Search - Anomaly

[AI-NN-PR] NSA

Description: 这个是人工免疫系统中的反向选择算法(Negative Selection Aglorithm)的编程实例,它主要用于异常检测方面。请多指教！-this artificial immune system is the inverse algorithm (A Negative Selection glorithm) programming examples, it was mainly used anomaly detection area. Please advise!
Platform: | Size: 1024 | Author: HaicoLi | Hits:

[AI-NN-PR] COMPUTEG

Description: computes the gravitational acceleration vector at a specified ％ ECF location using the JGM2 gravitational ellipsoid only. ％ Higher-order gravity terms (the "gravity anomaly") are ％ ingnored. Only the pure ellipsoid is used. -computes the gravitational acceleration vector at a specified ECF location using the JGM2 gravitational ellipsoid only. Higher-order gravity terms (the gravity anomaly ) are ingnored. Only the pure ellipsoid is used.
Platform: | Size: 4096 | Author: huguangfeng | Hits:

[Other] 276

Description: 在现有的单层马尔科夫链异常检测模型基础上,提出一种崭新的两层模型.将性质上有较大差异的两个过程,不同的请求和同一请求内的系统调用序列,分为两层,分别用不同的马尔可夫链来处理.两层结构可以更准确地刻画被保护服务进程的动态行为,因而能较大地提高异常的识别率,降低误警报率.-In the existing single-layer Markov chain model for anomaly detection based on a new two-tier model. Will have a larger difference in the nature of the two processes, different requests and requests within the same system call sequence, sub- for a two-tier, respectively, in different Markov chain to deal with it. a two-tier structure can be more accurately portray the process of protection services by the dynamic behavior, which can greatly improve the identification of abnormal rate and reduce false alarm rate.
Platform: | Size: 356352 | Author: 杨奇 | Hits:

[Special Effects] 0807

Description: 基于背景减除的时间差分法，可以有效的提取出前景，并且可以进行异常检测-Background subtraction based on the time difference method, can effectively extract the prospects, and anomaly detection can be
Platform: | Size: 6846464 | Author: wangzhen | Hits:

[Graph program] Prototype

Description: 视频异常检测须安装jmf 参考论文 Robust Real-Time Unusual Event Detection-Video anomaly detection should be installed JMF reference papers Robust Real-Time Unusual Event Detection
Platform: | Size: 1939456 | Author: 赵欣 | Hits:

[matlab] qpso

Description: 在网络异常检测中,为了提高对异常状态的检测率，降低对正常状态的误判率,本文提出一种基于量子粒子群优化算法训练小波神经网络进行网络异常检测的新方法。利用量子粒子群优化算法(QPSO)训练小波神经网络,将小波神经网络(WNN)中的参数组合作为优化算法中的一个粒子,在全局空间中搜索具有最优适应值的参数向量。- In order to improve the detection rate for anomaly state and reduce the false positive rate for normal state in the network anomaly detection, a novel method of network anomaly detection based on constructing wavelet neural network (WNN) using quantum-behaved particle swarm optimization (QPSO) algorithm was proposed. The WNN was trained by QPSO.
Platform: | Size: 1024 | Author: liang | Hits:

[Special Effects] RX

Description: 此算法使用于单波段或者多波段图像中的非监督异常检测，性能很好~-The algorithm used in single-band or multi-band image unsupervised anomaly detection, performance very good ~
Platform: | Size: 1024 | Author: 朱阳阳 | Hits:

[Other systems] tdu70

Description: 重力异常的向上延拓程序，很实用，推荐地球物理学生学习-Gravity anomaly upward extension procedure is very useful, recommended geophysics students
Platform: | Size: 1024 | Author: 许家姝 | Hits:

[OS program] p2ptrafficanomalydetection

Description: p2p异常流量检测，基于传输层特征检测，能检测出基本P2P应用所产生的P2P流量-p2p traffic anomaly detection
Platform: | Size: 1271808 | Author: 林若辰 | Hits:

