高定位性能,且P-SWIM引入的运行功耗也是3种机制中最低的,比RIS和GAF最多可节省47.6%和60.2%的功耗.     

Web挖掘中的用户识别与虹膜识别技术

提出引入生物信息技术解决Web挖掘中的用户识别问题的设想及基于隐马尔科夫模型的虹膜识别方法,该方法仅需要虹膜的方向域作为输入参数,对虹膜图像的噪声与扭曲并不敏感,从而使该方法具有鲁棒性的特点。通过准确识别用户,克服了现有Web体系无状态的缺陷,可以实现对Web日志数据按“用户维”进行切片,使挖掘出的结果能够满足对用户个性化使用的需求。     

车载数据采集系统的无线解决方案研究

针对高校班车“一卡通”数据采集难的问题,基于固定无线接入技术提出了一种车载数据采集系统的无线解决方案,在嵌入式车载终端与基站间搭建简易、安全的短距离无线通信协议,利用低成本的射频读卡模块和无线通信模块,设计了一个基于车载读卡器的无线数据采集系统,为校园内设备间的远程数据通信提供了一个新的解决方案。该系统在公交“一卡通”的数据采集中有着广阔的应用前景。     

信息安全风险评估在信息安全体系建设中的应用分析

计算机网络和信息系统存在大量的安全隐患,通过风险评估及早发现安全隐患并采取相应的加固方案成为信息安全保障建设必不可少的一部分。本文介绍了开展风险评估的必要性、时机的选择,以及风险评估的内容和开展风险评估应遵循的原则。     

Lower estimation of approximation rate for neural networks

Let SFd and Πψ,n,d = { nj=1bjψ(ωj·x+θj) :bj,θj∈R,ωj∈Rd} be the set of periodic and Lebesgue’s square-integrable functions and the set of feedforward neural network (FNN) functions, respectively. Denote by dist (SF d, Πψ,n,d) the deviation of the set SF d from the set Πψ,n,d. A main purpose of this paper is to estimate the deviation. In particular, based on the Fourier transforms and the theory of approximation, a lower estimation for dist (SFd, Πψ,n,d) is proved. That is, dist(SF d, Πψ,n,d) (nlogC2n)1/2 . T...     

解决Ad Hoc入侵终端问题的MAC层协议

针对目前Ad Hoc网络多信道环境下MAC层存在的入侵终端问题,研究并提出了MAC层协议的改进方案.即在原有的动态信道分配MAC层协议基础上,增加了对入侵终端发生情况下信道重新分配机制和链路重新建立机制.使得Ad Hoc网络在入侵终端冲突发生的情况下,各节点得以迅速重新恢复通信.最后,对改进后协议的正确性和有效性进行仿真验证.     

嵌入式可信终端TPM接口的研究与实现

针对当前嵌入式系统中存在的安全问题,提出带有可信机制的安全解决方案.给出了嵌入式可信终端的总体架构,然后分析了TPM的访问接口,最后讨论了在通用嵌入式开发平台上通过SMBus总线扩展TPM的方法,并介绍了嵌入式系统TPM设备驱动程序的设计.     

基于混沌遗传算法的柔性机械手滑模控制器优化设计

针对柔性机械手动力学方程的非最小相位特点,本文提出一种柔性机械手的终端滑模控制方法,将关节电机转角和柔性模态变量的线性组合定义为柔性机械手系统的输出.通过输入输出线性化,将系统分解为输入输出子系统和零动态子系统.设计终端滑模控制策略,使输入输出子系统在有限时间收敛到零;利用混沌遗传算法优化控制器的设计参数,使零动态了系统在甲衡点附近渐近稳定,从而保证整个系统的渐近稳定.本文提出的方法设计过程简单,易于实现.仿真结果证明了设计的有效性.