Implementation of Anonymous and Secure Communication System with Group Signatures
For Privacy Preserving Communications Both Anonymity and end to end encryption mechanism is essential. Identity Based Encryption technique is best suitable for secure and anonymous communications. For solving anonymous and secure communication problems both cryptographic and IBE based protocols needed which governs the proper communication between two parties. For the purpose of authentication of the user proxy server is maintained between user and service providers. The GM and KGC is essential in anonymous communication for issuing both signing and decryption keys for getting plaintext from ciphertext in original form. Public key encryption and digital signature mechanism needed for guarantees of secure communication between both ends. Finally protocol realizes secure and anonymous communication between sender and receiver. The Communication Protocol along with IBE and Group signatures allow secure anonymous authentication. In this way, illegitimate users cannot use anonymous system and cannot effect the communication between source and destination whereas legitimate users access systems without compromising anonymity. In this way the proposed system get secure and anonymous communication over the network. Keywords: Anonymous Communication, Anonymous Authentication, Secure Channel, Identity-Based Encryption, Group Signature.
Published by: Mr. Vaibhav P. Thakare, Prof . Chetan J. Shelke
Author: Mr. Vaibhav P. Thakare
Paper ID: V3I3-1370
Paper Status: published
Published: May 30, 2017
Development of Data Mining Model for the Evaluation of Human Skill Placement in the Engineering Sector
Data mining is one of the widespread research areas of present time as it has got wide variety of application to help people of today’s world. It is all about finding interesting hidden patterns in a huge history database. In this research work, data mining is comprehensively applicable to a domain called placement chance prediction, since taking wise career decision is so crucial for all of us for sure. A strategy to predict the overall absorption rate for every branches as well as the time it takes for all the students of a particular branch to get placed etc. are also proposed. From each combination of attributes from the history database of student records, corresponding placement chances is computed and stored in the history data base. From this data, various popular data mining models are built and tested. These model can be used to predict the most suitable branch for a particular new student with one of the above combination of criteria. A strategy to predict the overall absorption rate for various branches as well as the time it takes for all the students of a particular branch to get placed etc. are also proposed. The proposed method is tested on the data set provided by A.I.M.T college Lucknow and data is passes through the various data mining model, namely decision tree ,neural network and navie bayes classifier on area of the application to a domain, development of classifier and future outcomes were also configured on this thesis. At last this research work puts forward the data mining algorithm namely C 4.5 * stat for numeric data sets which has been proved to have competent accuracy over standard benchmarking data sets called UCI datasets. It also proposes to improve the standard C 4.5 algorithm.
Published by: Arun Mishra
Author: Arun Mishra
Paper ID: V3I3-1407
Paper Status: published
Published: May 30, 2017
An IOT Approach to Monitor Water Quality Using MQTT Algorithm
The degradation of water resources has become a common problem. The conventional methods of water quality monitoring involves the manual collection of water sample from different locations. These water samples were tested in the laboratory using the rigorous skills. Such approaches are time consuming and no longer to be considered efficient. Moreover, the current methodologies include analysis of various kinds of parameters of water quality such as physical and chemical. The old method of water quality detection and communication was time consuming, low precision and costly. Therefore, there is a need for continuous monitoring of water quality parameters in real time. By focusing on the above issues, a low cost water quality monitoring system is developed and designed that can monitor water quality in real time using IOT. In the proposed system water quality parameters are measured by the different sensors such as pH, turbidity, dissolved oxygen and temperature for communicating data onto a platform via microcontroller system i.e. Arduino model. So in order to meet all these requirements, other technologies can be used such as MQTT (Message Queuing Telemetry Transport) which allows publishing and subscribing od data between the sensor and end device. Instead of using GSM network or any other technology, MQTT algorithm will be implemented to make the system feasible, modular, scalar and cost-efficient. Not only this , with the help of MQTT algorithm there will be simultaneous flow of data between the sensors and server.
Published by: Mehwish Mir
Author: Mehwish Mir
Paper ID: V3I3-1415
Paper Status: published
Published: May 30, 2017
Improving the Performance for Crime Pattern Analysis Using Data Mining Techniques
As the crimes rates against women is increase day by day, the new problems are faced by the law organisation. Due to which this cause more burdens on the crime against women resources. The law organisation is able to generate such increases or decreases in crime, so it is necessary to find out the most useful method to control and avoid crimes against women. The aim of this paper is to classify clustered crime against women based on occurrence frequency during different years by the process of Data mining. Data mining is used to analysis, investigate and discovery of patterns for occurrence of different crimes against women. We connected a hypothetical model in light of information mining strategies, for example, grouping and characterization to real crime dataset recorded by OGD. The k-means clustering, KNN algorithm, decision tree algorithm and prediction method for future purpose, is used for the classification and clustering of crimes
Published by: Chhaya Yadav
Author: Chhaya Yadav
Paper ID: V3I3-1422
Paper Status: published
Published: May 30, 2017
Study and Synthesis of Manganese Doped Tio2 Nanoparticles
Nanoparticles of un-doped, 5%, 10%, 15% Mn doped TiO2 were prepared by the sol-gel technique by adding different proportions of Manganese to the Titanium dioxide and characterized using XRD and SEM. This increase in doping proportion of Mn in the oxide material reduced the band gap to a larger extent, so this material is activated under visible light. As the doping level of Manganese increased, the material acquired the property of Ferro-magnetism at room temperature. The simulation studies were carried out using DFT tool and analyzed.
Published by: P. Prudhvi Raj, Y. Bhaskar Rao
Author: P. Prudhvi Raj
Paper ID: V3I3-1423
Paper Status: published
Published: May 30, 2017
Location Based Smart Energy Meter
The paper deals with monitoring and controlling of electric power consumption on real time basis, thereby generating consumption statistics using IOT. It helps the user to know his/her power consumption. This could sub-sequentially reduce the manual work involved in the process of collecting the number of units consumed and for avoiding the manual costs and errors. The setup of this system is simple and does not require much hardware. The main elements are sensors which are interfaced to Intel Galileo Zen 2 with a Wi-Fi module for transmission of data (to the open source IOT platform Thing speak, where statistics can be viewed, there by controlling can be done).
Published by: K. C Mohan Kumar, V. Venugopal Reddy, Y. Bhaskarrao
Author: K. C Mohan Kumar
Paper ID: V3I3-1424
Paper Status: published
Published: May 30, 2017
