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Keyword: Intrusion detection systemAn Analysis of K-means Algorithm Based Network Intrusion Detection System
In this modern age, information technology (IT) plays a role in a number of different fields. And therefore, the role of security is very important to control and assist the flow of activities over the network. Intrusion detection (ID) is a kind of security management system for computers and networks. There are many approaches and…
Read MoreBuilding an Efficient Alert Management Model for Intrusion Detection Systems
This paper is an extension of work originally presented in WITS-2017 CONF. We extend our previous works by improving the Risk calculation formula, and risk assessment of an alert cluster instead of every single alert. Also, we presented the initial results of the implementation of our model based on risk assessment and alerts prioritization. The…
Read MoreNetwork Intrusion Detection System using Apache Storm
Network security implements various strategies for the identification and prevention of security breaches. Network intrusion detection is a critical component of network management for security, quality of service and other purposes. These systems allow early detection of network intrusion and malicious activities; so that the Network Security infrastructure can react to mitigate these threats. Various…
Read MoreDetection Method and Mitigation of Server-Spoofing Attacks on SOME/IP at the Service Discovery Phase
Service-oriented architecture has attracted attention in automotive development. The Automotive Open System Architecture (AUTOSAR) specifies Scalable Service-Oriented Middleware over IP (SOME/IP) as a key middleware for service-oriented communication in-vehicles. However, SOME/IP-based networks are vulnerable to server spoofing during the service discovery phase, enabling attackers to cause man-in-the-middle attacks by impersonating legitimate services. This paper proposes…
Read MoreHybrid Intrusion Detection Using the AEN Graph Model
The Activity and Event Network (AEN) is a new dynamic knowledge graph that models different network entities and the relationships between them. The graph is generated by processing various network security logs, such as network packets, system logs, and intrusion detection alerts, which allows the graph to capture security-relevant activity and events in the network.…
Read MoreiDRP Framework: An Intelligent Malware Exploration Framework for Big Data and Internet of Things (IoT) Ecosystem
The Internet of Things (IoT) is at a face paced growth in the advanced Industrial Revolution (IR) 4.0 in the modern digital world. Considering the current network security challenges and sophistication of attacks in the heavily computerized and interconnected systems, such as an IoT ecosystem, the need for an innovative, robust, intelligent and adaptive malware…
Read MoreMachine Learning for Network Intrusion Detection Based on SVM Binary Classification Model
Recently, the number of connected machines around the worldwide has become very large, generating a huge amount of data either to be stored or to be communicated. Data protection is a concern for all institutions, it is difficult to manage the masses of data that are susceptible to multiple threats. In this work, we present…
Read MoreNonlinear \(\ell_{2,p}\)-norm based PCA for Anomaly Network Detection
Intrusion detection systems are well known for their ability to detect internal and external intrusions, it usually recognizes intrusions through learning the normal behaviour of users or the normal traffic of activities in the network. So, if any suspicious activity or behaviour is detected, it informs the users of the network. Nonetheless, intrusion detection system…
Read MoreRisk Management: The Case of Intrusion Detection using Data Mining Techniques
Every institution nowadays relies on their online system and framework to do businesses. Such procedures need more attention due to the massive amount of attacks that occurs. These procedures have to go first through the management team of the institution, in order to prevent exploits of the attackers. Thus, the risk management can easily control…
Read MoreA Hybrid Approach for Intrusion Detection using Integrated K-Means based ANN with PSO Optimization
Many advances in computer systems and IT infrastructures increases the risks associated with the use of these technologies. Specifically, intrusion into computer systems by unauthorized users is a growing problem and it is very challenging to detect. Intrusion detection technologies are therefore becoming extremely important to improve the overall security of computer systems. In the…
Read MoreImproved Nonlinear Fuzzy Robust PCA for Anomaly-based Intrusion Detection
Among the most popular tools in security field is the anomaly based Intrusion Detection System (IDS), it detects intrusions by learning to classify the normal activities of the network. Thus if any abnormal activity or behaviour is recognized it raises an alarm to inform the users of a given network. Nevertheless, IDS is generally susceptible…
Read MoreIntrusion Detection in Cyber Security: Role of Machine Learning and Data Mining in Cyber Security
In recent years, cyber security has been received interest from several research communities with respect to Intrusion Detection System (IDS). Cyber security is “a fast-growing field demanding a great deal of attention because of remarkable progresses in social networks, cloud and web technologies, online banking, mobile environment, smart grid, etc.” An IDS is a software…
Read MoreIntrusion detection in cloud computing based attack patterns and risk assessment
This paper is an extension of work originally presented in SYSCO CONF.We extend our previous work by presenting the initial results of the implementation of intrusion detection based on risk assessment on cloud computing. The idea focuses on a novel approach for detecting cyber-attacks on the cloud environment by analyzing attacks pattern using risk assessment…
Read MoreAttacks Classification and a Novel IDS for Detecting Jamming Attack in WBAN
Wireless Body Area Network (WBAN) aims to monitor patient’s health remotely, by using mini medical sensors that are attached on the human body to collect important data via the wireless network. However, this type of communication is very vulnerable to various types of attacks, poses serious problems to the individual’s life who wears the nodes.…
Read MoreCross layers security approach via an implementation of data privacy and by authentication mechanism for mobile WSNs
To implement a new secure network with high mobility and low energy consumption, we use smart sensors. These sensors are powered by micro batteries generally non rechargeable. So, to extend their lifetime, it is necessary to implement new energy conservation techniques. Existing works separate the two features (security, energy conservation) and are interested specifically in…
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