Informatics Publishing Limited

D. Radhika ¹, D. Aruna Kumari ²

Affiliations
1 Computer Science Engineering, K L University, Guntur - 522502, Andhra Pradesh, India, IN
2 Department ECM, K L University, Guntur - 522502, Andhra Pradesh, IN

Abstract

Objectives: To proposed and implement a framework that facilitates exploration of algorithms for big data mining. Methods/Analysis: To achieve objectives, a framework is built in order to realize algorithms for big data mining and even provide Mining as a Service in cloud. As the existing data mining techniques can not work for MapReduce programming in distributed environment, we proposed new and equivalent method for k-Anonymity that can leverage the parallel processing power. Single host Hadoop is used to demonstrate the proof of concept of the proposed framework. Findings: The framework has ability to mind big data. It has the centralized service that can be used to mine data of different users. However, as of now, the framework is realized with only one algorithm that is MapReduce version of k-Anonymity which is meant for privacy preserving data mining. The application is proved to be scalable in distributed environment. The framework has provision for supporting cloud users to outsource their data for mining big data with different algorithms of their choice. The results revealed that the proposed framework can provide mining services to cloud users and help them to save money by reusing the service instead of reinventing the wheel. Novelty/Improvement: In the proposed work a mining service for cloud is proposed which is a novel idea that has not been implemented so far. It can save money and time to enterprises in the real world.

Keywords

Algorithms, Big Data, Big Data Mining, Mining Service.

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D. Aruna Kumari ¹, Y. Vineela ¹, T. Mohan Krishna ¹, B. Sai Kumar ¹

Affiliations
1 Department of Electronics and Computers, K L University, Guntur – 522502, Andhra Pradesh, IN

Abstract

For both the production and consumption of data the internet is becoming a standard whereas the security for private data is gradually decreasing. Therefore, to have a safe transaction in the data, security and privacy would be the key issues to be considered. In recent days, privacy has become a key issue in many data mining and knowledge discovery fields which lead to the development of many Privacy Preserving Data Mining (PPDM) techniques. In our work we use few of these techniques to privately preserve the data holder such as hospital data. In this we use techniques named “Anonymization”, “Suppression”, “Generalisation” and “Data Hiding” on different fields for the data to be more secure and project the data which is useful to the public. This is a new way of our approach to create awareness among the public to be more attentive and health conscious. The modified data is clustered based on diseases. Based on the end user requirement the private data of the individual is hidden and the required data is projected.

Keywords

Anonymization, Cluster, Data Hiding, Generalisation, Privacy Preserving Data Mining (PPDM), Suppression

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D. Aruna kumari ¹, M. Chandrika ¹, B. Surekha Ratnam Bharadwaj ¹

Affiliations
1 K L University, Green Fields, Vaddeswaram, Guntur-522008, Andhra Pradesh, IN

Abstract

Background/Objectives: The main objective is to provide security using Magnified Cipher Block Chaining mode-DES to ensure secure data on cloud. Methods: In this work we have to find how the data is converted into binary and splits into blocks of particular size. By using Magnified Cipher block chaining mode-DES we encrypt data and store into cloud. We send the key to the receiver then he/she access the data from the cloud and decrypt the data. By this methodology we can ensure high security because even cloud server cannot access data. Findings: In this research, many encryption and decryption algorithms like AES, DES, RSA, Cipher Block Chaining modes have been taken into account. By using the DES operation we proposed a magnified Cipher Block Chaining mode –DES to find out how the data is divided into blocks and how the DES operation will perform. In this work we also find out the several algorithms like AES, DES etc. DES algorithm has been designed to provide more secure because the data is to be perform 16 rounds for encryption and decryption. In our work we divide the data into blocks and encrypt the data using DES algorithm and sent to the next block depending on the midvalue+position. Like this all the blocks of the data are encrypted and decrypted. By this methodology we can provide more secure because we are storing the encrypted data in the cloud so that even cloud server cannot access. Improvement: In order to provide security we propose a Magnified Cipher Block Chaining mode using DES. On the basis of mid value + positions the data is encrypted and decrypted.

Keywords

Cipher Blocks Chaining, Cloud, Encryption, Decryption, Magnified, Security

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Ch. Lakshmi Manoja ¹, D. Aruna Kumari ¹

Affiliations
1 Department of Electronics and Computer Engineering, KL University, Vijayawada, Andhra Pradesh, IN

Abstract

Objective: Wireless sensing element network needs sturdy and efficiency economical transmission code to attenuate the efficiency utilization and increase the safety of the maximum amount as double. Methods/Statistical Analysis: The researchers principally are considering energy overwhelming. A grid-based technique is suggested as an answer for this drawback. Findings: The advised theme extends High Energy at the start and permits multi-hop communication among the collection by consolidates the collection of coordinated causing and receiving nodes. The functioning of the suggested system is to calculate in terms of dependableness and efficiency potency. Novelty/Improvements: Reproduction results show that marvellous vitality savings is achieved by accepting draining network time period theme among the grids.

