Intrusion detection system is responsible for monitoring the systems and detect attacks, whether on (host or a network) identifying attacks that could come to cause damage them, that’s mean an IDS prevents unauthorized access by giving alert administrator before causing any serious harm. As reasonable supplement of firewall, intrusion technology can assist deal with offensive, Intrusions Detect...

--Nowadays, computer network systems plays gradually an important role in our society and economy. It became a targets of a wide array of malicious attacks that invariably turn into actual intrusions. This is the reason that computer security has become an essential concern for network administrators. In this paper, an exploration of anomaly detection method has been presented. The proposed sys...

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...

Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomal...

Cloud computing has established a new horizon in the field of Information Technology. Due to the large number of users and extensive utilization, the Cloud computing paradigm attracts intruders who exploit its vulnerabilities. To secure the Cloud environment from such intruders an Intrusion Detection System (IDS) is required. In this paper the authors have proposed an anomaly based IDS which cl...

With the growth of networked computers and associated applications, intrusion detection has become essential to keeping networks secure. A number of intrusion detection methods have been developed for protecting computers and networks using conventional statistical methods as well as data mining methods. Data mining methods for misuse and anomaly-based intrusion detection, usually encompass sup...

Security of computers and the networks that connect them is increasingly becoming of great significance. Intrusion detection system is one of the security defense tools for computer networks. This paper compares two different model Approaches for representing intrusion detection system by using decision tree techniques. These approaches are Phase-model approach and Level-model approach. Each mo...

Feature Selection plays the very important role in Intrusion Detection System. One of the major challenge these days is dealing with large amount of data extracted from the network that needs to be analyzed. Feature Selection helps in selecting the minimum number of features from the number of features that need more computation time, large space, etc. This paper, analyzed different feature sel...

During the last decade, Intrusion Detection Systems (IDSs) have played an important role in defending critical computer systems and networks from cyber-attacks. Anomaly detection techniques have received a particularly great amount of attention because they offer intrinsic ability to detect unknown attacks. In this paper, we propose an enhanced hybrid anomaly detection approach based on negativ...

A Network Intrusion Detection System (NIDS) helps system administrators to detect network security breaches in their organization. However, many challenges arise while developing a flexible and effective NIDS for unforeseen and unpredictable attacks. In this work, we propose a deep learning based approach to implement such an effective and flexible NIDS. We use Self-taught Learning (STL), a dee...