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International Journal of Science Engineering and Technology International Journal of Science, Engineering and Technology A Peer Reviwed Journal Volume 1 | Issue 1 | October – November 2013 For detailed manuscript submission guidelines, visit http://www.ijset.in/?pageid=110 Volume 1 | Issue 1 | October‐ November 2013 International Journal of Science, Engineering and Technology Volume 1 | Issue 1| October‐ November 2013 Editorial Board Editor in Chief Dr. Kavita Sharma Editorial Board Member Dr. Anil Gupta Dr. Priyanka Gupta Mr. Saurabh Shukla Mr. Naveen Upadhyay Mr. Kshitiz Agarwal Prof. Mohsin Jamal (Dr.) Jitendra Joshi Mr. Parvin Kumar Dr. Sanjay Kumar Dr. Raghvendra Kr. Mishra Mr. Narendra Singh Rathore (Dr.) Giriraj Kumar Patidar Mr. Anoop Singhal International Journal of Science, Engineering and Technology 1 | Page Volume 1 | Issue 1 | October‐ November 2013 International Journal of Science, Engineering and Technology Volume 1 | Issue 1| October‐ November 2013 CONTENTS A Mechanics for Assuring Data Storage Security in Cloud Computing 3 Priya, Pratibha Gangwar, Mamta Gadoria VHDL Implementation for FSM Based Approaches of Traffic Light Controller 8 Nidhi Gopal, Madhuri Panwar, Pinky Gupta TAUR’S Model: An Analytical Solution for Drain Current in Undoped Body SDG 12 MOSFET Madhuri Panwar, Nidhi Gopal, Naveen Upadhyay Image Compression Technique Using Wavelet Transformation 16 Nidhi Gopal, Madhuri Panwar, Naveen Upadhyay Automatic Telephone Answering Machine With Image Processing 20 Richa Singh Rathore, Disha Malik 32‐bit Arithmetic Logical Unit (ALU) using VHDL 25 Disha Malik, Richa Singh Rathore Server Clustering Technology and Concept 31 Vaibhav Mathur M00383937, Computer Network, Middlesex University Cookies, and it’s tracking mechanism for User’s Identification 37 Vaibhav Mathur, M00383937, Computer Network, Middlesex University A Broadband Biconical Antenna for Wide Angle Reception 41 Saurabh Shukla, Naveen Upadhyay A Combination of Video Games and Artificial Intelligence 45 Jaya Sachan Accomplishment and Timing Presentation: Clock Generation of CMOS in VLSI 50 Manoj Kumar Choudhary Dynamic Model Representation in the Locality Frequent Neural Networks 55 Jitendra Joshi, Ritu Nagwani, Renu Deswal, Priyanka Sharma Future of V Band in Satellite Communication 60 Ashish Tyagi, Chandan Choudhary, Naveen Upadhyay International Journal of Science, Engineering and Technology 2 | Page Volume 1 | Issue 1 | October‐ November 2013 A MECHANICS FOR ASSURING DATA STORAGE SECURITY IN CLOUD COMPUTING 1Priya, 2Pratibha Gangwar, 3Mamta Gadoria 1M. Tech. Scholar, Jayoti Vidyapeeth Women’s University, Jaipur, [email protected] 2M. Tech. Scholar, Jayoti Vidyapeeth Women’s University, Jaipur, [email protected] 3M. Tech. Scholar, Jayoti Vidyapeeth Women’s University, Jaipur, [email protected] ABSTRACT Cloud Computing has been visualized as the next generation architecture of IT Enterprise. In contrast to traditional solutions, where the IT services are under proper physical, logical and personnel controls, Cloud Computing moves the application software and databases to the large data centers, where the management of the data and services may not be fully trustworthy [3]. This unique attribute however, poses many new security challenges which have not been well understood. In this we focus on cloud data storage security, which has always been an important aspect of quality of service. To provide the correctness of users’ data in the cloud, we propose an effective and flexible distributed scheme with two salient features, opposing to its predecessors. By utilizing the homomorphic token with distributed verification of erasure‐coded data, our scheme achieves the integration of storage correctness insurance and data error localization, i.e., the identification of misbehaving server(s). Unlike most prior works, the new scheme further supports secure and efficient dynamic operations on data blocks, including: data update, delete and append. Extensive security and performance analysis shows that the proposed scheme is highly efficient and resilient against Byzantine failure, malicious data modification attack, and even server colluding attacks. Index Terms: Cloud Computing, Cloud Service Provider, Cloud data storage, Error localization 1. Introduction integrity of their data [2]. From the perspective of data Organizations today are increasingly looking towards security, which has always been an important aspect Cloud Computing as a new revolutionary technology of quality of service,. Considering various kinds of data promising to cut the cost of development and for each user stored in the cloud and the demand of maintenance and still achieve highly reliable and long term continuous assurance of their data safety, elastic services. The Cloud technology is a growing