IJETE
Call for papers , Manuscript submission last date 30th April 2018. Send to ijete.editor@ijete.org

Volume 2 Issue 1 January 2015 Edition

SECURE3 AUTHENTICATION FOR SENSITIVE DATA ON CLOUD USING NORMAL, CHESSBOARD AND QR CODE PASSWORD SYSTEM
BHUSHAN SHINDE, PANKAJ PATIL, PUJA KASBE, SHARAD GHODAKE, PROF. V. WAGHMARE
pp 1-6
Abstract: Existing systems of authentication are plagued by many weaknesses. As a high-speed cloud infrastructure is being developed and people are informationalized, the sensitive data are also engaged in cloud field. However, the existing cloud sensitive file upload and download on cloud was exposed to the danger of hacking. Recently, the personal information has been leaked by a high-degree method such as Phishing or Pharming beyond snatching a user ID and Password. Seeing that most of examples which happened in the file uploading and downloading were caused by the appropriation of ID or Password belonging to others, a safe user confirmation system gets much more essential. In this paper, we propose a new authentication system file uploading and downloading on cloud using HADOOP technique. This authentication system is a combination of a three authentication system i.e. Secure3 system that Normal+Chessboard+QR-code Authentication.
IMAGE QUALITY ASSESSMENT FOR FAKE BIOMETRIC DETECTION:APPLICATION TO FACE AND FINGERPRINT RECOGNITION
SHRUTI GHORPADE, DHANASHRI GUND, SWAPNADA KADAM, PROF.MR.R.A.JAMADAR
pp 7-10
Abstract: Security is major concern for today’s scenario. A high level industry uses passwords like thumb, face, voice, iris, etc. So many security systems are available. But not so reliable. Here the developing system which is very precise and reliable. The system has two stages which is embedded system. Even if any stage is cracked falsely, unauthorized entry will be detected.Liveness detection methods are usually classified into two techniques. First is a Software-based techniques, in this case the fake trait is detected once the sample has been acquired with a standard sensor (i.e., features used to distinguish between real and fake traits are extracted from the biometric sample, and not from the trait itself). and second is a Hardware-based techniques, which add some specific device to the sensor in order to detect particular properties of a living trait (e.g., fingerprint sweat, blood pressure).The thumb samples are stored in the sensor If there is a fake samples which does not match with the stored samples (i.e.Face,Fingerprint) then the buzzer will beep continuously.The two types of methods present certain advantages and drawbacks over the other and, in general, a combination of both would be the most desirable protection approach to increase the security of biometric systems. As a coarse comparison, hardware-based schemes usually present a higher fake detection rate, while software-based techniques are in general less expensive (as no extra device is needed),and less intrusive since their implementation is transparent to the user.
HUMAN HEARTBEAT SENSING ROBOT USING ZIGBEE TECHNOLOGY
B.PRASANTH, A.RAVISHANKAR
pp 11-16
Abstract: This project is to design the robot for medical applications to monitor the patient’s status and give information to the doctor. In this project patient’s heartbeat is monitored with the help of heartbeat sensor. This data is given to the microcontroller through the scu. A microcontroller act as a brain or heart of the project. It as both analog and digital signal in a series communication. Here we else flash type reprogrammable microcontroller. If patient goes to the abnormal state this microcontroller transmits this information to the robot model ZigBee act as a communication protocol. In a root model ZigBee receives this information then if search the doctor presences with the help of RFID. RFID tag is placed in the doctor’s ID card. If doctor is identified by the robot means it gives voice information about the patient with the help of APR9600 and speaker.
SECURING ONLINE SHOPPING SYSTEM USING VISUAL CRYPTOGRAPHY
PROF. D. B. SATRE, VARAD DURUGKAR, AKSHAY AMBEKAR, AMITKUMAR YADAV, SUDARSHAN PATIL
pp 17-19
Abstract: In today’s world of internet, various online attacks has been increased as well as spread and among them the most famous and harmful attack is phishing. it is trying by an individual person or a group to get personal secret confidential information such as passwords, all types of card information from unsuspecting victims for identity theft, financial gain and other stolen activities. Fake websites which appear very like to the original ones are being hosted to gain this. Here an image based authentication using Visual Cryptography is implemented. The use of visual cryptography is traverse to preserve the privacy of an image captcha by decomposing means that original image captcha into two shares (known as sheets) that are generated by bank server. Original image captcha can be betrayed only when both are simultaneously available. the individual sheet images do not betray the identity of the original image captcha. Once the original image captcha is passed to the user it can be used as the password by user. Using this website cross verifies its identity and proves that it is a genuine website before the end users.by Using (2,2) visual secret sharing scheme a secret image is encrypted in shares which are meaningless images that can be transmitted or distributed over an untrusted communication channel.
IMAGE BINARIZATION AND OCR TOOLKIT FOR OLD DEGRADED DOCUMENTS
PROF.D.J.BONDE, PRATHAMESH BHOKARE, RAMDAS CHAVAN, AKASH DHAWADE, PRASHANT PATULE
pp 20-24
Abstract: Segmentation of text from badly degraded document images is a very challenging task. Because of little bit difference between background and foreground text of various document images. In this paper we propose image binarization technique which addresses the issue of adaptive image contrast which is combination of local image contrast and local image gradient . In this technique adaptive contrast map is first constructed as an input of degraded document image. The contrast map is then binarized and combined with Canny’s edge map to identify the text stroke edge pixels. Then further document is segmented by a local threshold that is estimated based on the intensities of detected text stroke edge pixels within a local window. The proposed method is simple, robust, and involves minimum parameter tuning.