路由信息的攻击对AODV协议性能的影响分析

AODV协议是移动自组网络中一种按需反应的表驱动路由协议。在移动自组网中，每个节点既是计算机又是路由器，容易遭受基于路由信息的网络攻击，而现今的路由协议基本没有考虑到该问题。本文在分析移动自组网中针对路由信息主要攻击方法的基础上，建立了主动性和自私性两个攻击模型，并且在AODV协议中扩充实现了这两类攻击行为。通过对模拟结果的分析和比较，讨论了路由信息的攻击对AODV协议性能的影响，并进一步探讨了针对基于路由信息攻击的防御措施。     

黑客网络攻击及其防护措施

首先阐述了目前计算机网络中存在的安全问题，接着分析了各种常见的网络攻击及其防护措施。     

A Robust Algorithm for Watermarking 2D Vector Maps with Low Shape-Distortions

The technique of watermarking has been introduced into 2D vector maps for many potential applications such as protecting the copyright of important GIS （geographical information system） data and tracing the data source of military maps. In most previous works, although the validity of the map data could be preserved during the embedding procedure, the shape-distortions of the map elements are usually neglected which would tend to degrade the invisibility of the watermarking schemes. A shape-preserving algorithm for watermarking 2D vector maps is presented in this paper. A 1D distance sequence extracted from the original map is adopted as the cover data instead of 2D coordinates. A watermark bit is represented by changing the distributions of the cover data. The embedding procedure induces lower shape-distortions than in former works. Experimental results indicate better invisibility of the proposed scheme, as well as its robustness to certain attacks such as map simplification, interpolation, additive noise and most geometric transforms.     

针对RFID身份认证协议——ARAP协议的攻击及改进

证明了针对匿名RFID身份认证协议ARAP协议可以进行假冒伪造攻击,并提出了改进版的ARAP协议。攻击的实质在于协议中运用的异或运算会将相同的值消去,或者可以设计特定的随机数实现重放攻击。提出了一种新的运算操作———置换操作,并在改进版的ARAP协议中将原协议的部分异或运算改为置换操作。改进版的ARAP协议还能抵抗跟踪攻击、非同步攻击和重放攻击等。     

电力系统中假数据注入攻击研究

假数据注入攻击是电力系统安全研究的重要问题之一,对智能电网发展趋势下的电力系统安全、稳定运行具有重要的意义.综述了电力系统中假数据注入攻击的研究进展,分析了EMS和假数据注入攻击的原理,并对假数据注入攻击研究工作进行了介绍,最后总结了研究现状中存在的问题以及需要进一步研究的工作.     

一种双矩阵组合公钥算法

组合公钥算法中存在选择共谋攻击、随机共谋攻击和线性分析共谋攻击.本算法中用户的私钥是基本私钥与辅助私钥的逆元模乘的结果,基本私钥与辅助私钥分别由基本私钥矩阵和辅助私钥矩阵中的元素组合生成,用户的私钥间不存在线性关系.经过分析,本算法可以抵抗组合公钥算法中存在的选择共谋攻击和随机共谋攻击,并且辅助密钥矩阵的大小可以根据需...     

SQL注入攻击及其预防方法研究

SQL注入攻击是黑客常用的网络攻击手段之一。文章分析了SQL注入攻击的原理和攻击步骤,针对性地提出了从程序编写和服务器设置两方面有效预防SQL注入攻击的方法。     

Confidentiality of a selectively encrypted H.264 coded video bit-stream

It is an assumption that selective encryption does not strongly protect confidentiality owing to the partial visibility of some video data. This is because, though encryption keys may be difficult to derive, an enhanced version of selectively encrypted video sequence might be found from knowledge of the unencrypted parts of the sequence. An efficient selective encryption method for syntax elements of H.264 encoded video was recently proposed at the entropy coding stage of an H.264 encoder. Using this recent scheme as an example, the purpose of this paper is a comprehensive cryptanalysis of selectively encrypted H.264 bit-streams to contradict the previous assumption that selective encryption is vulnerable. The novel cryptanalysis methods presented in this paper analyze the ability of an attacker to improve the quality of the encrypted video stream to make it watchable. The conclusion is drawn that if the syntax elements for selective encryption are chosen using statistical and structural characteristics of the video, then the selective encryption method is secure. The cryptanalysis is performed by taking into account the probability distribution of syntax elements within the video sequence, the relationship of syntax elements with linear regression analysis and the probability of successfully attacking them in order to enhance the visual quality. The results demonstrate the preservation of distorted video quality even after considering many possible attacks on: the whole video sequence; each video frame; and on small video segments known as slices.     

基于k-距离与重加权M-估计量的鲁棒协同推荐算法(英文)

The existing collaborative recommendation algorithms have lower robustness against shilling attacks.With this problem in mind,in this paper we propose a robust collaborative recommendation algorithm based on k-distance and Tukey M-estimator.Firstly,we propose a k-distancebased method to compute user suspicion degree(USD).The reliable neighbor model can be constructed through incorporating the user suspicion degree into user neighbor model.The influence of attack profiles on the recommendation results is reduced through adjusting similarities among users.Then,Tukey M-estimator is introduced to construct robust matrix factorization model,which can realize the robust estimation of user feature matrix and item feature matrix and reduce the influence of attack profiles on item feature matrix.Finally,a robust collaborative recommendation algorithm is devised by combining the reliable neighbor model and robust matrix factorization model.Experimental results show that the proposed algorithm outperforms the existing methods in terms of both recommendation accuracy and robustness.     

FDI攻击下非线性多智能体系统分布式无模型自适应控制

为研究受到虚假数据注入攻击的单输入单输出非线性多智能体系统的分布式无模型自适应控制问题,提出了一种新的分布式动态线性化方法, 以获得非线性多智能体的等效线性数据模型。与现有多智能体的分布式无模型自适应控制在控制器设计中有所不同, 本文设计的控制器不需要网络拓扑结构的信息, 仅使用系统的输入输出数据。仿真算例验证了所提出的分布式无模型自适应控制算法可以实现多智能体系统的均方有界趋同控制。算法保证了多智能体系统在受到网络攻击时可以实现趋同控制目标。