the problem of verifying correctness of data storage in trend and is still undergoing lots of experiments. Cloud the cloud becomes even more challenging. The data promises huge cost benefits, agility and scalability to stored in the cloud may be frequently updated by the the business. All business data and software are users, including insertion, deletion, modification, stored on servers at a remote location referred to as appending, reordering, etc. To ensure storage Data centers [1]. Cloud Computing is an Internet‐based correctness under dynamic data update is hence of development. Users can now subscribe high quality paramount importance [3]. services from data and software that reside solely on remote data centers. The pioneers of Cloud 2. Problem Statement Computing Vendors are Amazon Simple Storage The proposed system has three important entities. Service (S3) and Amazon Elastic Compute Cloud (EC2) User: Users store data in the cloud and depend on the [5]. While these internet‐ based online services do cloud for all its computations on the data stored in the provide huge amounts of storage space and cloud. customizable computing resources, this computing Cloud Service Provider (CSP): CSP contains resources platform shift, however, is eliminating the and expertise in building and managing distributed responsibility of local machines for data maintenance cloud storage servers, owns and operates and leases at the same time. As a result, users are at the mercy of the live Cloud computing systems. their cloud service providers for the availability and International Journal of Science, Engineering and Technology 3 | Page Volume 1 | Issue 1 | October‐ November 2013 Third Party Auditor (TPA): TPA has expertise and capabilities that users may not have, is trusted to assess, audit and expose risk of cloud storage services on behalf of the users upon request from the users. A special entity is considered to ensure the security and dependability of the Cloud Server referred to as Adversary Model. The adversary is interested in Figure 1.1: Cloud data storage architecture continuously corrupting the user’s data files stored on individual servers. Once a server is comprised, an A. Limitations of Existing System : These adversary can pollute the original data files by techniques, while can be useful to ensure the storage modifying or introducing its own fraudulent data to correctness without having users possessing data, prevent the original data from being retrieved by the cannot address all the security threats in cloud data user [4]. storage, since they are all focusing on single server scenario and most of them do not consider dynamic 3. Cloud Data Storage Architecture With Existing data operations. As a complementary approach, System researchers have also proposed distributed protocols From the perspective of data security, which has for ensuring storage correctness across multiple always been an important aspect of quality of service, servers or peers. Again, none of these distributed Cloud Computing inevitably poses new challenging schemes is aware of dynamic data operations. As a security threats for number of reasons. result, their applicability in cloud data storage can be 3.1 Firstly, traditional cryptographic primitives for the drastically limited.[4] purpose of data security protection cannot be directly adopted due to the users’ loss control of data under B. Proposed System Cloud Computing. Therefore, verification of correct In this paper, we propose an effective and flexible data storage in the cloud must be conducted without distributed scheme with explicit dynamic data support explicit knowledge of the whole data. Considering to ensure the correctness of users’ data in the cloud.. various kinds of data for each user stored in the cloud This construction drastically reduces the and the demand of long term continuous assurance of communication and storage overhead as compared to their data safety, the problem of verifying correctness the traditional replication‐based file distribution of data storage in the cloud becomes even more techniques. Whenever data corruption has been challenging. detected during the storage correctness verification, 3.2 Secondly, Cloud Computing is not just a third party our scheme can almost guarantee the simultaneous data warehouse. The data stored in the cloud may be localization of data errors, i.e., the identification of the frequently updated by the users, including insertion, misbehaving server(s) [4]. delete ion, modification, appending, reordering, etc. C. Advantages of Proposed System To ensure storage correctness under dynamic data 1. Compared to many of its predecessors, which only update is hence of paramount importance. provide binary results about the storage state across the distributed
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