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Articles by P. Vivekanandan
Total Records ( 6 ) for P. Vivekanandan
  P. Malathi and P. Vivekanandan
  Phishing webpage that mimic the webpage of legitimate, to steal information from users which become the fashionable practice and sophistical growing among the perpetrators of the Web. This phishing scams become a gigantic problem from e-Bankers and e-Commerce users. It is dynamic and very complex problem to classify phishing webpage because of alike absolute character of legitimate webpage. This study presents an approach to overcome the complicatedness for foretelling or classifying e-Banking phishing webpage. The classification of phishing webpage leads to the subjective consideration of various factors, the Neuro-Fuzzy Classification (NEFCLASS) Back Propagation algorithm can be an effectual analysis of classification model. The NEFCLASS Back Propagation algorithm analyzes the webpage in natural way in human intellectual manner. The various multi modal features are considered in this study for effectual classification with three phishing stratums. Thirty features are extracted are grouped in six different property that under three stratums, respectively.
  P. Malathi and P. Vivekanandan
  The growing internet access rate makes the malicious users to spread malware, spyware, viruses into the genuine users storage medium and steal many user specific personal information. Also, the malware spoils the working of user devices and reduces the performance and usage of the user computers. The user information steals by the malware are used to perform various malformed activities by them. Sometimes, the malware which intrudes into the user devices transfer many information about the customer information which can be used to perform various network threats. To solve this issues, there are many antivirus programs and tools are designed which monitor the activities and presence of viruses in the user devices. Apart from this, there are few scripts which are running at the time of user visit which transfers much user personal information without knowing the users. This kind of programs or scripts will not be monitored by any virus programs or security tools. By considering these client side scripts, a stream estimation based end point elimination technique is proposed and it identifies a set of endpoints or connections established at any point of time and eliminates un_trusted connections to secure the internet access. The proposed approach has produced efficient results in client script restriction and has reduced the time complexity also.
  P. R. Therasa and P. Vivekanandan
  The quality of the software is the very important factor in the field of software development which can be determined by many quality attributes of the software. Thus, the quantification of the quality parameters and incorporating them into the quality models are essential for software maintainability. The ISO/IEC 25010:2011 standard is developed to integrate the quality model based on software attributes. In this study, a fuzzy based model is proposed to predict the software maintainability from UML class diagram. The outcomes are presented and the knowledge modeling using fuzzy logic is discussed. The development of this model is based on the factors that affect the maintainability like other software quality factors. This hierarchy consists of factors, attributes and metrics which are used for measuring the maintainability of object-oriented software. This proposed model captures the factors that determine maintainability at design level and expressed by coupling and size attributes. Some of the metrics which quantify these attributes (NA, NM, NAssoc, NAgg etc.) are then considered as the input parameters to the proposed model. The process is applied to a case study where the Mamdani fuzzy inference engine is used to predict software maintainability. The performance of the model was evaluated using RMSE. In order to estimate the software maintainability, the analysis of different membership functions defined in fuzzy inference system by MATLAB for the mentioned metrics are presented.
  E. Sivajothi and P. Vivekanandan
  Wireless sensor network is the collection of sensors grouped together to perform a specific task. The sensors are placed either in a regular pattern or in a random manner. In contrast to regular deployment, random deployment may lead to the existence of redundant sensors, used to monitor the same field of interest. The redundant sensors may degrade the network performance in many aspects such as energy consumption, coverage, connectivity, etc. In this study the tradeoff between the number of active sensors, coverage, energy and connectivity is discussed in detail. Parameters such as connectivity, number of neighbors and distance towards the sink and coverage overlap are put into fuzzy logic system. The output measure, namely, Node Selection Probability (NSP) from the fuzzy inference system decides whether or not the sensor nodes should be redeployed and need to be alive or inactive. Simulation results show that the algorithm effectively extends the network life time and has achieved high throughput, residual energy and coverage with reduced number of sensors. The number of sensors are reduced by eliminating the redundant sensors which will produce the maximum redundant effect.
  S. Behin Sam , S. Sujatha , A. Kannan and P. Vivekanandan
  Distributed Denial of Service (DDOS) attacks have emerged as a prevalent way to shut an organization off from the internet and has resulted in financial losses to the same. In the case of DDOS attack, an adversary attempts to disconnect network elements by disabling the communication links or nodes. The effectiveness of DDOS defenses depends on factors such as the specific attack scenario and various characteristics of the network routers. However, little research has focused on the nature of the network`s topology that can also be an effective DDOS defense. This study focuses on the adversaries who try to disable the communication links. It stresses the need for either a strong connectivity or m-connectivity among the nodes (routers). This approach will discourage the adversary from attempting to disable the network, as the cost for causing the damage will increase. Validation of this approach was performed using a network simulator and the results are shown.
  K. Gobianand , P. Vivekanandan , K. Pradeep , C.V.R. Mohan and S. Karthikeyan
  The study was aimed to investigate the anti-inflammatory and anti-pyretic activities of ethanolic extract of Cassia fistula Linn. (ELE) in experimental rats. Anti-inflammatory activity was evaluated using carrageenan induced rat paw oedema and cotton pellet granuloma models, while the antipyretic effect was evaluated using against TAB vaccine induced pyrexia. Various doses of ELE (50, 100, 250, 500 and 750 mg kg-1b.wt.,) were tested for its anti-inflammatory effect and the results were compared with standard drugs (diclofenac and indomethacin). Results indicate that the ELE significantly inhibited both the carrageenan-induced hind paw oedema and cotton-pellet granuloma in a dose dependant manner. ELE at 250 and 500 mg kg-1b.wt., reduced TAB vaccine induced pyrexia in rats after 60 min, whereas at 750 mg kg-1b.wt., it reduced the vaccine induced elevated body temperature post 30 min of its administration. The results suggest that there exists a potential benefit in utilizing Cassia fistula Linn. in treating conditions associated with inflammation and fever. These properties can be attributed to the presence of phyto constituents present in ELE and the exact mechanism needs to be elucidated.
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