Cyber attacks are becoming increasingly complex, especially when the target is a modern IT infrastructure, characterized by a layered architecture that integrates several security technologies such as firewalls and intrusion detection systems. These contexts can be violated by a multistep attack, that is a complex attack strategy that comprises multiple correlated intrusion activities. While a ...

Intrusion detection is one of the challenging tasks in today’s networked world. It is necessary to formulate a new intrusion detection system, which can monitor the network to detect the malicious activities. The proposed work focuses the issues, namely accuracy and efficiency. One way to improve performance is to use a minimal number of features to define a model in a way that it can be used t...

Recently data mining methods have gained importance in addressing network security issues, including network intrusion detection-a challenging task in network security. Intrusion detection systems aim to identify attacks with a high detection rate and a low false alarm rate. Intrusion Detection System (IDS) and Intrusion Prevention Systems (IPS) in computer network security are real-time softwa...

With the expansion of computer networks, security has become a important issue for computer systems. The threat from attackers and criminal enterprises has grown with the expansion of Internet, therefore, intrusion detection systems have become a core component of computer network due to such threats. In this paper, we present framework integrated with neural network to build an effective intru...

The Internet of Things (IoT) is widely used in advanced logistic systems. Safety and security of such systems are utmost important to guarantee the quality of their services. However, such systems are vulnerable to cyber-attacks. Development of lightweight anomaly based intrusion detection systems (IDS) is one of the key measures to tackle this problem. In this paper, we present a new distribut...

Wireless Sensor Network (WSN) consists of low cost sensor nodes which cannot afford to implement sophisticated security system in it. That is why intrusion detection architecture for WSN is considerably different and difficult to implement. Most of the current implementations are based on exchanging anomaly signals among the leaf level sensors resulting in too much power consumption. We propose...

Neural gas network is a single-layered soft competitive neural network, which can be applied to clustering analysis with fast convergent speed comparing to Self-organizing Map (SOM), K-means etc. Combining neural gas with principal component analysis, this paper proposes a new clustering method, namely principal components analysis neural gas (PCA-NG), and the online learning algorithm is also ...

Intrusion detection in Wireless Sensor Network (WSN) is of practical interest in many applications such as detecting an intruder in a battlefield. The intrusion detection is defined as a mechanism for a WSN to detect the existence of inappropriate, incorrect, or anomalous moving attackers an intrusion detection system is a layered framework mechanism designed to support homogeneous network envi...

As ad-hoc networks have different characteristics from a wired network, the intrusion detection techniques used for wired networks are no longer sufficient and effective when adapted directly to a wireless ad-hoc network. In this article, first τhe security challenges in intrusion detection for ad-hoc networks are identified and the related work for anomaly detection is discussed. We then propo...