Secure distributed cloud service using trusted third party
Cloud storage is a system with a distributed data center that takes advantage of virtualization technology and provides an interface for data storage. It makes servers or data centers able to work together for conveniently sharing and accessing resources. Enterprise cloud user demand that there is a secure supply chain and that every step in that supply chain can be verified in real-time and when things go wrong it is more possible to figure out what went wrong and that there is someone who can be held accountable. Before storing data to an untrusted cloud server, some measures should be adopted to guarantee the security of data. However, the communication overhead will increase when users transmit files encrypted by traditional encryption schemes. Remote data integrity checking enables a data storage server to prove to a verifier that it is actually storing a data owner’s data honestly. We use Hadoop file system to provide high throughput access to user data. If the semi-honest cloud server does not delete the data honestly and returns an incorrect deletion result, the misbehavior of the cloud server can be detected by the data owner with an overwhelming probability. The user cannot deny after requiring the cloud server to delete the data. This implies that the proposed scheme can support traceability.
Published by: Hari Kumar P., Chandra Sekar S., Dinesh Kumar V., Gopikrishna G.
Author: Hari Kumar P.
Paper ID: V5I2-1347
Paper Status: published
Published: March 26, 2019
3D reconstruction of regular objects from multiple 2D images using a reference object
The dimensional analysis of an object from an image reduces a lot of burden for a user, like the traditional measuring tape method. Using the dimensions will make reconstruction of the 3D model of the real-time object easier. However, this method is not used in the current implementation. Dimensional analysis can also be helpful in online shopping where the user’s availability for fitting is not possible. 3D model replaces the fitting stage in online shopping. Once the dimensions of an object’s surface are found, it is easy to calculate surface areas, given surface areas we can calculate volume. But the calculation of volume requires more than one dimension of the object. In this paper, an approach using a reference object, whose real-time dimensions are already known is used. The whole process is divided into three tasks - Object detection using SURF algorithm, Dimensional Analysis of the 2D object using pixel per metric ratio given that there is a reference object on the same plane and 3D reconstruction using Structure from Motion algorithm.
Published by: Krishna Sai Joga, K. Kavya Sree, Navya Spandana, G. Gowri Pushpa
Author: Krishna Sai Joga
Paper ID: V5I2-1477
Paper Status: published
Published: March 26, 2019
Forensic Criminology
This research focuses on the history development of forensic science and also shed light on the fusion of science and law that is how forensic science has brought in the administration of justice. This research aims to point out the flaws in the laws with reference to forensic evidence.
Published by: Barani Manikantan
Author: Barani Manikantan
Paper ID: V5I2-1317
Paper Status: published
Published: March 25, 2019
Fire monitoring system using RF module
The objective of this project is to design and monitor system for the fire alerts in the surrounding environment using Flame sensor. It is transmitted wirelessly using an RF module. The output is displayed in LCD and Lab-VIEW GUI.
Published by: Vedashree J., Abinaya S., Ganesh Babu C., Muchenedi Hari Kishor
Author: Vedashree J.
Paper ID: V5I2-1268
Paper Status: published
Published: March 25, 2019
Twitter sentimental analysis
This paper presents the effectiveness of linguistic features to identify the sentiment of Twitter messages using the apache storm framework. We calculate the effectiveness of present lexical resources and features that capture information about the informal and creative language used in microblogging. In the past few years, there has been a huge growth in the use of microblogging platforms such as Twitter. Influenced by intensification, companies, and media organizations are increasingly seeking ways to excavate Twitter information about what people think and feel about their products and services. Here we download Twitter messages for a particular hashtag and carry out sentiment analysis i.e. to find a positive, negative or neutral sense of that tweet using apache storm framework. Each hashtag may have 1000 of comments and new comments are added every minute, in order to handle so many live tweets we are using apache storm framework.
Published by: Mandar Menjoge, Vedant Bhawalkar, Mazhar Sayyad, Jainam Gosaliya
Author: Mandar Menjoge
Paper ID: V5I2-1396
Paper Status: published
Published: March 25, 2019
Anomaly detection in code base
Any product when under development, goes through numerous changes before finally being released to the customer. While these changes are being done, it adds new features, modifies existing ones. How do we know if a product is in good shape to be released? Yes, we test the product, run the existing unit, functional, performance tests etc. What if the number of tests is in 10000s. How do we analyse each test result? Is there an automated way to detect the overall health of the product using the results of regression tests? Anomaly Detection using machine learning algorithms gives us a way to find out the overall health of the product. Using Anomaly Detection, we can quickly find out about the code base and if new changes should be allowed in before the existing code base is stabilized. It helps to determine, how far the existing code base is away from being released to the customer. It can help the code base to be almost always stable irrespective of the number of code changes that are merged into it.
Published by: Sudipto Nandan
Author: Sudipto Nandan
Paper ID: V5I2-1418
Paper Status: published
Published: March 25, 2019