Keywords

Clustered Routings, Grid Network, Hotspot Effect, Mobile Routers, Sensor Networks

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D. Aruna Kumari ¹, T. Gunasekhar ²

Affiliations
1 Department of ECM, K L University, Vaddeswaram, Guntur - 522502, Andhra Pradesh, IN
2 Department of CSE, K L University, Vaddeswaram, Guntur - 522502, Andhra Pradesh, IN

Abstract

Background/Objectives: In the cloud computing environment, since information owner's stress over private data in their information being revealed without authorization, they attempt to hold the learning inside of the information, while applying security saving strategies to the information. Methods/Statistical Analysis: Before, an information bother methodology was ordinarily used to adjust the first information content; however it likewise brings about information twisting, and henceforth prompts noteworthy loss of learning inside of the information. To protect the user privacy, a convertible a randomization scheme is required. It allows the specific recipient to retrieve a perturbed data and that into the original signature so that it achieves enough privacy verifiability for the user. Findings: In this paper, we propose a novel and secure reconstruction scheme with privacy measure. To take care of this issue, this study presented the idea of reversible whole number change in the picture handling area and added to a Reconstruction algorithm calculation that can disturb and restore information. In this paper we developed an extended block cipher mode method that effectively masks the sensitive information of health care systems database. Application/Improvements: In the final section, we analyze the privacy performance with various parameter values.

Keywords

Cloud Computing, Data perturbation, Privacy-Preserving, Privacy Measure, Reconstruction.

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N. Gowtham Kumar ¹, Niranjan Polala ², D. Aruna Kumari ³

Affiliations
1 Computer Science and Engineering, KL University, Vijayawada - 522502, Andhra Pradesh, IN
2 Department of Computer Science and Engineering, KITS, Warangal - 506009, Telangana, IN
3 Department of Electronics & Computer Engineering, KL University, Vijayawada - 522502, Andhra Pradesh, IN

Abstract

Background/Objectives: The recent revolution in information technology has had a major impact on Global Communication. The use of Cloud computing in many organizations has significantly increasing due to the benefits in terms of accessibility and inexpensive in general. Due to these anticipated advantages of Cloud Computing many companies and users do not analyze the security issues carefully. Methods/Statistical Analysis: The unprecedented massive surveillance carried out by unauthorized parties around the world threaten cloud users. Offering strong data protection and build confidence to rich applications in the cloud is a challenging task. To mitigate technical impediments in cloud this paper suggested some available security prepositions. Findings: This paper mainly focuses on various propositions such as protecting virtual infrastructures, use of proxies and SSH tunneling, Disk encryption to provide protection for the data at rest, Homomorphic encryption to provide confidentially to the data in transit and finally data integrity to check whether data modified at cloud servers, to take care of privacy and freedom of data of Cloud users while adapting to cloud. Applications/Improvements: These security prepositions may ensure in increasing the trust to incorporate the user services on the cloud beyond the shadow of the doubt.

Keywords

Data Integrity, Encrypted, Homomorphic Encryption, Multi-Tenancy, Massive Surveillance, Side Channels Attacks, Tunneling.

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M. Chakravarthi ¹, D. Aruna Kumari ², D. Aruna Kumari ²

Affiliations
1 Department of Electronics and Computer Engineering, KL University, Vaddeswaram, Guntur – 522502, Andhra Pradesh, IN
2 Department of Electronics and Computer Engineering, KL University, Vaddeswaram, Guntur – 522502, Andhra Pradesh

Abstract

Objective: To design and implement a Zigbee Imaging system to track and detect the multi colored moving objects using Additive color model technique. Analysis: Digital image processing methods like Segmentation, background subtraction and point detectors are very popular and prominently used in the object detecting and tracking from live streaming frame sequences. These methods require high computing systems to process the data in real time. Methodology: To overcome such constraints, we implement the low cost IEEE 802.15.4 Zigbee based Image Processing System. This system can process and transmit the images efficiently even in Dynamic environment conditions. In this paper, we illustrate Zigbee Imaging system functionality at sensitive places of observation. Finding/Improvements: We implement our proposed system with a Low cost CMOS color camera and Advanced RISC processor, which are used for supporting the Zigbee imaging system in detecting and tracking the objects. The system operates at 30 fps with resolution 88x144.This system can detect and track 8 objects at a time in the camera field view and transmits the tracked information to the host system with wireless Technology 802.15.4 Zigbee. The Experimental results of Prototype system to image sequences are also figured.

Keywords

Additive Color Model, Multi Color Moving Object, Object Spying, Zigbee Imaging System.

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