Informatics Publishing Limited

N. Premalatha ¹, A. M. Natarajan ²

Affiliations
1 Department of Computer Science and Engineering, Kongu Engineering College, Perundurai, IN
2 Bannari Amman Institute of Technology, Sathyamangalam, IN

Abstract

A medium access control (MAC) protocol decides when competing nodes may access the radio channel, and tries to ensure that no two nodes are interfering with each other’s transmissions. In this paper we propose a QoS model for wireless ad hoc networks. Unlike other models it provides stochastic end to end delay guarantees using a routing protocol called GPSR (Greedy Perimeter Stateless Routing) protocol. After the routing is over the packets transmission is done through CTMAC (Concurrent Transmission MAC) protocol with fragmentation. The packets are transmitted concurrently where concurrent transmission is possible. CTMAC inserts additional control gap between the transmission of control packets (RTS/CTS) and data packets (DATA/ACK), which allows a series of RTS/CTS exchanges to take place between the nodes in the vicinity of the transmitting, or receiving node to schedule possible multiple, concurrent data transmissions. It completely utilizes the channel bandwidth and increase the fairness of each flow without causing congestion. This increases the throughput. The results shows us that the throughput of QoS model, where network flow is identified using GPSR protocol and packets are transmitted through CTMAC protocol with fragmentation, is increased when compared with the throughput of CTMAC protocol alone.

Keywords

Wireless, Congestion Control, MAC Protocol, QOS Enhancement, Fragmentation, CTMAC Protocol, Throughput, GPSR.

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K. Preethi , N. Premalatha , T. Saraswathi , V. Srisivaranjani , H. Jeyamohan

Abstract

Cloud Computing has  been  envisioned  as  the  next  generation  architecture  of  the  IT  enterprise due  to   its   on demand self-service, ubiquitous network access,  location-independent resource pooling , rapid resource elasticity   and  usage-based pricing . The  fundamental  aspect  of  cloud  storage  computing model is  that  data  is  being centralized  or  outsourced  into  the cloud without  the  burden of  local  hardware  and  software management  thereby  new  and  challenging  threat on data arises. Fingerprint  Authentication , a significant  security element  and  popular  biometric  modality  which  is  used  extensively  in  several  applications  for  person authentication,  providing  high uniqueness  and  acceptable performance. In existing  system  the  security  of  fingerprint  data  is not  highly  ensured . In this project a new approach of remote user fingerprint authentication scheme using the concept of Merkle Hash Tree has been proposed. The data owner stores the file in an encrypted form in the cloud server. The cloud user has to register with the owner along with the ischolar_main signature. In the client side, the Fingerprint template is split it into eight shares using image processing technique. The splitted eight shares are given as inputs to merkle hash tree wherein each share has to undergo hashing function and hence ischolar_main signature is generated. The signature is generated and stored in the cloud server. The user has to submit the adjacent and sibling shares of fingerprint template for authentication purpose. The signature is generated in the cloud service provider and thus verified with the stored signature in the cloud. The misuse of sensitive data can be   avoided and this provides an effective and efficient user remote authentication with the cloud.

Keywords

Cloud Computing, Finger Print, Root Signature, Biometric, Authentication.

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S. Sasireka ¹, N. Premalatha ¹

Affiliations
1 Dr. MCET, Pollachi, Coimbatore – 641 035, IN

Abstract

We present an efficient approach, a system used to detect attacks in multitiered web services and classify through Hierarchal clustering Algorithm. Our approach can create normality models of isolated user sessions that include both the web front-end (HTTP) and back-end (File or SQL) network transactions with respect to Data volumes and Classify them. Implements a lightweight virtualization technique to assign each user's web session to a dedicated container, an isolated virtual computing environment. We use the cluster algorithm to accurately associate the web request with the subsequent DB queries. DoubleGuard can build a causal mapping profile by taking both the webserver and DB traffic into account. Internet services and applications have become an inextricable part of daily life, enabling communication and the management of personal information from anywhere. To accommodate this increase in application and data complexity, web services have moved to a multitiered design wherein the webserver runs the application front-end logic and data are outsourced to a database or file server. In this paper, we present DoubleGuard, an IDS system that models the network behavior of user sessions across both the front-end webserver and the back-end database. By monitoring both web and subsequent database requests, we are able to ferret out attacks that an independent IDS would not be able to identify. Furthermore, we quantify the limitations of any multitier IDS in terms of training sessions and functionality coverage. We implemented DoubleGuard using an Apache webserver with MySQL and lightweight virtualization.

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