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10. A Novel approach as Multi-place Watermarking for Security in Database

Author

Mehta, Brijesh B. and Rao, Udai Pratap

Subjects
Computer Science - Databases, Computer Science - Cryptography and Security, Computer Science - Multimedia
Abstract

Digital multimedia watermarking technology had suggested in the last decade to embed copyright information in digital objects such as images, audio and video. However, the increasing use of relational database systems in many real-life applications created an ever-increasing need for watermarking database systems. As a result, watermarking relational database system is now emerging as a research area that deals with the legal issue of copyright protection of database systems. The main goal of database watermarking is to generate robust and impersistent watermark for database. In this paper we propose a method, based on image as watermark and this watermark is embedded over the database at two different attribute of tuple, one in the numeric attribute of tuple and another in the date attribute's time (seconds) field. Our approach can be applied for numerical and categorical database., Comment: 5 pages, 3 figures, Int'l Conf. Security and Management, SAM'11

Published
2014

11. ElGamal Homomorphic Encryption-Based Privacy Preserving Association Rule Mining on Horizontally Partitioned Healthcare Data

Author

Domadiya, Nikunj and Rao, Udai Pratap

Subjects
Coronavirus(COVID-19), General Computer Science, Breast Cancer Disease, Association Rule Mining, Original Contribution, Data Mining Privacy, Electrical and Electronic Engineering, Distributed Healthcare Data Mining
Abstract

In today’s world, life-threatening diseases have become a pre-eminent issue in healthcare due to the higher mortality rate. It is possible to lower this mortality rate by utilizing healthcare intelligence to detect diseases early. Patient’s medical data is stored in the EHR system, which is kept up to date by the healthcare provider. Data mining techniques like Association Rule Mining can detect a patient’s disease from their symptoms using digital healthcare data stored in the EHR system. Association rule mining’s efficacy can be improved by using global data from various EHR systems. It mandates that all EHR systems exchange healthcare records to a central server. When personal health information is made available on an untrusted server, several privacy laws may be violated. As a result, the challenge of privacy preserving distributed healthcare data mining has become a well-known study field in the healthcare industry. This research uses an efficient ElGamal homomorphic encryption technique to protect privacy in a distributed association rule mining. The proposed approach to discover the risk factor of most life-threatening diseases like breast cancer and heart disease with its symptoms and discuss the scope for combating COVID-19. Theoretical analysis of the proposed approach shows that it is efficient and maintains privacy in an insecure communication environment. An experimental study with a real dataset shows the proposed approach’s benefit compared to the local single EHR system results.

Published
2022

14. Assessment of Routing Attacks and Mitigation Techniques with RPL Control Messages: A Survey.

Author

BANG, ANKUR O., RAO, UDAI PRATAP, KALIYAR, PALLAVI, and CONTI, MAURO

Subjects
*WIRELESS personal area networks, *INTERNET protocol version 6, *INTERNET of things, *DATA transmission systems
Abstract

Routing Protocol for Low-Power and Lossy Networks (RPL) is a standard routing protocol for the Low Power and Lossy Networks (LLNs). It is a part of the IPv6 over Low-Power Wireless Personal Area Network (6LoWPAN) protocol stack. Features such as energy-efficient mechanisms and availability of the secure modes of operations make RPL suitable for the constrained Internet of Things (IoT) devices. Hence, the majority of IoT applications rely on RPL for data communication. However, routing security in RPL-based IoT networks is a significant concern, motivating us to study and analyze routing attacks and suggested countermeasures against them. To this end, we provide a comprehensive survey on the state-of-the-art security threats and their corresponding countermeasures in RPL-based IoT networks. Based on our study, we propose a novel classification scheme that uses a mapping between RPL attacks and their countermeasure techniques to the RPL control messages used to develop these techniques. Furthermore, we provide an in-depth statistical analysis that includes analysis of routing attacks through the RPL control messages, distribution of various mitigation techniques as per the method used, RPL control messages involved in the mitigation techniques, and details of the tools used by multiple researchers. In the end, we highlight some open challenges and future research opportunities on this topic. We believe that this survey will be beneficial to researchers and practitioners working in the area of RPL security. [ABSTRACT FROM AUTHOR]

Published
2023
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25. A Survey on Preserving Privacy for Sensitive Association Rules in Databases

Author

Modi, Chirag, Rao, Udai Pratap, Patel, Dhiren R., and The proceedings of International Conference on Recent Trends in Business Administration and Information Processing (BAIP 2010 – LNCS-CCIS)

Subjects
Association rule mining, Evaluation metrics, Privacy-preserving data mining, Frequent itemset hiding, Research areas, Statistical database, Frequent itemset
Abstract

Privacy preserving data mining (PPDM) is a novel research area to preserve privacy for sensitive knowledge from disclosure. Many of the researchers in this area have recently made effort to preserve privacy for sensitive knowledge in statistical database. In this paper, we present a detailed overview and classification of approaches which have been applied to knowledge hiding in context of association rule mining. We describe some evaluation metrics which are used to evaluate the performance of presented hiding algorithms. © 2010 Springer-Verlag Berlin Heidelberg., by Chirag Modi, Udai Pratap Rao and Dhiren R. Patel

Published
2010

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