基于SURF特征提取和Brute-Force搜索的图像匹配算法

针对传统图像匹配算法面临的特征提取的信息较少,匹配成功率不高以及匹配速率较低等问题,提出基于SURF特征提取和Brute-Force搜索的图像匹配算法。利用SURF算法中的Hessian矩阵来获取图像中鲁棒性较好的突变点,并使用不同尺寸的滤波器同时处理尺寸空间多层图像的突变点,以此来提高匹配速率,最后采用Brute-Force搜索算法对图像特征点进行最佳匹配,以此来提高匹配成功率。实验表明,该算法在图像匹配效果和匹配效率方面都表现良好。

Network Log-Based SSH Brute-Force Attack Detection Model

The rapid advancement of IT technology has enabled the quick discovery,sharing and collection of quality information,but has also increased cyberattacks at a fast pace at the same time.There exists no means to block these cyberattacks completely,and all security policies need to consider the possibility of external attacks.Therefore,it is crucial to reduce external attacks through preventative measures.In general,since routers located in the upper part of a firewall can hardly be protected by security systems,they are exposed to numerous unblocked cyberattacks.Routers block unnecessary services and accept necessary ones while taking appropriate measures to reduce vulnerability,block unauthorized access,and generate relevant logs.Most logs created through unauthorized access are caused by SSH brute-force attacks,and therefore IP data of the attack can be collected through the logs.This paper proposes a model to detect SSH brute-force attacks through their logs,collect their IP address,and control access from that IP address.In this paper,we present a model that extracts and fragments the specific data required from the packets of collected routers in order to detect indiscriminate SSH input attacks.To do so,the model multiplies a user’s access records in each packet by weights and adds them to the blacklist according to a final calculated result value.In addition,the model can specify the internal IP of an attack attempt and defend against the first 29 destination IP addresses attempting the attack.

面向入侵检测的模式匹配算法研究

在入侵检测系统的实现中,关键部分是检测引擎的实现。而在检测引擎的实现中,关键的是数据分析模块。对于基于规则的入侵检测来说,模式匹配算法非常重要,它直接影响到系统的准确性和实时性能。论文主要研究了BruteForce算法,Boyer-Moore算法,Aho-Corasick算法,Set-wiseBoyer-Moore-Horspool算法,Aho-Corasick_Boyer-Moore算法。

KMP算法与特殊子串滑动算法整合的构想与实践

在数据结构模式匹配算法中,Brute-Force算法是一个重要的基础算法,但是在性能上远不及KMP算法。而理解KMP及其改进算法是一个复杂的问题,其关键是KMP函数的求解过程。通过特殊子串滑动算法与KMP算法整合的实践,简化了特殊问题,省略了KMP函数的求解过程,在很大程度上提高了模式匹配问题的工作效率。

基于SURF特征点的图像拼接算法

本文采用基于SURF特征点的图形拼接算法,首先检测SURF特征点,进行特征向量的提取,利用Brute-Force算法,对图像的特征向量进行初步匹配;利用RANSAC模型估计算法,将匹配进行提纯,计算出两幅图像之间的坐标变换模型;最后根据坐标变换模型,将两幅图像映射为一幅图像,实现图像拼接。实验结果显示本文算法效果显著。

基于自适应筛选Harris角点检测的快速图像配准算法

针对传统Harris角点检测算法的图像配准过程计算量大、速度慢等问题,提出一种快速预筛选Harris角点检测算法。首先通过FAST算法快速排除大量非特征点,再通过抑制半径解决FAST角点聚簇现象,然后在FAST角点邻域内筛选出Harris角点,最后采用Brute-Force匹配方式得到精准匹配。实验结果表明:所提改进算法不仅提高了角点检测速度而且减少了冗余角点数量,在图像配准过程中有效提高了配准速度与精度,配准效果良好。

Efficient quantum private comparison protocol based on one direction discrete quantum walks on the circle

We propose an efficient quantum private comparison protocol firstly based on one direction quantum walks.With the help of one direction quantum walk,we develop a novel method that allows the semi-honest third party to set a flag to judge the comparing result,which improves the qubit efficiency and the maximum quantity of the participants’secret messages.Besides,our protocol can judge the size of the secret messages,not only equality.Furthermore,the quantum walks particle is disentangled in the initial state.It only requires a quantum walks operator to move,making our proposed protocol easy to implement and reducing the quantum resources.Through security analysis,we prove that our protocol can withstand well-known attacks and brute-force attacks.Analyses also reveal that our protocol is correct and practical.

