G. M. Kadhar Nawaz

Secured communication for MANETS in military

A new way to increase the security of data transmission of mobile ad hoc networks [MANETS] is presented in this work. There is a massive increase in using MANETS for unmanned army system for both surveillance and future combat operations. This has necessitated the development of innovative MANET solutions catering to the reliability, security and scalability needs of the defense communications environment [15]. Security and reliability are crucial aspects of MANET, especially in security sensitive applications like military. Secure Message Transmission SMT[1] protocol secure the data transmission phase by tailoring an end-to-end secure data forwarding protocol to the MANET communication requirements and increases the reliability through transmitting the messages in multiple paths with minimal redundancy. This work increases the through the removal of Byzantine Faults [8] in the multiple paths. A binary search probing technique which is resilient to Byzantine failures caused by individual or colluding nodes is incorporated in the SMT protocol to provide more secured transmission. The fault detection algorithm bounds logarithmically (log n -n the number of nodes in the path), so the delay is reduced drastically. The simulated implementation of the work in NS2 shows the marginal increase in the throughput. The delay and jitter variants can also be improved if the nodes location can be predicted. Predicting the nodes location and reducing the unnecessary traffic with the aid of Spatial and Temporal mining is the second phase of this work.

Performance analysis of network traffic behavior in conventional network over MPLS

Multiprotocol Label Switching (MPLS) is an Internet Engineering Task Force (IETF) specified framework that provides for the efficient designation, routing, forwarding and switching of traffic flows through the network. MPLS is a versatile solution to address the problems faced by present-day networks like speed, scalability, quality-of-service (QoS) management, and traffic engineering. MPLS carries differentiated services across the Internet through a virtual path capability between packet (label) switches. MPLS also has the capabilities to engineer traffic tunnels by avoiding congestion and utilizing all available bandwidth with an efficient manner. MPLS signaling protocols are Constrained based Label Distribution Protocol (CR-LDP), Resource Reservation Protocol (RSVP) and Traffic Extension RSVP (RSVP-TE). In this paper, a full comprehensive simulation environment is created for a conventional network and MPLS applied over that traditional network to evaluate the comparative performance of network traffic behavior. Finally, the results are evaluated and analyzed, and their behaviors are shown by means of graphical manner.

Reliable communication for MANETS in military through identification and removal of byzantine faults

A MANETS (Mobile Ad Hoc Networks) is a spontaneous network that can be established without any infrastructure. Problems are faced while setting up and using a MANET which is both reliable and secure. Transmitting message over multiple paths will increase the security and reliability of transmission in an open collaborative MANET environment where any node can maliciously or selfishly disrupt and deny communication of other nodes. An SMT protocol [1] provides a way to secure message transmission by dispersing the message among several paths with minimal redundancy. The multiple routes selected are known as APS — Active Path Set. An improved way of secured and reliable communication in military using MANETS is presented in this work. This work is towards improving the security of the message transmission among multiple routes by including the most reliable routes in the active path sets through the identification and removal of Byzantine Faults. The route discovery process with binary search probing technique is resilient to Byzantine failures caused by individual or colluding nodes. Malicious links are detected and these links are then avoided by multiplicatively increasing their weights. The fault detection algorithm bounds logarithmically (log n — n the number of nodes in the path), so the delay is reduced drastically. The simulated implementation of the work clearly shows 16 percent increase in average throughput.

Outliers detection on protein localization sites by partitional clustering methods

A large molecule composed of one or more chains of amino acids in a specific order, the order is determined by the base sequence of nucleotides in the gene that codes for the protein. Proteins are required for the structure, function, and regulation of the bodys cells, tissues, and organs and each protein has unique functions. Localization sites of proteins are identified by the mechanism and moved to its corresponding organelles. In this paper, we introduce the method clustering and its types K-Means and K-Medoids. The clustering algorithms are improved by implementing the two initial centroid selection methods instead of selecting centroid randomly. K-Means algorithm can be improved by implementing the initial cluster centroids are selected by the two proposed algorithms instead of selecting centroids randomly, which is compared by using Davie Bouldin index measure, hence the proposed algorithm1 overcomes the drawbacks of selecting initial cluster centers then other methods. In the yeast dataset, the defective proteins (objects) are considered as outliers, which are identified by the clustering methods with ADOC (Average Distance between Object and Centroid) function. The outliers detection method and performance analysis method are studied and compared, the experimental results shows that the K-Medoids method performs well when compare with the K-Means clustering.

