Applying Intrusion Detection Algorithms on the KDD-99 Dataset
نویسندگان
چکیده
منابع مشابه
Application of Machine Learning Algorithms to KDD Intrusion Detection Dataset within Misuse Detection Context
A small subset of machine learning algorithms, mostly inductive learning based, applied to the KDD 1999 Cup intrusion detection dataset resulted in dismal performance for user-to-root and remote-to-local attack categories as reported in the recent literature. The uncertainty to explore if other machine learning algorithms can demonstrate better performance compared to the ones already employed ...
متن کاملNeural Networks Based Feature Selection from KDD Intrusion Detection Dataset
We present the application of a distinctive feature selection method based on neural networks to the problem of intrusion detection, in order to determine the most relevant network features. We use the same procedure for feature selection and for attack detection, which gives more consistency to the method. We apply this method to a case study and show its advantages compared to some existing f...
متن کاملProposed Approach for Intrusion Detection on KDD Dataset by Hybrid Classifiers
With the rapid increase of internet technology, the malicious activities on the network are also increasing. So the use of an efficient method is must to detect the intrusion. Security for all networks is becoming a big problem. In this paper we proposed hybrid approach of classifier with Adaptive boost with SVM RBF.
متن کاملNetwork Intrusion Detection Using Hybrid Simplified Swarm Optimization and Random Forest Algorithm on Nsl-Kdd Dataset
During the last decade the analysis of intrusion detection has become very significant, the researcher focuses on various dataset to improve system accuracy and to reduce false positive rate based on DAPRA 98 and later the updated version as KDD cup 99 dataset which shows some statistical issues, it degrades the evaluation of anomaly detection that affects the performance of the security analys...
متن کاملWhy machine learning algorithms fail in misuse detection on KDD intrusion detection data set
A large set of machine learning and pattern classification algorithms trained and tested on KDD intrusion detection data set failed to identify most of the user-toroot and remote-to-local attacks, as reported by many researchers in the literature. In light of this observation, this paper aims to expose the deficiencies and limitations of the KDD data set to argue that this data set should not b...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Production Systems and Information Engineering
سال: 2019
ISSN: 1785-1270
DOI: 10.32968/psaie.2019.004