Volume 9, Issue 1, January 2018

Multilayered Cloud Security Model Using Multifactor Session-Long Biometrics Access Control

Karthika Venkatraman and Jihad Qaddour

Department of Information Technology, Illinois State University, Normal, United States of America

Abstract - Cloud computing has tremendously simplified the software industry by enabling companies to offer software, infrastructure and platforms as services with the advantages of maintenance, availability, provisioning time and scalability. As individuals and firms increasingly rely on cloud-based systems to process sensitive data and intellectual property, the security risks surrounding cloud technology have increased by proportion. This paper investigates the vulnerabilities surrounding single point authentication, replay attacks and predictability. Then proposed a multilayered security model using multifactor biometrics authentication for access control. Additional features in the proposed model are to use diverse biometric templates in a randomized way, use strong algorithms for replay protection, session-long authentication with fine-grained biometrics and template updation in database after every successful authentication. Furthermore, the proposed solution approaches security as an ongoing mechanism and extends authentication service to the entire session, as opposed to traditional approaches that offer authentication only at the beginning of a session.

Index Terms - - Cloud Security, Multilayer Security Model, Identity Management, Multifactor Biometrics Authentications, Session-Long-Authentication, Fine-Grained Replay and Fine-Grained Multi-Factor Authentication

Link Prediction in Social Networks Using Fuzzy-based SVM

Pages: 8-13 (6) | [Full Text] PDF (567K)

Sara Esmaeillou, Ali Soleimani and Ramin Karimi

Islamic Azad University, Malard, Tehran, Iran

Abstract - Link prediction can be used in many cases, for instance, detecting and identifying convicts and criminals, which requires high accuracy and fault cost in this context is very high Thus prediction might increase probability of detecting such groups. Researches in the context of link prediction in social networks have mostly focused on conventional methods which are based on indices. In this paper, link prediction using SVM and Fuzzy is proposed. In the proposed method, Fuzzy and support vector machine are used simultaneously. Main idea of the proposed method is to classify samples using SVM and fuzzy membership functions each sample which has the highest matching regarding membership functions of each class belongs to that class. Sample fracture curves are obtained from SVM algorithm and then this curve is used in membership functions of Fuzzy algorithm.

Index Terms - Social Networks, Link Prediction and FSVM

Implementation of SMART Hospital System Using PPSPC and IoT Devices

Pages: 14-19 (5) | [Full Text] PDF (464K)

R. Narayanan, V. Balaji Sharath Kumar, C. Hemnath and T. Shantha Kumar

Department of CSE, Alpha College of Engineering, Chennai, Tamilnadu, India

Abstract - This paper identifying records that produces compatible results using Fast Clustering Selection Algorithm. A selection algorithm may be evaluated from both the efficiency and effectiveness points of view. While the efficiency concerns the time required to find a record, the effectiveness is related to the quality of the record. The selection algorithm fetches the result with the help of register number. The Selection algorithm works in two steps. In the first step, the register number fetches the result from the server. The record for every individual will be obtained by hit method. The sender sends the request to the server. In the second step, the most representative record that is strongly related to target classes is fetched from database. The record fetches from the database by the register number. The string generation algorithm is guaranteed to generate the optimal result k candidates. We analyses the results of students using Selection Algorithm. We need to define compatible operation analogs by introducing max-min operation & min-max operation. It automatically collects data from the web to enrich the result. The analysis of result for huge students make more time. The accuracy of the result has to be considered. We need to fetch the result individually by their register number. It leads to time inefficiency. In a proposed system, we obtain the result for a group of students. The Selection method fetches the result for a student according to their register number which is entered in between a range. The result for the student automatically fetched from the server. Once the result for the candidate has been fetched from the server, it stored in the client database. Then we sort the result of the student as group. It increases the accuracy and makes the efficient one. It reduces the burden of the people who analyze the result. The result analysis is performed within a short period. We can generate the report based on the GRADE system. Our experimental evaluation shows that our approach generates superior results. Extensive experiments on large real data sets demonstrate the efficiency and effectiveness. Finally we sort the results of students using FAST CLUSTERING SELECTION algorithm.

Index Terms - FAST, Minmax and Maxmin Operation

Insufficiency of Activity Diagram for Modeling Business Processes

Pages: - (-) | [Full Text] PDF (576K)

Mohammed Hamouda Karboos Hamid and Abd elgaffar Hamid Ahmed

Sudan University of Science and Technology, College of graduate Studies, Khartoum, Sudan
Sudan University of Science and Technology, Faculty of Computer Science and Information Technology, Khartoum, Sudan

Abstract - It is important to note that, a good description of system behavior help in elicitation of system requirements which will result into development of coherent system. Some studies declared that step of requirement capturing is significant and yet the most difficult and the least formalized one [1]. Nowadays systems became large and complex, therefor organizations need for mechanisms to help them in describing their systems business processes. Such mechanisms should be understandable by both business experts and software modelers to communicate. UML AD is using to model business process [22]. There are several modelers speaking UML, but few are known business process models [22]. So, opportunity given by UML activity diagram will save cost rather than impose them to learn new modeling language. Furthermore, relationship between UML activity models and business process models were not well covered in literature. This study has revealed some limitations of UML AD and pointed out to approach to extend UML so as to make an enhanced behavioral modelling language.

Index Terms - Business Process Modeling, Business Process Model and Notation (BPMN), Unified Modeling Language (UML), Activity Diagram (AD) and Business Modeling Languages

Volume 9, Issue 1, January 2018

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