Application of Immune Complement Algorithm to NSL-KDD Intrusion Detection Dataset
نویسندگان
چکیده
منابع مشابه
Network 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 کاملFeature Selection for Intrusion Detection using NSL-KDD
These days, network traffic is increasing due to the increasing use of smart devices and the Internet. Amount of the intrusion detection studies focused on feature selection or reduction because some of the features are irrelevant and redundant which results lengthy detection process and degrades the performance of an intrusion detection system (IDS). The purpose of this study is to identify im...
متن کاملApplication 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 کاملFeature Ranking and Support Vector Machines Classification Analysis of the NSL-KDD Intrusion Detection Corpus
Currently, signature based Intrusion Detection Systems (IDS) approaches are inadequate to address threats posed to networked systems by zero-day exploits. Statistical machine learning techniques offer a great opportunity to mitigate these threats. However, at this point, statistical based IDS systems are not mature enough to be implemented in realtime systems and the techniques to be used are n...
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: AL-Rafidain Journal of Computer Sciences and Mathematics
سال: 2012
ISSN: 2311-7990
DOI: 10.33899/csmj.2012.163705