The m-delay Autoregressive Model with Application

The classical autoregressive(AR)model has been widely applied to predict future data usingmpast observations over five decades.As the classical AR model required m unknown parameters,this paper implements the AR model by reducing m parameters to two parameters to obtain a new model with an optimal delay called as the m-delay AR model.We derive the m-delay AR formula for approximating two unknown parameters based on the least squares method and develop an algorithm to determine optimal delay based on a brute-force technique.The performance of them-delay AR model was tested by comparing with the classical AR model.The results,obtained from Monte Carlo simulation using the monthly mean minimum temperature in PerthWestern Australia from the Bureau of Meteorology,are no significant difference compared to those obtained from the classical AR model.This confirms that the m-delay AR model is an effective model for time series analysis.

Chaotic Encryption Scheme Using 1-D Chaotic Map

This paper proposes three different chaotic encryption methods using 1-D chaotic map known as Logistic map named as Logistic, NLFSR and Modified NLFSR according to the name of chaotic map and non-linear function involved in the scheme. The designed schemes have been crypt analyzed for five different methods for testing its strength. Cryptanalysis has been performed for various texts using various keys selected from domain of key space. Logistic and NLFSR methods are found to resist known plaintext attack for available first two characters of plaintext. Plaintext sensitivity of both methods is within small range along with medium key sensitivity. Identifiability for keys of first two of the scheme has not been derived concluding that methods may prove to be weak against brute-force attack. In the last modified scheme avalanche effect found to be improved compared to the previous ones and method is found to resist brute-force attack as it derives the conclusion for identifiability.

Optimal Power System Restoration and Reconfiguration in Distribution Circuit Using BFAM and BPSO

This paper approaches the problem of restoring a faulted area in an electric power distribution system after locating and isolating the faulted block and reconfiguring the system. Through this paper we are going to explain the power system restoration technique using brute-force attack method (BFAM) and binary particle swarm optimization (BPSO). This is a technique based on the possible combination in mathematical analysis which is explained in the introduction. After isolating the fault, main concentration will be towards the reconfiguration of the restored system using BPSO. Here due to fault in the system near-by agent will be affected and become useless and will go in the non-working mode. Now in order to restore these near-by loads we will give a new connection called NO (Normally Open. Using these switch system will be restored with power availability. After restoration using the BFAM, the BPSO will be used in order to provide the stable configuration. The output of the BFAM will be used as input for the BPSO and then we will reconfigure our system in order to provide the stable configuration. The effectiveness of the proposed BFAM and BPSO is demonstrated by simulating tests in a proposed distribution network and verified the results using the Matlab and C programming.

Research on Linux Kernel Version Diversity for Precise Memory Analysis

The diversity of Linux versions brings challenges to Linux memory analysis,which is an established technique in security and forensic investigations.During memory forensics,kernel data structures are essential information.Existing solutions obtain this information by analyzing debugging information or by decompiling kernel functions to handle a certain range of versions.In this paper,by collecting and analyzing a number of Linux versions,we characterize the properties of different Linux kernel versions and how struct offsets change between versions.Furthermore,the Linux kernel provides over 10,000 configurable features,which leads to different kernel structure layouts for the same kernel version.To deal with this problem,we propose a method of identifying kernel struct layout based on brute-force matching.By examining the relationships between kernel structures,common features are extracted and exploited for brute-force matching.The experimental results show that the proposed technology can deduce structure member offsets accurately and efficiently.

数字航空影像与机载点云的配准参数优化及对应数据集构建

数字航空影像和机载点云之间的配准参数精度会直接影响到配准效果,利用共线方程及影像特征点和点云特征点之间计算相似性测度的方法进行参数优化,有效避免了由于初始参数误差导致的配准偏差。首先,提取航空影像及激光雷达(light detection and ranging,LiDAR)点云的特征点;然后,根据初始配准参数及距离误差计算影像与点云之间的匹配点对;最后,通过强制搜索(brute-force,BF)优化方法来寻找更加精确的匹配参数。此外,还构建了2D-3D对应区域的数据集,用于航空影像和机载LiDAR数据配准的相关研究。

Constrained query of order-preserving submatrix in gene expression data

Order-preserving submatrix （OPSM） has become important in modelling biologically meaningful subspace cluster, capturing the general tendency of gene expressions across a subset of conditions. With the advance of microarray and analysis techniques, big volume of gene expression datasets and OPSM mining results are produced. OPSM query can efficiently retrieve relevant OPSMs from the huge amount of OPSM datasets. However, improving OPSM query relevancy remains a difficult task in real life exploratory data analysis processing. First, it is hard to capture subjective interestingness aspects, e.g., the analyst＇s expectation given her/his domain knowledge. Second, when these expectations can be declaratively specified, it is still challenging to use them during the computational process of OPSM queries. With the best of our knowledge, existing methods mainly fo- cus on batch OPSM mining, while few works involve OPSM query. To solve the above problems, the paper proposes two constrained OPSM query methods, which exploit userdefined constraints to search relevant results from two kinds of indices introduced. In this paper, extensive experiments are conducted on real datasets, and experiment results demonstrate that the multi-dimension index （cIndex） and enumerating sequence index （esIndex） based queries have better performance than brute force search.