Bhupendra Verma

A Behavioral Study of Wormhole Attack in Routing for MANET

Wireless mobile ad-hoc networks are those networks which has no physical links between the nodes. There is no fixed topology in this network due to the random mobility of nodes, interference, multipath propagation and path loss. Many Routing protocols have been proposed and developed for accomplishing this task. The intent of this paper is to analyze three ad-hoc routing protocols AODV, DYMO, FISHEYE against wormhole attack in wireless network. This paper concentrates evaluating the performance of routing protocols when wormhole attacks involve in wireless network. The performance analysis for above protocol is based on variation in speed of nodes in a network with 50 nodes. All simulation is carried out with QualNet 5.0 simulator.

A Novel Approach for Intrusion Detection System Using Artificial Immune System

Intrusion detection, a topic that has evolved heavily due to the rising concern for information technology security, has endured numerous architecture abstractions. All of these architecture abstractions have strengths and weaknesses with regard to various factors like efficiency, security, integrity, durability, and cost-effectiveness, to name a few. In this chapter, we explore the appropriateness of the artificial immune system negative selection for intrusion detection and anomaly detection problems. Negative selection is appropriate for anomaly detection problems, especially when compared to statistical K-mean clustering methods, and can detect unseen or unknown attack.

Software Assessment Parameter Optimization using Genetic Algorithm

Software assessment of a project is a key aspect for the prediction of the cost, duration and the expertise required for the project. An efficient optimization algorithm is urgently needed. In this paper, we analyze the genetic algorithm (GA) technique for the development of a software assessment model for the NASA software project dataset. The simulation is performed using MATLAB environment and the results are tested on the basis of measures such as MMRE, MdMRE, MMER, Prediction Accuracy (25%) and the estimation time. The results of the developed Genetic Algorithm (GA) based model was also compared to known models in the literature. The assessment provided by the developed GA model was good compared to other models. General Terms Parameter Optimization, Software Assessment.

A New Approach for Vertical Handoff in Wireless 4G Network

Future generation 4G wireless network is designed for flawless and continues connections between devices of several independent wireless networks like WLAN, GPRS and so on. Heterogeneous wireless networks will be dominant in the next-generation wireless networks with the integration of various wireless access networks. One of the most challenging problems for coordination is vertical handoff, which is the decision for a mobile node to handoff between different types of networks in heterogeneous network. Handoff is based on received signal strength comparisons; in this paper we develop a Vertical Handoff strategy for 4G network based on bandwidth and Power (Signal Strength) between different networks .we compare the results with handoff mechanism depending upon only signal strength. Results show a significant performance improvement of the proposed system over the signal strength driven handoff or connectivity driven handoff.

Biologically Inspired Computer Security System: The Way Ahead

Last two decades have witnessed tremendous growth of internet and it acts as a centrifugal force for a whole new array of applications and services which drives the e- business/ commerce globally. Millions of application has been designed to reach out to the end-user to provide necessary information. The users who are participating in various activities over internet are exposed to public network which is vulnerable to the ever growing threats like never before due to the fascination and value of information/ transaction involved. So concern about security of computer systems is justifiable, and to overcome/ prevent these threats has resulted in the development of various security concepts and products such as Firewalls, Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS). Lately it has been witnessed that there lies a huge potential in biological algorithms and methods to solve complex real world problems, we just need to relate and model the solution based on these biological theories. This paper critically reviews the information that is available on the internet as one has to spend a considerable amount of time to search it, also it explores the possibilities of development of a biologically inspired computer security system to overcome the ever growing complex security challenges.

Secure and Intelligent Decision Making in Semantic Web Mining

With the huge amount of information available online the World Wide Web is a fertile area for data mining research. The Web has become a major vehicle in performing research and education related activities for researches and students. Web mining is the use of data mining technologies to automatically interact and discover information from web documents, which can be in structured, unstructured or semistructured form. We present an enterprise framework regarding semantic web mining in distance learning, which can be used to not only improve the quality of web mining results but also enhances the functions and services and the interoperability of long distance educational information systems and standards in the educational field. For on line distance education system we propose an Ontology-based approach to share online data and retrieve all relevant data about students and their courses. Thus semantic web ontology help build better web mining analysis in educational institute and web mining in-turns helps contract basis more powerful ontology in distance learning. Since the majority of the online data considered as private data we need various mechanism for privacy preservation and control over the online presence data. We propose privacy protection in semantic web mining using role back access control.

