Geoparsing means automatically identifying locations in text. The location mentions in messages during crime and disaster events are very crucial, as they can help emergency response teams to quickly identify the place to send rescue teams to the location. Use of social media during such crisis events has been rapidly increasing all over the world, as well as in India. We consider here the source of messages as Twitter because it is realtime, robust and can handle large amounts of data. We collect tweets at real time and then parse those tweets for crisis situation and location information. Extracting the location information to the level of streets & buildings will help to detect the exact location of the event; this is done with the help of NLP methods.We use classifiers to classify tweets to obtain the event occurred.

Problem statement: Morphing of images has evolved and become a challenging field in information hiding and data security. The objective of this study is to secure the image data over internet while transmitting using the concept of image morphing Approach: To address this issue, the study proposed the new approach for image data security using the concept of image morphing. The morphing algorithm produces the stego keys. These stego keys are securely transmitted over Internet using TCP/IP. The stego keys are transmitted through TCP/IP’s identification field. The proposed method suggests how to transmit stego keys through identification field of IP. Results: Exterior sample points were manually identified and its inner values were interpolated using a triangular mesh. The complexity of Beier and Neely algorithm is O (n, p, w). Where n is the number of feature lines p is no of pixels in the image w is the amount of computation required for one pair feature line. By our approach the complexity is O (n,k),where n is the number of pixels and k is the number of triangles. Computations required are less, thus effect in increasing the performance of algorithm. The stego keys are identified during morphing process. As complexity reduces the speed of stego keys identification increases. Conclusion: The result showed that the proposed approach is efficient in terms of complexity and speed to generate the morph. The solution proposed for image data security over Internet is highly secure because the keys were transferred through IP identification field. The randomness in the identification field value makes this scheme no detectable

In today's age of web 2.0, large numbers of product reviews posted on the Internet. Such reviews are important to customers or users and to companies. Customers use the reviews for deciding quality of product to buy. Companies or vendors use opinions to take a decision to improve their sales according to intelligent things done by other competitors. However, all reviews are given by customers or users are not true reviews. These reviews are given to promote or to demote the product. Some reviews are given on brand of product, and others are related to advertising of another product. There is need to find how many reviews are spam or non spam. In this paper, the system is proposed for detecting untruthful spam reviews using n-gram language model and reviews on brand spam detection using Feature Selection. Given system separately identifies spam and joined the result showing spam and non spam reviews.

A new morphed steganographic algorithm is proposed in this paper. Image security is a challenging problem these days. Steganography is a method of hiding secret data in cover media. The Least Significant Bit is a standard Steganographic method that has some limitations. The limitations are less capacity to hide data, poor stego image quality, and imperceptibility. The proposed algorithm focuses on these limitations. The morphing concept is being used for image steganography to overcome these limitations. The PSNR and standard deviation are considered as a measure to improve stego image quality and morphed image selection, respectively. The stego keys are generated during the morphed steganographic embedding and extracting process. Stego keys are used to embed and extract the secret image. The experimental results, which are based on hiding capacity and PSNR, are presented in this paper. Our research contributes towards creating an improved steganographic method using image morphing. The experimental result indicates that the proposed algorithm achieves an increase in hiding capacity, stego image quality, and imperceptibility. The experimental results were compared with state of the art steganographic methods.

Abstract:The quick response (QR) code was designed for storage information and high-speed reading applications. QR codes are used to create a link between the real world products (tagged with the QR code) and the Internet. A new rich QR code is proposed that has two storage levels: a public level and a private level. The public level can be read by any QR code reading application, while the private level is constructed by replacing the black modules by specific textured patterns. These patterns, do not introduce disruption in the standard reading process and always perceived as black modules by any QR code reader. Thus the private level is invisible to standard QR code readers. It can also be used for document authentication. It consists of information encoded using q-ary code with an error correction capacity which helps to increase the storage capacity of the QR code and to determine the original document from a copy. The sensitivity of the used patterns to the print-and-scan (P&S) process represents this authentication. The pattern recognition method can be used both in a private message sharing and in an authentication scenario. The storage capacity can be notably enhanced by increasing the code alphabet q or by increasing the textured pattern size.