Performance enhanced mobile agent for e-commerce based applications

To reduce the network traffic in the internet, mobile agent technology is used in vast number of network based applications. However, there are some security issues. Many of the existing models are used to provide the security for the mobile agent. In most of the existing models, cloning the mobile agent is high which increases time and also occupies more space. To reduce the mobile agent cloning, this research proposes a new model to enhance the security of the data. In this model the mobile agent travel around the network, collects the required data from one host, encrypt it and send it to the owner immediately. After sending the data then the mobile agent migrate into the next host. This model enhances the security of the data and also retain the size of the mobile agent same.

A Radical Block to Byzantine Attacks in Mobile Ad Hoc Networks

Mobile Ad Hoc networks is a wide area of mobile computing and has many narrowed domains such as sensor networks, VANETs, pervasive and ubiquitous computing. These set of varying networks are used in applications ranging from crucial to commercial and social usage. Few of the applications of MANETs are in medical field, military field, disaster recovery, wild life study, predicting natural calamities, and health care, transportation systems and most of the applications are security sensitive applications. In spite of tremendous research carried out in the security domain of networks, still it exists as an ever green field for new findings. MANETS are vulnerable to attackers and Byzantine attacks are the most harmful and hazardous one among the active attacks. This work presents a triple layered protection and detection mechanism and a complete blockage to this kind of insider attacks. The affected system can be recovered quickly even if the attackers partition the network into many components. Prediction is done well in advance before the attackers succeed in their intention and remedial actions are taken to retain the systems performance and reliability. The node’s behavior from the point of entrance into system is measured at each layer and aggregate performance in the form of weighted Laplacian matrix or Kirchhoff matrix is transferred between the layers as a cross layer feedback. The reliable detection and recovery scheme based on cryptosystems and message dispersion also use this feedback in blocking the Byzantine attacks. The implemented system gives highly accurate analysis of feedback of the system behavior.

Fuzzy-ant based dynamic routing on large road networks

Route selection is essential in everyday life. We have several algorithms for detecting efficient route on Large Road Networks. This paper introduce the hierarchical community, is presented. It splits large road networks into hierarchical structure. It introduces a multi parameter route selection system which employs Fuzzy Logic (FL) and ants behavior in nature is applied for the dynamic routing. The important rates of parameters such as path length and traffic are adjustable by the user. The purposes of new hierarchical routing algorithm significantly reduce the search space. We develop a community-based hierarchical graph model that supports Dynamic efficient route computation on large road networks.

Detecting outliers on UCI repository datasets by Adaptive Rough Fuzzy clustering method

The clustering is the most effective method to identify the outliers in the UCI Repository dataset. This paper proposes detecting outliers on UCI datasets using Adaptive Rough Fuzzy C-Means clustering algorithm. In the first phase of the Adaptive Rough Fuzzy C- Means algorithm, the Rough k means algorithm is used for pre-processing of UCI repository dataset and it is normally identify the outliers and removed from the dataset. After removed outliers in the dataset, the remaining data objects are clustered by Rough K-Means, Fuzzy C-Means and Adaptive fuzzy c means methods. The experimental result of the clustering algorithms and outlier detection methods are compared and also analysed using validity indexes (Davies Bouldin index, Rand index and Adjusted Rand index), performance analysis, cluster compactness and scalability methods. Further, the experimental readings show that the Adaptive Rough Fuzzy C-Means clustering algorithm outperformed the Rough K-Means and fuzzy C-Means clustering method.

Maximum performance with minimum cost in data mining applications through the novel online data warehouse architecture by using storage area network with fibre channel fabric

The primary issues of data warehouse architecture are higher cost, and poor performance. The reasons for these problems focus the architectural design. The solutions are proposed with the new modified data warehouse design through online data warehouse architecture with the recent technological support from cloud computing - storage area networks through the use of high speed fibre channel based storage devices with fibre channel switches. Finally the benefits and advantages of proposed design were discussed with the cost and performance.