Intrusion Detection Based on Adaptive Immune Classifier

The distribution properties of the normally data and anomaly data in the network connectivity features have huge differences ; therefore, there exist the low rate of detection and false positive rate problem for the traditional classifier which is applied to the network intrusion detection. An adaptive classifier based on the artificial immune cluster is presented. The new classifier adopts multi -granularities idea and it effectively eliminates the inconsistency between the classification algorithm and the clustering algorithm. Through the classification of the data sets in real variety of network intrusion data sets, experimental results show that the classifier has high detection rate and low false positive rate; it has better classification performance and generalization ability than RBF and BP classifiers.     

Clustering Detection Algorithms for Network Intrusions

Traditional abnormal detection methods need a reference model with a profile of normal action, but building the character profile and specifying threshold of abnormal alarm are difficult. So this paper puts forward intrusion detection in combination with clustering and data processing . This algorithm comes true dynamicly updating the center of cluster and the biggest distance within cluster with fast convergence. The effect is better with the help of pre-processing the data. By means of simulated experiments, this algorithm is proved feasible and efficient for unknown intrusion detection.     

Intrusion Detection Based on Data Mining

As computer networks play increasingly vital roles in modern society, information security becomes one of the most important research issues in the field of information technology. But intrusions cause a serious security risk, how to efficiently prevent and detect intrusions becomes one of hot research problems in the field of information supervision. The traditional process of building the model of intrusion detection is slow, whose cost of research and development is high. However, data mining has unique advantages in acquiring unknown knowledge. So, intrusion detection based on data mining becomes a hot issue. The research background, architectures, techniques, problems to be solved and the future direction are discussed after analyzing current status of network intrusion and situation of R&D on intrusion detection and data mining.     

Image edge detection algorithm in fuzzy domain

An image edge detection algorithm in fuzzy domain is proposed, which combines adaptive fuzzy enhancement and multi direction fuzzy morphology to detect the edges of fuzzy image. The adaptive fuzzy enhancement method enhances the fuzzy image within blocks with sliding windows to avoid losses of the real edges resulting from enhancing with single threshold for the whole image and lead strong adaptive ability to image region variance. The multi direction fuzzy mathematical morphology operates on the enhanced fuzzy image with structure elements of multiple different directions to extract the real edges with directionality and restrain non directional noise. Experiments show the algorithm can detect fuzzy image edge effectively with strong antinoise ability.     

Approach for Load State Detection in MIN

Some thoroughly research on the basic method for load state detection in MIN is introduced. Load sources of SCP and SSP in MIN are analyzed in detail after investigating the relationship between inter resource and load state in the system. And load detection parameters and model are presented. Moreover, a novel strategy to detect system load state based on fusion of multi detection data is presented. By some test, the theory and method are proved most feasible. Our research show that load state of MIN can be recognized by detecting utility of internal resource utilizing of single node in MIN, and multi redundant detecting data fusion is effective approach to improve the reliability and trust degree of the result.     

Adaptive Intrusion Detection System Based on Agent and Data Mining

Intrusion detection system is an essential component of network security protection mechanisms. Most intrusion detection system can not adapt the variation of network environment. Aiming at this problem, an adaptive strategy that composed of condition space and strategy space is proposed. The condition space describes the network environment and the strategy space describes the strategy. There is an exclusive strategy corresponds to a certain environment state in condition space. On the base of the adaptive strategy, an adaptive intrusion detection system based on agent and data mining is designed. The simulation experiments indicate that the adaptive strategy is effective.     

Application of Self-tuning Models to Air Handling Units for Fault Detection

Building management control systems (BMCS) are widely employed in modern buildings. The huge amount of data available on central stations and outstations provide rich information for fault diagnosis of HVAC systems. An online fault diagnosis method for variable air volume air handling units was presented using self-tuning HVAC component models. The model parameters are tuned online by using a genetic algorithm (GA) which minimizes the error between measured and estimated performance data, so high modeling accuracy is assured. If the error between measured and estimated performance data exceeds preset thresholds, it means the occurrence of faults or abnormalities in the air handling unit system. The statistical method of selecting thresholds also is presented. The fault detection method was tested and validated using data collected from real HVAC systems. The results of validation show that the fault detection method can be integrated in BMCS systems to detect faults in air handling unit systems efficiently.     

