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Articles by P. Malathi
Total Records ( 4 ) for P. Malathi
  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.
  D. Binu and P. Malathi
  Biometric-based systems are used for human recognition in real-time applications. Due to the huge size of biometric database in current methodologies, more time is required for image search in the database. In this study, an innovative technique is introduced called Two-Modal Biometrics based Content-Based Image Retrieval approach (TMB-CBIR) for biometric authentication. In the two-modal biometrics, iris and fingerprint images are considered. In the iris image, both color and texture features are extracted where color feature is used for indexing and text feature is used to find the similarity of images extracted by using Speeded Up Robust Features (SURF) algorithm. In the fingerprint images, the Improved Locality-Sensitive Hashing (ILSH) indexing method is used that considers the locality of points so that the nearby points remain closer instead of recognize perfect match. In this method, the data is disseminated and every data point is uniformly hashed. Union of Candidate Lists fusion method is used to merge both lists of candidate identities output. Finally, the set of reference images are chosen from convex hull of feature space in order to reduce the estimation time. Experimental results show that TMB-CBIR achieves high accuracy and less response time.
  P. Madhavan and P. Malathi
  The tremendous usage of mobile nodes in wireless communication medium makes energy efficiency a fundamental requirement of Mobile Adhoc Network. Energy plays a vital role in prolonging the network life time. DFA based QOS Aware Clustering (DFA-QAC) for the Energy-aware Optimized Link State Routing protocol (E-OLSR) is used. This algorithm takes into account the mobility, residual energy of the nodes and gives major improvements regarding the number of elected cluster heads. The objective is to elect a reasonable number of cluster heads which regulates the network traffic and preserving bandwidth. The proposed scheme DFA-QAC uses modified weighted clustering technique which helps to decide the mode of each node. It can able to select the nodes having highest residual energy as a cluster head and able to switch between states. DFA based representation helps to determine the pattern of switching between various states and can able to predict average energy required for cluster formation. Reclustering mechanism helps in electing the new cluster head, when a node has entered or it has just left its cluster. The results of the proposed scheme E-OLSR perform better than the traditional AODV protocol. The performance metrics such as energy consumption. Packet delivery ratio and throughput has been analyzed in the proposed scheme.
  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.
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