نتایج جستجو برای: kdd cup 99
تعداد نتایج: 84698 فیلتر نتایج به سال:
In order to improve the efficiency of network intrusion detection, this paper proposes a wavelet transform based support vector machine ensemble algorithm. Firstly, we use wavelet transform to remove the redundant attributes from the original dataset. Then we train a support vector machine ensemble on the simplified dataset. As the wavelet transform in this algorithm can effectively remove the ...
In this chapter the anomaly detection by using Hybrid Artificial Immune Algorithm (HAIA) is presented. The HAIA is based on AIS and GA. In this research work, HAIA approach is used to develop Network Anomaly Detection System (NADS). The detector set is generated by using GA and the anomalies are identified using NSA which is based on AIS. The HAIA algorithm is tested with KDD Cup 99 benchmark d...
Intrusion detection is a problem that has attracted a great deal of attention from computer scientists recently, due to the exponential increase in computer attacks in recent years. DARPA KDD Cup 99 is a standard dataset for classifying computer attacks, to which several machine learning techniques have been applied. In this paper, we describe the results obtained using functional networks – a ...
Research in the field of computer and network science demands for tools and methodology to test their security effectively. Intrusion Detection System is used to perform the same with a fact that an intruder’s behavior will be noticeably different from that of a legitimate user and would exploit security vulnerabilities. Proposed here is a novel intrusion detection approach with the application...
We describe our wining solution for the KDD Cup Orange Challenge.
KDD 99 intrusion detection datasets, which are based on DARPA 98 dataset, provides labeled data for researchers working in the field of intrusion detection and is the only labeled dataset publicly available. Numerous researchers employed the datasets in KDD 99 intrusion detection competition to study the utilization of machine learning for intrusion detection and reported detection rates up to ...
The crux of the problem in KDD Cup 2016 involves developing data mining techniques to rank research institutions based on publications. Rank importance of research institutions are derived from predictions on the number of full research papers that would potentially get accepted in upcoming top-tier conferences, utilizing public information on the web. This paper describes our solution to KDD C...
This paper describes the solution of National Taiwan University for track 2 of KDD Cup 2012. Track 2 of KDD Cup 2012 aims to predict the click-through rate of ads on Tencent proprietary search engine. We exploit classification, regression, ranking, and factorization models to utilize a variety of different signatures captured from the dataset. We then blend our individual models to boost the pe...
In this paper, a two-phase method for computer network intrusion detection is proposed. In the first phase, a set of patterns (data) are clustered by the fuzzy c-means algorithm. In the second phase, outliers are constructed by a distance-based technique and a class label is assigned to each pattern. The KDD Cup 1999 data set is used for the experiment. The results show that, for binary classif...
In order to better apply the K-modes algorithm intrusion detection, this paper overcomes problems of existing based on rough set theory. Firstly, for problem clustering in initial class center selection, an selection Ini_Weight weighted density and overlap distance is proposed. Secondly, algorithm, a new WODKM Thirdly, applied detection obtain unsupervised model. The model detects by dividing c...
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