Automatic image analysis and spot classification for detection of fruit fly infestation in hyperspectral images of mangoes

Fruit fly infestation of mangos is a major concern for growers and exporters, leading to requirements for quarantine treatments such as vapor heat treatment or irradiation and subsequent reduction in quality and consumer acceptance. An on-line method for detection and removal of infested fruit would thus benefit producers and consumers. An algorithm has been developed to identify spots generated in hyperspectral images of mangoes infested with fruit fly larvae. The algorithm incorporates background removal, application of a Gaussian blur, thresholding, and particle count analysis to identify locations of infestations. Each of the four algorithm steps involves adjustable parameters which were iteratively tested to find the optimal combination for detection in terms of false positive and false negative results. For algorithm parameters selected to minimize false negative results, a false negative error rate of 1.0% was achieved with 11.1% false positive error and 6.0% overall error in heavily infested samples. For the same sample set, the lowest overall error rate achieved was 2.0%, with 1.0% false positive and 3.0% false negative. For samples with lower infestation rates, the error rates were much higher, the lowest overall error being 12.3%. This therefore demonstrates the feasibility of hyperspectral imaging for fruit fly detection while highlighting the need for technology with improved resolution and signal to noise ratio to allow detection of single larvae.     

Intrusion Detection Technology in Ad Hoc Network

With the rapid development of wireless network and mobile computing,the security of network becomes more important.As one of wireless mobile network,mobile Ad hoc network has new vulnerabilities that do not exist in a fixed wired network,and is susceptible to attacks.This paper introduces some methods which used in intrusion detection system and provides a new model of system based on multi-layer integrated distributed technology,especially recommend the protocol analyzing method in this system.     

智能视频分析的车辆异常行为检测方法

为验证公司自主研发的呋喃它酮代谢物化学发光微粒子检测试剂盒的检测效果,用化学发光微粒子免疫法和高效液相色谱串联质谱法对猪肉、鸡肉、鱼肉、虾4个样品中呋喃它酮代谢物残留量进行检测,比对两种方法试验结果间的差异。结果表明,使用直接竞争CLIA试剂盒检测动物性食品中呋喃它酮代谢物残留量,其特异性强,灵敏度较高,在猪肉、鸡肉、鱼肉、虾样品中0.2、0.4、0.8μg/kg 3个水平的加标回收率均在94.0%~101.0%之间,变异系数均小于15%,最低检测限分别为86.24、84.09、84.51、88.12 ng/kg;此方法与高效液相色谱串联质谱法检测实际样品的阴、阳性判断结果一致,其结果稳定、可靠,可满足现场快速检测动物组织中呋喃它酮代谢物残留的要求。     

大型商场建筑夏季冷负荷动态预测模型

夏季建筑冷负荷的正确预测是实现大型复杂中央空调优化运行、节能降耗的关键。笔者探讨了商场建筑冷负荷的主要影响因素,确定了建筑动态冷负荷预测模型的输入,提出了夏季基于新风机组供电频率的商场顾客率间接测量方法,解决了商场内顾客量难以检测的难题。还提出了AFC-HCMAC神经网络预测模型算法,实现了大型商场建筑冷负荷的动态预测。仿真结果表明:顾客率在商场冷负荷预测中占有重要地位,在冷负荷预测模型中增加商场顾客率可显著提高预测精度;AFC-HCMAC神经网络预测算法与传统的HCMAC神经网络算法比较,可有效降低神经网络节点数,提高预测精度。     

An edge detection method based on a good point set genetic algorithm

In order to improve the convergence rate of genetic algorithms based on edge detection, a novel edge detection method based on a good point set genetic algorithm (GGA) was proposed. The proposed method designed the crossover operation with the theory of good point set in which the progeny inherits the common genes of the parents which represent its family so as to improve the convergence rate of the genetic algorithm. Furthermore, before the algorithm was used for edge detection, the feature space of the image grey level was transformed into the feature space of the fuzzy entropy. Dissimilarity enhancement processing next was applied to the image by using a fuzzy entropy theory to filter the non edge pixels so as to reduce the scale of the solution domain. This approach offered another efficient way to improve the convergence rate. Experimental results show the proposed algorithm performs very well in terms of convergence rate. The detected edge image is well localized, thin, and robustly resistant to noise.     

Application of Serial Ports Simulation in a Non-communication Fault Detection Device of Distribution Networks

This paper summarizes two kinds of fault detection techniques for distribution automation, that is with and without communication in fault detection, and then analyzes their merits and shortcomings. Moreover, according to the development tendency of distribution automation techniques, this paper presents an approach, through which the noncommunication FTU devices can detect transient fault voltage of distribution systems effectually. To detect transient fault voltage without standby batteries, the PIC Single Chip microcomputer with low power consumption and DSP chip with powerful data processing capabilities are adopted to form a dual CPU system. To realize the communication between the two CPUs, the general I/O port,s of the DSP chip are firstly used to simulate the UART communication of the serial ports and communicate with the PIC Single Chip microcomputer. The novel FTU devices based on this approach are tested in static and dynamic simulation experiments, the results are satisfied.     

