An intrusion detection system (IDS) is an active process or device that analyzes system and network activity for unauthorized entry. Nowadays many intrusion detection systems are developed based on many different machine learning techniques. Some of the models are based on single classifying techniques while some models are based on combining different classifying techniques, such as hybrid or ...

Intrusion Detection systems are increasingly a key part of system defense. Various approaches to Intrusion Detection are currently being used but they are relatively ineffective. Among the several soft computing paradigms, we investigated genetic algorithms and neural networks to model fast and efficient Intrusion Detection Systems. With the feature selection process proposed it is possible to ...

Anomaly detection in network traffic is one of the key techniques to ensure security future networks. Today, importance this topic even higher, since growing and there a need have smart algorithms, which can automatically adapt new conditions, detect threats recognize type possible attack. Nowadays, are lot different approaches, some them reached relatively sufficient accuracy. However, majorit...

Predicting different behaviors in computer networks is the subject of many data mining researches. Providing a balanced Intrusion Detection System (IDS) that directly addresses the trade-off between the ability to detect new attack types and providing low false detection rate is a fundamental challenge. Many of the proposed methods perform well in one of the two aspects, and concentrate on a su...

The Internet of Things (IoT) has rapidly transformed digital environments across a multitude domains with increased connectivity and pervasive virtualization. distributed computing paradigm Edge Computing been postulated to overcome the concerns response time, bandwidth, energy consumption, cybersecurity. In comparison other concerns, limited studies have focused on cybersecurity, mainly due in...

This paper aims to propose the semi-supervised learning system that deals with huge and dynamic data in time and memory efficient manner. In today’s world the numbers of applications are available in information system which deals with large amount of data in changing environment. In such environments, this data is available in the form online streams. The memory and time limitations are the ma...

This research present a proposal Hybrid Multilevel Network Intrusion Detection System (HMNIDS) which is a "hybrid multilevel IDS", is hybrid because use misuse and anomaly techniques in intrusion detection, and is multilevel since it apply the two detection techniques hierarchal in two levels. First level applies anomaly ID technique using Support Vector Machine (SVM) for detecting the traffics...