[Other] DDoSattackIPtraceback

Description: 一篇关于DDOS异常检测，找到IP攻击源的论文。对学习网络安全的很有帮助-Anomaly detection on a DDOS to find the source IP attack on the papers. Very helpful for learning network security
Platform: | Size: 408576 | Author: yihoumei | Hits:

[Windows Develop] KRLS

Description: Multivariate Online Anomaly Detection Using Kernel Recursive Least Squares
Platform: | Size: 3072 | Author: 钱叶魁 | Hits:

[Windows Develop] ziyuanfenxi

Description: 这是一个对运行程序进行内存资源分析的软件，是进行软件破解，运行动态跟踪，汉化，异常纠错的好帮手，个人认为挺实用，希望对大家有所帮助-This is a process of memory resources to run the analysis software, the software is cracked, run the dynamic tracking, localization, anomaly correction has been extremely helpful that the very use of personal, we want to help
Platform: | Size: 3012608 | Author: 樊福剑 | Hits:

[Industry research] AnAnomalyBasedApproachforIntrusion

Description: A new system for web attack detection is presented. It follows the anomaly-based approach, therefore known and unknown attacks can be detected. The system relies on a XML file to classify the incoming requests as normal or anomalous. The XML file, which is built from only normal traffic, contains a description of the normal behavior of the target web application statistically characterized. Any request which deviates from the normal behavior is considered an attack. The system has been applied to protect a real web application. An increasing number of training requests have been used to train the system. Experiments show that when the XML file has enough information to closely characterize the normal behavior of the target web application, a very high detection rate is reached while the false alarm rate remains very low.
Platform: | Size: 688128 | Author: keerthi | Hits:

[Windows Develop] AttacksClassificationinAdaptivIntrusion

Description: Recently, information security has become a key issue in information technology as the number of computer security breaches are exposed to an increasing number of security threats. A variety of intrusion detection systems (IDS) have been employed for protecting computers and networks from malicious network-based or host-based attacks by using traditional statistical methods to new data mining approaches in last decades. However, today s commercially available intrusion detection systems are signature-based that are not capable of detecting unknown attacks. In this paper, we present a new learning algorithm for anomaly based network intrusion detection system using decision tree algorithm that distinguishes attacks from normal behaviors and identifies different types of intrusions. Experimental results on the KDD99 benchmark network intrusion detection dataset demonstrate that the proposed learning algorithm achieved 98 detection rate (DR) in comparison with other existing methods.-Recently, information security has become a key issue in information technology as the number of computer security breaches are exposed to an increasing number of security threats. A variety of intrusion detection systems (IDS) have been employed for protecting computers and networks from malicious network-based or host-based attacks by using traditional statistical methods to new data mining approaches in last decades. However, today s commercially available intrusion detection systems are signature-based that are not capable of detecting unknown attacks. In this paper, we present a new learning algorithm for anomaly based network intrusion detection system using decision tree algorithm that distinguishes attacks from normal behaviors and identifies different types of intrusions. Experimental results on the KDD99 benchmark network intrusion detection dataset demonstrate that the proposed learning algorithm achieved 98 detection rate (DR) in comparison with other existing methods.
Platform: | Size: 312320 | Author: keerthi | Hits:

[Crack Hack] protocol-anomaly-detection-network-based-intrusio

Description: A taxonomy was developed by Axelsson to define the space of intrusion detection technology and classify IDSs. The taxonomy categorizes IDSs by their detection principle and their operational aspects. The two main categories of detection principles are signature detection and anomaly detection. The remainder of this paper will compare the two categories of detection principles and describe a new type of anomaly detection based on protocol standards. While the taxonomy applies to both host-based and network-based IDSs, and more particularly protocol anomaly filters. This is the result of research work done at Defcom Sweden, Stockholm.
Platform: | Size: 82944 | Author: sinsin | Hits:

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