对信息安全保密问题的思考

随着网络技术的飞速发展和应用的广泛深入，网络与信息安全保密问题，正日益突出地显示出来，受到越来越多的关注。本文围绕在网络环境下，信息安全保密所面临的威胁，从技术及管理两方面阐述了应采取的措施。     

计算机实验室的资源配置及维护策略

本文提出了采取NAT技术、VMware虚拟机技术及Serv-UFTP服务器对计算机实验室的资源进行合理配置,解决了IP地址不足、一机多用及用户数据存储;采取网络硬盘还原卡,实现了硬盘数据保护及网络对拷,达到了减少维护工作量的目的。     

计算机网络的建设

论述了计算机网络建设应用采取的指导思想,概要地介绍了当前网络建设的主流技术及多媒体技术在网络建设中的应用 。     

WDM光网的拥塞控制

Internet的快速发展对网络通信提出了更高的要求，拥塞控制已成为网络能否有效可靠运行的关键技术。提出在采用WDM技术的光因特网中，为保证网络业务服务质量，降低和控制网络拥塞，当前可采取的策略，并指出各策略的优劣、需要进一步研究的内容及发展趋势。     

确保网络安全的物理隔离技术

文章介绍了网络工程所采取的安全措施，并重点介绍了物理隔离技术，阐述了几种物理隔离技术对各种环境下网络和单机进行信息安全保护的措施及方法，以及它们各自的特点．     

ATM：基于转接技术的未来网络

该文介绍了ＡＴＭ网络，从技术的角度重点讨论了ＡＴＭ的核心－转接器技术，包括其基本结构和分类，剖析了两种典型的转接器结构，同时涉及了ＡＴＭ网络走向商业化存在的问题，指出了对于这样一个未来网络在现实中所应采取的态度。     

交换局域网在企业CAD技术中的应用

一、前言随着计算机网络技术的发展，企业级CAD技术已从单机应用向网络分布式CAD一体化方向迈进。传统共享介质型网络，在流量大时，由于冲突和重传增加使网络吞吐率严重下降，不能适应CAD／CAE／CAM一体化系统中网络交互信息量猛增对通信带宽及实时性提出的要求。本文就企业CAD系统的实施方案，采取交换式局域网构架结台WindowsNTServer4．0网络操作系统的几方面技术进行探讨。二、企业CAD网络技术应用随着计算机技术突飞猛进的发展，以网络为中心的企业计算机应用时代已经来临。由于微机新技术的突破，使微机售价不断下降，性能…     

信息系统的安全技术与方法

本文概要地说明了信息系统所面临的威胁和攻击及其应采取的安全对策及安全技术，重点介绍了信息系统实体、软件（包括ＯＳ和ＤＢ）、数据、网络的安全技术与方法和系统的运行安全与管理，以及系统安全评价方法与标准。     

视频流自适应传输技术研究

对当前视频流技术所采取的各种压缩算法及标准、传输协议、拥塞控制等技术进行了总结与分析，在此基础上对IP网络上的视频流自适应传输技术进行了研究，建立了实现该技术的框架。此技术框架综合了实时的视频自适应编码技术和有效的带宽自适应传输技术。实验结果表明，在对视频流的实时性要求高的应用上具有较突出的优势。     

网络信息安全技术原理、应用及展望

该文阐述了网络信息安全的五个组成方面,具体分析了在实际应用中的网络安全技术手段,探讨了国内外研究开发网络信息安全技术的现状、发展趋势及我们所应着重采取的策略.     

面向OpenStack/Ceph的虚拟机备份系统研究

针对OpenStack面临的虚拟机容灾备份问题,提出了一种基于Ceph存储快照的虚拟机容灾备份系统,备份时对虚拟机存储在Ceph中的磁盘生成快照,再根据备份要求计算有效数据或者变化数据,保存虚拟机的配置信息以及磁盘数据,恢复时自动创建相同配置的虚拟机并将当前快照点的磁盘数据恢复到该虚拟机中.实验表明,该方法比OpenStack的快照备份方法能有效节省备份时间和存储空间,并且可以实现后者不具有的增量备份、多磁盘备份等功能.     

一种基于ESXi的虚拟机备份与恢复系统

设计并实现了一种基于ESXi的虚拟机备份与恢复系统。通过远程抓取虚拟机变化的数据块,并将其备份到备份服务器来实现灾难冬份,通过将备份数据写回到远程虚拟机来实现灾难恢复。系统只需部署于备份服务器,便可快速高效地备份虚拟机。并不会增加虚拟机的额外负载;提供Web服务器可使用户远程控制备份恢复任务;支持多种备份与恢复策略。     

面向流式数据处理系统的高效故障恢复方法

针对流式数据处理系统Flink无法高效处理单点故障的问题,提出了一种基于增量状态和备份的故障容错系统Flink+。首先,提前建立备份算子和数据通路;然后,对数据流图中的输出数据进行缓存,必要时使用磁盘;其次,在系统快照时进行任务状态同步;最后,在系统故障时使用备份任务和缓存的数据恢复计算。在系统实验测试中,Flink+在无故障运行时没有显著增加额外容错开销;而在单机和分布式环境下处理单点故障时,与Flink系统相比,所提系统在单机8任务并行度下故障恢复时间减少了96.98%,在分布式16任务并行度下故障恢复时间减少了88.75%。实验结果表明,增量状态和备份方法一起使用可以有效减少流式系统单点故障的恢复时间,增强系统的鲁棒性。     

