AIRCC's International Journal of Computer Science and Information Technology

Kavuri Roshan ¹, K. Reddi Prasad ¹, Niraj Upadhayaya ¹, A. Govardhan ²

Affiliations
1 Department of Computer Science and Information Technology, J.B. Institute of Engineering and Technology, Hyderabad, Andhra Pradesh, IN
2 Department of Computer Science, JNTUH, Kukatpally, Hyderabad, IN

Abstract

Mobile users like to use their own consumer electronic devices anywhere and at anytime to access multimedia data. Hence, we expect that wireless ad hoc networks will be widely used in the near future since these networks form the topology with low cost on the fly. However, consumer electronic devices generally operate on limited battery power and therefore are vulnerable to security threats like data flooding attacks. The data flooding attack causes Denial of Service (DoS) attacks by flooding many data packets. However, there are a few existing defence systems against data flooding attacks. Moreover, the existing schemes may not guarantee the Quality of Service (QoS) of burst traffic since multimedia data are usually burst. Therefore, we propose a novel defence mechanism against data flooding attacks with the aim of enhancing the throughput.

Keywords

Data Flooding Attack, Throughput, Bursttraffic, Wireless Ad Hoc Network.

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A. P. SivaKumar ¹, P. Premchand ², A. Govardhan ³

Affiliations
1 Department of Computer Science Engineering, JNTUACE, Anantapur, IN
2 Department of Computer Science Engineering, Osmania University, Hyderabad, IN
3 Department of Computer Science Engineering, JNTUHCE, Nachupalli, IN

Abstract

Retrieving information from different languages may lead to many problems like polysemy and synonymy, which can be resolved by Latent Semantic Indexing (LSI) techniques. This paper uses the Singular Value Decomposition (SVD) of LSI technique to achieve effective indexing for English and Hindi languages. Parallel corpus consisting of both Hindi and English documents is created and is used for training and testing the system. Removing stop words from the documents is performed followed by stemming and normalization in order to reduce the feature space and to get language relations. Then, cosine similarity method is applied on query document and target document. Based on our experimental results it is proved that LSI based CLIR gets over the non-LSI based retrieval which have retrieval successes of 67% and 9% respectively.

Keywords

Latent Semantic Indexing, Cross Language Information Retrieval, Indexing, Singular Value Decomposition.

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K. Venkateswara Rao ¹, A. Govardhan ², K. V. Chalapati Rao ¹

Affiliations
1 Department of Computer Science and Engineering, CVR College of Engineering, Ibrahimpatnam RR District, Andhra Pradesh, IN
2 JNTUH College of Engineering, Jagityala, Karimnagar Dist, Andhra Pradesh, IN

Abstract

Spatiotemporal databases deal with changes to spatial objects with time. The Spatiotemporal knowledge discovery process involves the integration of such database systems with data warehousing, data mining and online-analytical processing technologies. The applications in this domain will process spatial, temporal and attribute data elements and use spatio-temporal relationships among these elements. These applications deal with the evolution of spatial objects and changes in their topological relationships, associations along with time. These advanced database applications require storing, management and processing of complex spatiotemporal data. In this paper we consider the classification and modeling requirements for spatiotemporal applications, System modeling, preprocessing spatiotemporal data, discovering spatiotemporal topological relationships and extension of apriori algorithm for mining spatiotemporal frequent predicates. The design of an appropriate system that can capture spatiotemporal features of datasets is discussed. Prototype implementation of the system is carried out on top of open source object relational spatial database management system called postgresql and postgis. The algorithms are experimented on historical cadastral datasets which are created using OpenJump. The results that are visualized using OpenJump software are presented.

Keywords

Spatiotemporal Database, Spatiotemporal Application, Spatiotemporal Data Modeling, Spatiotemporal Relationships, Spatiotemporal Data Mining, Spatiotemporal Data Analysis.

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T. Venkat Narayana Rao ¹, A. Govardhan ², Syed Jahangir Badashah ³

Affiliations
1 Tirumala Engineering College, Bogaram, Kesara, RR District, A.P., IN
2 Jawaharlal Nehru Technological University, Hyderabad, College of Engineering, Jagityala, A.P., IN
3 Sathyabama University, Chennai, IN

Abstract

This paper proposes a reversible data hiding mechanism based on multiresolution analysis with difference expansion algorithm. Based on the multiresolution analysis of an image, gradient information of crude original image is exploited to select proper embedding areas. Adaptively embedding method based on Difference Expansion Algorithm is proposed to embed data into the host image without causing overflow/underflow and distortion problems. The original host image can be obtained upon the extraction of the embedded information. Driving application of reversible date hiding is authentic and can be used in some special applications, such as law enforcement, banks, medical and military fields, where original cover media is required for legal reason. Embedding data into cover media while keeping the media reversible opens a new door for linking some data with original media. With this proposed method we ensure that the Host information improves the compression efficiency, and thus the lossless data embedding capability is achieved. Experimental results signify that the proposed reversible data hiding method can embed a large payload with low visual distortion in the host image.

Keywords

Reversible, Data Hiding, Authentication, Lossless Extraction, Multi-Resolution, Embedding, Peak Signal to Noise Ratio, Stego-Image.

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G. Shyama Chandra Prasad ¹, A. Govardhan ², T. V. Rao ³

Affiliations
1 JNTUH, Hyderabad, AP, IN
2 JNTUH, College of Engineering, jagitial, Karimnagar, AP, IN
3 Chaithanya Institute of Engineering and Technology, Kakinada, AP, IN

Abstract

In this paper, an approach to integral color texture invariant information with a neural network approach to object recognition is proposed. A color-texture context for image retrieval system based on the integral information of an image is represented as one compact representation base on color histogram approach. A general and efficient design approach using a neural classifier to cope with small training sets of high dimension, which is a problem frequency encountered in object recognition, is focused in this paper for general images. The proposed system is tested for various colored image samples and the recognition accuracy is evaluated.

Keywords

Color-Texture Context, Recognition System, Histogram, Neural Network.

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