马铃薯A病毒液相芯片快速检测方法的建立

旨在建立可检测马铃薯A病毒(Potato virus A,PVA)的液相芯片快速检测技术,用Primer Premier 5.0软件对GenBank中PVA核苷酸序列进行分析,设计其特异性探针并用生物素标记。探针偶联荧光编码微球后与PVA的PCR产物杂交反应,用液相芯片检测仪检测荧光信号。结果显示该法具有较好的特异性,不与侵染马铃薯的番茄黑环病毒(Tomato black ring virus,TBRV)、马铃薯纺锤块茎类病毒(Potato spindle tuber viroid,PSTVd)、马铃薯Y病毒(Potato virus Y,PVY)及番茄斑萎病毒(Tomato spotted wilt virus,TSWV)反应;检测灵敏度约为10 pg/μL总RNA。该方法可用于PVA的快速检测。     

Improved Method of Small Weak Targets Detection Based On Background

An improvement method is given to detect small weak targets. It predicts the background gray and the actual gray of the current pixel molded by two predicting windows. The method can not only solve the edge blur problem of the traditional method, but fit for the detection of the bipolar targets. It can perform at a high calculation speed, which is an important improvement in the filed. In the process of real-time missile-tracking. The reliability and stability of detection require that the method cannot only solve the edge blur problem of the traditional method, but work well with the background no matter it is bright or dark. According to the experiment using the images provided by DX-1 missile-tracking project, the method is proved effective.     

Network Security Monitor

Illegal traffics on network can be actively detected by network security monitor An advanced system is given which can capture network data stream and intercept malicious attack, so as to alarm or take response action in real-time. The system is composed by sniffer, monitor control center, remote management unit,etc. Attack activities under surveillance can be distinguished by two methods,which are rule based method and statistics based method. Intrusion recognition by sniffer is the key technology of the system. In addition, dilemma between real-time data stream and high inquiry speed, as well as dynamic addition of attack rules contributes to the main concern of system design. Backdoor of The system can be self detected, while intelligent analysis and bi-directional surveillance ability has also been implemented. With all these advance features, the system is presented not only as a strong assistant to traditional network security products, but also an important tool for counter-fighting with rampant network intrusion nowadays.     

抗除草剂棉花LLCOTTON25的多重PCR检测方法

为了建立1种抗除草剂棉花LLCOTTON25多重PCR检测方法,根据抗除草剂棉花LLCOTTON25分子特征,同时选择棉花内源参照基因(SADI)、花椰菜花叶病毒启动子(P-Ca MV 35S)、根癌农杆菌终止子(T-NOS)和目的基因(bar)4个基因作为多重PCR(Polymerase chain reaction)检测基因,参照国家相关标准中的特异性引物序列,通过对反应条件的优化以及方法特异性和灵敏度测试,建立了可同时检测除内源基因外的3种外源目的基因的多重PCR检测体系。利用已知样品对本体系验证,抗除草剂棉花LLCOTTON25能被同时检出SADI、P-Ca MV 35S、T-NOS、bar等4个基因,而其他样品均不能被同时检出这4个基因。结果表明此体系可运用于抗除草剂棉花LLCOTTON25检测。     

River Water Quality Comprehensive Evaluation for Water Source Heat Pump

River water quality is one of the important conditions must be considered when river water source heat pump is used. It is also the key factor of efficiency of river water source heat pump. Based on analysis of the water quality factors which influence the river water source heat pump heat exchanger fouling, the main quality indicators and value are conformed. Using fuzzy comprehensive evaluation method and the actual monitoring data, quality classification of river water which is the source of water source heat pump is analyzed. For the difficulty of multiple indicators which need to detect and meet the related national standard in practical engineering application, the definition of scaling potential value is put forward. As the water quality comprehensive evaluation index of water source heat pump, the scaling potential value not only can consider the influence of the main water quality parameters on water source heat pump heat exchanger fouling, but also can conveniently and quickly provide direct basis for water quality judgment and system selection in the engineering application.     

应用纳米磁珠荧光PCR检测棉花曲叶病毒

 为了提供快速灵敏检测棉花曲叶病毒(Cotton leaf curl virus, CLCuV)的技术以防止其传播扩散,本研究根据CLCuV外壳蛋白基因（Coat protein, CP）保守序列设计了引物和TaqMan探针,并结合纳米磁珠(Magnetic nanoparticles, MNPs)建立了该病毒的MNP实时荧光PCR (Real-time PCR)检测方法。该方法检测阈值约为525 fg·μL^-1 DNA。通过对CLCuV、非洲木薯花叶病毒、烟草线条病毒、黄瓜花叶病毒及番茄斑萎病毒的检测表明,该方法具有良好的特异性;同时该方法无需任何PCR后处理,交叉污染风险小。本方法可用于CLCuV的快速检测。