Authentication using Finger Knuckle Print Techniques
In this paper, a new approach is proposed for personal authentication using patterns generated on dorsal of finger. The texture pattern produced by the finger knuckle is highly unique and makes the surface a distinctive biometric identifier. Important part in knuckle matching is variation of number of features which come by in pattern form of texture features. In this thesis, the emphasis has been done on key point and texture features extraction. The key point features are extracted by SIFT features and the texture features are extracted by Gabor and GLCM features. For the SIFT and GLCM features matching process is done by hamming distance and for the Gabor features matching is done by correlation. The database of 40 different subjects has been acquired by touch less imaging by use of digital camera. The authentication system extracts features from the image and stores the template for later authentication. The experiment results are very promising for recognition of second minor finger knuckle pattern.
Published by: Sanjna Singla, Supreet Kaur
Author: Sanjna Singla
Paper ID: V2I4-1151
Paper Status: published
Published: July 13, 2016
A Robust Cryptographic Approach using Multilevel Key Sharing Paradigm
Cloud computing is a popular technology that provides services to the users on demand and on pay-per-usage fee that is they only pay for the data utilized when required. With the vast growth in the use of mobile phone applications, the users are relying on their phones for their personal as well as professional work and suffering from many problems (storage, processing, security etc). To overcome these limitations and growth in the use of cloud applications, a new development area has emerged recently called as Mobile cloud computing. Mobile cloud computing is an integration of three technologies cloud computing, mobile computing and internet, enabling the users to access the services at any time and from any place. Mobile phones are sensitive devices and the personal data is not secured when user stores data on cloud and can be easily attacked by unauthorized person. This paper presents a two level encryption through a mobile application that encrypts the data before moving it to the cloud that ensures the security and the users authentication.
Published by: Tajinder Kaur
Author: Tajinder Kaur
Paper ID: V2I4-1150
Paper Status: published
Published: July 13, 2016
A Malicious Data Prevention Mechanism to Improve Intruders in Cloud Environment
We proposed a new model presents improved key management architecture, called multi-level complex key exchange and authorizing model (Multi-Level CK-EAM) for the Cloud Computing, to enable comprehensive, trustworthy, user-verifiable, and cost-effective key management. In this research, we will develop the proposed scheme named Multi-Level CK-EAM for corporate key management technique adaptable for the Cloud Computing platforms by making them integral and confidential. To add more security, there is a next step which includes Captcha, user has to fill the correct given Captcha which eliminates the possibility of robot, botnet etc. In addition, it also has to be created in way to work efficiently with Cloud nodes, which means it must use less computational power of the Cloud computing platforms.
Published by: Tajinder Kaur
Author: Tajinder Kaur
Paper ID: V2I4-1149
Paper Status: published
Published: July 13, 2016
Arduino based Low Cost Power Protection System
In this paper, harmonics, noises, reactive power etc. are considered as major concerns. This paper presents the development of simple power quality software for the purpose of protection of any system under fault conditions. By designing virtual instruments using LabVIEW software, the real time data of hardware are fed to the software using Arduino for interfacing with LabVIEW. The software recognizes the different types of fault conditions based on pre set values and indicates the type of fault occurred in system. It also disconnects the equipments on load side. Testing results and analysis indicate that the proposed method is feasible and practical for protection of the system during fault conditions.
Published by: Anurag Verma, Mrs. Shimi S.L
Author: Anurag Verma
Paper ID: V2I4-1148
Paper Status: published
Published: July 13, 2016
Extensive Labview based Power Quality Monitoring and Protection System
Power quality issues and mitigation techniques became hot research topics soon after the introduction of solid state devices in power system. The equipments of non-linear nature introduce power quality issues such as harmonics, reduction in power factor, voltage unbalance, transients etc. and cause malfunction or damage of power system equipments. In this paper, harmonics, noises, reactive power etc. are considered as major issues. There is an ever increasing need for power quality monitoring systems due to the growing number of sources of disturbances in AC power systems. Monitoring of power quality is essential to maintain proper functioning of utilities, customer services and equipments. The authors surveyed different existing methods of power quality monitoring already in use and available in literature and arrived at the conclusion that an improved and affordable power quality monitoring system is the need of the hour. This paper presents the development of a simple power quality system for the purpose of measurement by designing virtual instruments using LabVIEW software. The real time data of hardware are acquired and fed to the software using Arduino for interfacing with LabVIEW. All power quality parameters are also measured by fluke power analyzer for validation. Observations taken from the hardware under test depict the importance of power quality monitoring, and also the accuracy and the precision of the developed system. The testing results and analysis indicate that the proposed method is feasible and practical for analyzing power quality disturbances.
Published by: Anurag Verma, Mrs. Shimi S.L
Author: Anurag Verma
Paper ID: V2I4-1147
Paper Status: published
Published: July 13, 2016
Credit Card Fraud Detection and False Alarms Reduction using Support Vector Machines
In day to day life credit cards are used for purchasing goods and services with the help of virtual card for online transaction or physical card for offline transaction. In a physical-card based purchase, the cardholder presents his card physically to a merchant for making a payment. To carry out fraudulent transactions in this kind of purchase; an attacker has to steal the credit card. To commit fraud in these types of purchases, a fraudster simply needs to know the card details. Most of the time, the genuine cardholder is not aware that someone else has seen or stolen his card information. The only way to detect this kind of fraud is to analyze the spending patterns on every card and to figure out any inconsistency with respect to the “usual” spending patterns. To commit fraud in these types of purchases, a fraudster simply needs to know the card details. Most of the time, the genuine cardholder is not aware that someone else has seen or stolen his card information. The only way to detect this kind of fraud is to analyze the spending patterns on every card and to figure out any inconsistency with respect to the “usual” spending patterns. Fraud detection based on the analysis of existing purchase data of cardholder is a promising way to reduce the rate of successful credit card frauds. As manually processing credit card transactions is a time-consuming and resource-demanding task, credit card issuers search for high-performing and efficient algorithms that automatically look for anomalies in the set of incoming transactions. Data mining is a well-known and often suitable solution to big data problems involving risk such as credit risk modelling, churn prediction and survival analysis. Nevertheless, fraud detection in general is an atypical prediction task which requires a tailored approach to address and predict future fraud. Though most of the fraud detection systems show good results in detecting fraudulent transactions, they also lead to the generation of too many false alarms. This assumes significance especially in the domain of credit card fraud detection where a credit card company needs to minimize its losses but, at the same time, does not wish the cardholder to feel restricted too often. In this work, we propose a novel credit card fraud detection system based on the integration support vector machines.
Published by: Mehak Kamboj, Shankey Gupta
Author: Mehak Kamboj
Paper ID: V2I4-1145
Paper Status: published
Published: July 12, 2016