Data aggregation in wireless sensor network using SVM-based failure detection and loss recovery

Abstract

In wireless sensor network, data aggregation can cause increased transmission overhead, failures, data loss and security-related issues. Earlier works did not concentrate on both fault management and loss recovery issues. In order to overcome these drawbacks, in this paper, a reliable data aggregation scheme is proposed that uses support vector machine (SVM) for performing failure detection and loss recovery. Initially, a group head, selected based on node connectivity, splits the nodes into clusters based on their location information. In each cluster, the cluster member with maximum node connectivity is chosen as the cluster head. When the aggregator receives data from the source, it identifies node failures in the received data by classifying the faulty data using SVM. Furthermore, a reserve node-based fault recovery mechanism is developed to prevent data loss. Through simulations, we show that the proposed technique minimises the transmission overhead and increases reliability.     

Methods and software tools to support combined binary code analysis

Methods and tools for binary code analysis developed in the Institute of System Programming, Russian Academy of Sciences, and their applications in algorithm and data format recovery are considered. The executable code of various general-purpose CPU architectures is analyzed. The analysis is performed given no source codes, debugging information, and specific OS version requirements. The approach implies collecting a detailed machine instruction level execution trace; a method for successively increasing presentation level; extraction of algorithm’s code followed by structuring of both code and data formats it processes. Important results are obtained, viz. an intermediate representation is developed that allows carrying out most preliminary processing tasks and algorithm code extraction without having to focus on specifics of a given machine; and a method and software tool are developed for automated recovery of network message and file formats. The tools are integrated into the unified analysis platform that supports their combined use. The architecture behind the platform is also described. Examples of its application to real programs are given.     

人工智能的逆向工程——反向智能研究综述

在大数据时代,人工智能得到了蓬勃发展,尤其以机器学习、深度学习为代表的技术更是取得了突破性进展.随着人工智能在实际场景中的广泛应用,人工智能的安全和隐私问题也逐渐暴露出来,并吸引了学术界和工业界的广泛关注.以机器学习为代表,许多学者从攻击和防御的角度对模型的安全问题进行了深入的研究,并且提出了一系列的方法.然而,当前对机器学习安全的研究缺少完整的理论架构和系统架构.从训练数据逆向还原、模型结构反向推演、模型缺陷分析等角度进行了总结和分析,建立了反向智能的抽象定义及其分类体系.同时,在反向智能的基础上,将机器学习安全作为应用对其进行简要归纳.最后探讨了反向智能研究当前面临的挑战以及未来的研究方向.建立反向智能的理论体系,对于促进人工智能健康发展极具理论意义.     

ATM电路仿真设备中自适应时钟恢复算法的设计与实现

ATM技术很好地解决了数据的透明传送问题,但定时信息在ATM网中的传递透明性由于统计复用而受到损害,而时钟同步是电路仿真业务的关键问题。文中介绍了自适应时钟恢复算法的背景,原理及其具体设计方案,提出了一种基于状态机的算法,对时钟捕捉的精确度作了理论分析,并给出来部分实验结果。     

Transfer of Fixation Using Affine Structure: Extending the Analysis to Stereo

This paper describes an algorithm for maintaining fixation upon a 3D body-centred point using 3D affine transfer, extending an earlier monocular method to stereo cameras. Transfer is based on corners detected in the image and matched over time and in stereo. The paper presents a method using all available matched data, providing immunity to noise and poor conditioning. The algorithm, implemented at video rates on a multi-processor machine, incorporates controlled degradation in the presence of insufficient data. Results are given from experiments using a four-axis active stereo camera platform, first which show the greater stability of the fixation point over the monocular method, both as it appears in the image and occurs in the scene; and, secondly, which show the recovery and evolution of 3D affine structure during fixation. It is shown that fixation and explicit structure recovery can occur separately, allowing the information required for gaze control to be computed in a fixed time.     

Dynamic neural control for a plasma etch process

This paper presents results and commentary on using a cascade neural network and a policy-iteration optimization routine to provide suggested process setpoints for recovery from long-term machine drift in a LAM 4520 6-in dielectric etcher. Traditional plasma etch variables such as pressures, gas flows, temperatures, RF power, etc, are combined with a generalized representation of the time dependent effects of maintenance events to predict film etch rates, uniformity, and selectivity, A cascade neural-network model is developed using 15 months of data divided into train, test, and validation sets. The neural model both fits the validation data well and captures the nonuniformity in the in-control region of the machine. Two control algorithms use this model in a predictive configuration to identify input state changes, including maintenance events, to bring an out-of-control situation back into control. The overall goal of the optimization is to reduce equipment downtime and decrease cost of ownership of the tool by speeding up response time and extending the lifetime of consumable parts. The optimization routines were tested on 11 out-of-control situations and successfully suggested reasonable low-cost solutions to each for bringing the system back into control.