Praneet Saurabh

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.

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.

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.

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.

A Novel Immunity Inspired Approach for Anomaly Detection

Immune System (AIS) over the years has caught attention of researchers of various domains for complex problem solving. AIS model the procedure and methodologies of Biological Immune System (BIS) which protects the body from diverse attacks and different challenges. Scientists over the years are amazed with the appealing features of BIS that can be exploited. The most significant of them is its ability to distinguish self and non-self. This theory forms the basis of Negative Selection Algorithm (NSA) in AIS. NSA is competent for anomaly detection problems. From this perspective this research paper presents a Novel Immunity inspired approach for Anomaly Detection (NIIAD) with the feature of fine tuning. The main intention of adopting finetuning is to covering more self region and identifying non self region proficiently. Experimental results reflects high detection ratio with less false alarm and low overhead.

A Novel Approach to Predict Cancer by Ensembling of Kernel Based Dimension Reduction and Classifier Using DNA Microarrays

DNA Micro arrays allow the parallel monitoring of thousands of expression levels of genes simultaneously. The secret behind of this technology is the fact that DNA nucleotide bases will hybridize to certain other nucleotide bases. With the help of DNA Micro arrays we can predict Human cancer considering the genes expression levels across a collection of sample. In this paper we introduce ensemble approach to classification method which included Dimension Reduction. For Dimension Reduction we use Supervised Locally Linear Embedding and for Classification uses Support Vector Machine.

A New Neural Network-Based IDS for Cloud Computing

Services provided by cloud computing are the very fascinating as it offers of free access or paid access to the buyers. This paradigm facilitates a verity of facets to the users. Being such an interesting concept and having so many beneficial features, the cloud also suffers from several security risks. This results in creating a lot of challenges at the time of implementation. Since, cloud services are not confined to limited boundaries therefore chances of misadventure leading to compromise is immense. Intrusion detection system (IDS) within the cloud environment is an interesting idea and this paper presents “A neural network-based intrusion detection system for cloud computing (NN-IDS)”. It discusses the various integrated methods that provide detection in cloud environment and also takes prevention measures for the malignant functions found within the cloud. Experimental results show that NN-IDS performs much better than existing work and shows significant improvement in accuracy and precision.

Weight-Based Secure Approach for Identifying Selfishness Behavior of Node in MANET

Mobile adhoc networks (MANET) is an interesting concept, as all mobile nodes work like router. They can receive and transmit data packet any time in hostile environment even when the source and the destination mobile nodes are not directly connected to each other. In this circumstance, data packets are forwarded to the destination mobile node by relaying the transmission through intermediary mobile nodes. Due to selfish behavior, packets are intentionally dropped by intermediate nodes, also intermediate nodes continuously forward or broadcast control packets in network that consumes energy of node and lowers performance. This makes discovery of secure routing path and detection of selfish nodes and their activities as important challenges in MANET. This paper proposes a weight-based secure approach for identifying selfish behavior in MANET (WSISB). The proposed WSISB identifies the above-discussed activities and it will also discover a trusted path for secure data transmission. Experimental results show that WSISB performs much better than existing techniques and show significant improvement in terms of performance.