A New Approach to Overcome Problem of Congestion in Wireless Networks

During past few years the wireless network has grown in leaps and bounds as it offered the end users more flexibility which enabled a huge array of services. All these services are achieved due to the network which is the backbone. The concept of the wireless network and the wireless devices also brings a lot of challenges such as energy consumption, dynamic configuration and congestion. Congestion in a network occurs when the demand on the network resources is greater than the available resources and due to increasing mismatch in link speeds caused by intermixing of heterogeneous network technologies. It is not limited to a particular point in the network but it can occur at various points in the network and it results into high dropping and queuing delay for packets, low throughput and unmaintained average queue length. It is factor that affects a network in a negative manner. Queue management provides a mechanism for protecting individual flows from congestion. One of the technique which uses Active Queue Management technique is RED. The basic idea behind RED queue management is to detect incipient congestion early and to convey congestion notification to the end-hosts, allowing them to reduce their transmission rates before queues in the network overflow and packets are dropped. Carnegie Mellon University proposed a new queue based technique for wireless network called CMUQ. The basic philosophy behind CMU queue is to prevent congestion. This paper introduces a new range variable and priority queue for existing CMU queue and for RED algorithm.

An Immunity Inspired Anomaly Detection System: A General Framework

Exponential growth of internet acted as a centrifugal force in the development of a whole new array of applications and services which drives the e-business/ commerce globally. Now days businesses and the vital services are increasingly dependent on computer networks and the Internet which is vulnerable to the evolving and ever growing threats, due to this the users who are participating in various activities over internet are exposed to many security gaps which can be explored to take advantage. These alarming situations gave rise to the concern about security of computer systems/ networks which resulted in the development of various security concepts and products but unfortunately all these systems somehow fail to provide the desired level of security against ever-increasing threats. Later on it has been observed that there lies a huge analogy between the human immune system (HIS) and computer security systems as the previous protects the body from various external and internal threats very effectively. This paper proposes a general immunity inspired security framework which uses the concepts of HIS in order to overcome the ever growing complex security challenges.

A Novel Approach to Classify High Dimensional Datasets Using Supervised Manifold Learning

Classifying high-dimensional datasets is a very challenging task. In high dimensional spaces, the performance of supervised learning methods suffer due to the huge difference between number of columns and number of rows, which degrades both accuracy and efficiency performance of classification. In this paper we propose a two phase approach to the given datasets to address the present scenario. Dimension Reduction Method Supervised Locally Linear Embedding (SLLE) is applied in the first phase to reduce dimension of the datasets and in next phase classification through K-NN and SVM is done. Experiments are carried on different high dimensional datasets and then we compared of different dimension reduction and classification methods.

Redefining and Extending the Scope of System Development Life Cycle: Perspective of Today's and Futuristic Human-System Interaction Environment

With the latest innovations in the field of digital computing, communication and interconnecting technology, a new and of its own type of pervasive physical-digital ecosystem has started to emerge and in future it will be more ubiquitous, more dominant, more potent, more useful, more helpful, more usable. Finally, it will emerge as inevitable and indispensable part of our mundane interaction environment and everyday lifestyle experience. The designers, developers and practitioners of human-system interaction design have got a vital role to play in this transformation. The system development life cycle is the fundamental iterative reference cycle that specifies how to design and develop such technological systems. This work first focuses on those aspects which are of most significance from point of view of human-human concerns mediated by human-system interaction and are not appropriately addressed by canonical interaction-system development life cycle. This work then extends it along with specifying the realizing methodologies, in order to broaden the scope of the canonical system development life cycle to fulfil the present and future requisites in relation to people’s interaction with the totality of ubiquitous environment in all respects.