Network Intrusion Detection Systems must effectively identify security threats and protect the applications. The focus of the paper is the presence of class imbalance problem in intrusion datasets. An efficient intrusion detection system must accurately identify all threats even if they form a small fraction of the intrusion data. The effect of class imbalance on the benchmark NSL_KDD dataset is evaluated using four popular classification techniques and the results are analyzed.

Class imbalance problem in the Network Intrusion Detection Systems

/pdf/an-overview-of-intrusion-detection-system-5g3mwwashy.pdf

An Overview of Intrusion Detection System

MANET is mobile ad hoc network where mobile means moving, ad hoc means impromptu. Thus, MANET is a kind of transient networks in which nodes are able to move without any fixed infrastructure or centralized administration. A MANET can be used in special situation where the structure of installation is very complex like disaster area, battle field, etc. The battery power of nodes decides the life span of wireless ad hoc network. The recharge or battery change option seems to be infeasible in most of the applications. Therefore, data packet needs to be sent from one node to the other using minimal energy utilization. But, malicious nodes in case of vampire attacks spend more energy than that of normal and thus leading to power drooping of node and breakdown of the network. Vampire attack is the resource depletion attack and thus resulting in early drainage of the battery. The main concept is about honest and dishonest nodes. If there is a dishonest node present in the middle of honest nodes, then it will consume more energy than the normal in order to transmit the data packets to the neighboring node. In this paper, we have presented a new detection and prevention algorithm for vampire attack for MANET based on the concept of hash value and timestamp.

Detection and Prevention of Vampire Attack for MANET

iii OZ iv DEDICATION v ACKNOWLEDGMENT vi LIST OF TABLES ix LIST OF FIGURES x LIST OF ABBREVIATIONS xi

http://i-rep.emu.edu.tr:8080/jspui/bitstream/11129/1671/1/HusseinNaseer.pdf

Design of a Network-Based Anomaly Detection System Using VFDT Algorithm

Mobile and Pervasive Computing was introduced by the technological vision of Mark Weiser. With the ideology of Urban Development, it is considered that the world will be composed of interconnected devices and system models of networks, which allows the accessibility of information present across the globe. A U-City characterized by the information and computing technologies is gradually becoming indistinguishable and unviable from daily life. In that regard, this article provides an in-depth evaluation of Mobile and Pervasive Computing considered as an evolutionary framework applicable in electric motors, which are invisible hence forming a pervasive environment. Mobile technology will play an essential role in urban development. This signifies that the mobility initiatives are applicable for many telecommunication aspects used in our daily lives. The article starts by illustrating the significant mobile technologies in the urban areas, thereby elaborating on the planning format of pervasive computing, which is meant for urban development. To effective plan for the establishment or expansion of urban centers, the article calls for planners to concentrate on the formation of pervasive computing areas that define the correlations between people, places, objects, buildings and infrastructure. Mobile Crowd Sourcing Technologies for smart environments calls for planners to concentrate on revolutionizing the globe by aligning technological functions and enhance the integration and coordination of various services involved in technological intelligence.

Implementation of IDS Within a Crew Using ID3Algorithm in Wireless Sensor Local Area Network

5 Abstract: With the tremendous growth of the usage of computers over network and development in application running on various platform captures the attention toward network security(1). Intrusion detection system has become an important component of a network infrastructure protection mechanism. The Intrusion Detection System (IDS) plays a vital role in detecting anomalies and attacks in the network (5). In this work, data mining concept is integrated with an IDS to identify the relevant, hidden data of interest for the user effectively and with less execution time. In proposed system, we first preprocess dataset (KDD 99 cup). Then we study different types of decision tree algorithms (C4.5 and its extension) of data mining for the task of detecting intrusions and compare their relative performances. Based on this study, it can be concluded that even extended C4.5 is complex but decision tree obtained is the most suitable with high true positive (correct detection of attacks) and low false positive (Incorrect detection) with high accuracy.

/pdf/intrusion-detection-system-using-data-mining-2o9sp7zi3o.pdf

Janhavi Deo

Papers

Intrusion Detection System using Data Mining