Security algorithms like RSA are becoming increasingly important for communications to provide companies, organizations, and users around the world, secure applications who rely heavily on them in their daily work. Security algorithms use different acquaintances among companies which might belong to various countries or even cities. Such data should essentially be encrypted to make sure that there is security in transportation. Thus, the current research paper leads to the novel system of security for the safe transfer of data. This paper examines the general principles of encryption and focuses on the development of RSA and the complexity of the encryption key so that it becomes more secure in the applications used. In this project, we will work on the RSA algorithm by adding some complexity to the 3keys (3k). This addition will increase the security and complexity of the algorithm's speed while maintaining encryption and decryption time. The paper also presents an approach by means of public key encryption to enhance cryptographic security. Moreover, double security is provided by the algorithm of RSA. This novel RSA algorithm was investigated in MATLAB. Numerical results for the various parameters such as Mean Square Error (MSE), correlation and Bit Error Ratio (BER) were implemented for the encryption of the message. The experimental results demonstrated that the proposed algorithm for 3 keys has small error rate in the retrieval of the encoded text.

Modified RSA-based algorithm: a double secure approach

An important task of a teacher is to make every student learn and pass the end examination. For this, teachers make lesson plans for year/semester according to number of working days with a goal to complete syllabus prior to final examination. The lesson plans are made without knowledge of the class attendance for any particular day, since it is hard for a teacher to make a correct guess. Therefore, when class strength is unexpectedly low on a given day, the teacher can either postpone the lecture to next day or continue and let the absent students be at loss. Postponing the lecture will not complete the syllabus on expected time and letting students be at loss is also not a solution. This paper will discuss the solution to this problem by using a Machine Learning Model which is trained with past records of attendance of students to find a pattern of class attendance and predict accurate class strength for any future date according to which the lesson plans can be made or modified. Teachers having prior knowledge of class strength will help them to act accordingly to achieve their goals.

Enhancement in Teaching Quality Methodology by Predicting Attendance Using Machine Learning Technique

The cloud computing has become an emerging issue in IT industry as well as in academics due to its variant advantages. Cloud computing consist of many computing possessions like memory, storage and processor which are not physically available at the user’s site. These devices are stored outside and controlled by the cloud service providers, there is always a risk of losing data or the data may be altered by internal as well as external attackers. However, it may not be fully trustworthy because the user does not have copy of all stored data which refer to the fact that while users can put their files into the cloud server, nobody knows that where exactly they should be. Further, it poses various security challenges as generating secure and reliable data storage over unreliable cloud service provider. The data integrity is one of the prime concern in cloud computing. This paper presents a framework for data integrity in cloud computing using tamper-proofing algorithms (TPA) such as tamper-proof checking code (TPC) and tamper- resistance (TPR).

On Security and Data Integrity Framework for Cloud Computing Using Tamper-Proofing

Osteoporosis is a disease which has affected major part of human body that is bones. It trends to reduce the mass of the bones and hence degrade the micro architecture of tissues of bones. There are multiple imaging technologies which have been used from the decades in diagnosis and the micro architecture of distressed as well as affected bones in order to find the bone density deficiency. Image processing methods are widely used like filtering, segmentation, classification, image enhancement as well as other pre-processing technique to diagnosis the affected bone structure easily. It will help to extract the vital information about deformed micro architecture pattern. In this paper we have collected the basic information of tissues such as osteoblast as well as osteoclast and also have presented a comparative study of various diagnosis technique based on the image processing for the osteoporosis. The main aim of this work is to assess the prevalence of osteoporosis and changes in bone mass with increasing age, compare bone health status of apparently healthy men, premenopausal and postmenopausal women. In this work, we have used ethical database of 260 subject 130 men, 80 women (premenopausal) and 50 women (postmenopausal). Bone mineral density (BMD) has been measured through dual energy X-ray absorptiometry at femoral neck.

On Classification of BMD Images Using Machine Learning (ANN) Algorithm

The main emphases on any object based tracking with vision algorithms are parametric state space based algorithms like a Bayesian filter and its family of algorithms or nonparametric algorithms like Mean Shift algorithms which are color sensitive. In this paper, We have considered vision based algorithm with Bayesian filter algorithms. We have seen more of the state space tracking algorithms uses point based object tracking approaches in which researchers did very well in the last decades, with the advent of faster computing devices available the tracking algorithm have improved a lot with extended object tracking where the object is tracked as an entire object instead of the point-based approaches. The proposed system of the algorithm is providing good results in terms of state estimation over its point based approach. So using this vision algorithm the complete object can be tracked using sensor system and this is the novelty of paper.

Improvement in Extended Object Tracking with the Vision-Based Algorithm

Recently, the electronic heath record (EHR) has become the chosen method to maintain a patient's health information. The advancement of cloud computing enables users to access their data with flexibility, providing large storage capability at low costs, which encourages EHR maintainers to consider shifting from their own storage to the cloud. In cloud computing, it is no doubt that securing EHRs poses a gigantic challenge. Various security properties like access control, data privacy, and scalable access between different clouds needs to be satisfied. This article presents a secure and efficient blueprint for securing data confidentiality on cloud computing storage. The proposed framework is carried out for EHR confidential data on cloud storage. Moreover, the proposed approach combines the obfuscation and RSA encryption together to enforce confidentiality and authentication. Through this framework, the data confidentiality and authentication scheme on EHR information can be enforced on clouds storage.

Surender Kumar Sharma

Papers

Enhanced Security for Electronic Health Care Information Using Obfuscation and RSA Algorithm in Cloud Computing