Rajarathnam Nallusamy

Bio: Rajarathnam Nallusamy is an academic researcher from Infosys. The author has contributed to research in topics: Digital watermarking & Watermark. The author has an hindex of 8, co-authored 35 publications receiving 196 citations.

A Study of DWT and SVD Based Watermarking Algorithms for Patient Privacy in Medical Images

Abstract: Information and Communication Technologies (ICT) are being adopted widely to improve citizen's health care. Health information systems (HIS) of different hospitals exchange electronic medical records including digital medical images of patients. Medical images and accompanying reports have special requirement of protecting the privacy of the patient by not revealing personal particulars especially when they are transmitted over networks. To increase the security of medical images and preserve patients' privacy, digital watermarking has been proposed. In this paper, we study the performance of three different watermarking algorithms (DWT, SVD and DWT-SVD based watermarking algorithms). We have created two different watermarks with same watermark information but with different characteristics - one is QR Code as watermark image which is capable of carrying large information in small space, while the other one is a normal text image watermark and embedded inside medical images. We, then, have assessed the quality of watermarked images obtained after embedding the watermarks using both objective (PSNR) as well as subjective (opinions from physicians, a radiologist and a medical physicist) methods and found that watermarking has not resulted in loss of medical information. Further, we have conducted several experiments to evaluate the performance of these algorithms in terms of robustness, capacity, and embedding time. Experimental results show that DWT based method is suitable for medical applications where embedding time and imperceptibility are prime concerns while SVD based methods are suitable for medical applications where robustness and capacity are the main concerns.

Multi-user Attribute Based Searchable Encryption

Abstract: Globalized services economy is increasingly adopting cloud computing in which applications, platforms, and infrastructure are available as services. Huge volume of data including sensitive data is outsourced and stored remotely in public clouds. There is a need for efficient protection of the privacy and security of users and their data without affecting its utility to authorized users. There needs to be a trade-off between data security and availability. Multi user encryption schemes provide partial solution by encrypting data and managing keys efficiently among the users but exposing the entire data accessible to all the users. But, in certain applications, the data need to be accessed by only specified users and they shall have access to only specified parts of the data on a need to know basis. Ciphertext policy attribute based encryption supports keyword based search but require large amount of data for a single keyword thereby increasing the size and hence the cost of storage on the cloud. In this paper, we have proposed an encryption scheme which requires less storage space on the cloud but provides fine grained access control to authorized users. This is a hybrid scheme that combines the strengths of both attribute based encryption and searchable encryption.

Method, system, and computer-readable medium for detecting leakage of a video

Abstract: The present invention relates to a computer-implemented method, system and computer readable medium for detecting source of leakage of a video. The method comprises processing a video by a processing device resulting a processed video, identifying at least one responsible user for safekeeping and/or distributing and/or screening the processed video, creating a watermark wherein the watermark comprises an information about an owner of the video, the responsible user, and at least one transaction information, embedding the watermark inside the processed video resulting a watermarked video, distributing the watermarked video to at least one consumer, and identifying the responsible user by extracting the watermark from a pirated copy of the watermarked video and extracting the information contained in the watermark from the watermarked video.

Methods for embedding and extracting a watermark in a text document and devices thereof

Abstract: Method, apparatus and non-transitory computer readable medium for embedding and extracting a watermark in a text document using digital watermarking processes is disclosed. When the text document is watermarked, the following steps are performed. The pages of the text document are transformed into corresponding images. Then, the margins on each of the images are detected and cropped to generate the cropped images. The cropped images are segmented into blocks among which some blocks are selected based on content of each block. The watermark is embedded in the selected blocks using a digital watermarking process. When the watermark from the watermarked text document is extracted, the watermark-embedding process is referred to determine the block information, for selecting each block of a watermarked text document, from where the watermark needs to be extracted.

Watermarking video content using visual cryptography and scene averaged image

Abstract: With the increasing convergence of network, services, and devices, more number of end user devices are accessing digital media content which were hitherto accessible mainly from computers and television sets. This makes the digital media more prone to illegal copying and distribution. In this paper, we propose a robust digital video watermarking scheme for copyright protection using the principles of visual cryptography, scene change detection in videos, and conversion of each scene into an image by averaging the frames in the scene. In the proposed method, data is extracted and stored as one share of the watermark pattern instead of embedding data into the original video as in the conventional watermarking schemes. Since no data is embedded, the method is robust against watermark attacks aimed at detecting and destroying or distorting data embedded into videos. Simulation results show that the method is robust even in the case of 50% frame drop. All the watermarked scenes, not frames, need to be dropped for an effective attack against the watermark. Dropping of scenes makes the video less attractive for illegal copying and distribution.

Challenges and Opportunities of Big Data in Health Care: A Systematic Review.

Abstract: Background: Big data analytics offers promise in many business sectors, and health care is looking at big data to provide answers to many age-related issues, particularly dementia and chronic disease management. Objective: The purpose of this review was to summarize the challenges faced by big data analytics and the opportunities that big data opens in health care. Methods: A total of 3 searches were performed for publications between January 1, 2010 and January 1, 2016 (PubMed/MEDLINE, CINAHL, and Google Scholar), and an assessment was made on content germane to big data in health care. From the results of the searches in research databases and Google Scholar (N=28), the authors summarized content and identified 9 and 14 themes under the categories Challenges and Opportunities, respectively. We rank-ordered and analyzed the themes based on the frequency of occurrence. Results: The top challenges were issues of data structure, security, data standardization, storage and transfers, and managerial skills such as data governance. The top opportunities revealed were quality improvement, population management and health, early detection of disease, data quality, structure, and accessibility, improved decision making, and cost reduction. Conclusions: Big data analytics has the potential for positive impact and global implications; however, it must overcome some legitimate obstacles. [JMIR Med Inform 2016;4(4):e38]

Big data analytics for preventive medicine

Abstract: Medical data is one of the most rewarding and yet most complicated data to analyze. How can healthcare providers use modern data analytics tools and technologies to analyze and create value from complex data? Data analytics, with its promise to efficiently discover valuable pattern by analyzing large amount of unstructured, heterogeneous, non-standard and incomplete healthcare data. It does not only forecast but also helps in decision making and is increasingly noticed as breakthrough in ongoing advancement with the goal is to improve the quality of patient care and reduces the healthcare cost. The aim of this study is to provide a comprehensive and structured overview of extensive research on the advancement of data analytics methods for disease prevention. This review first introduces disease prevention and its challenges followed by traditional prevention methodologies. We summarize state-of-the-art data analytics algorithms used for classification of disease, clustering (unusually high incidence of a particular disease), anomalies detection (detection of disease) and association as well as their respective advantages, drawbacks and guidelines for selection of specific model followed by discussion on recent development and successful application of disease prevention methods. The article concludes with open research challenges and recommendations.

Subjective Assessment of Region of Interest-Aware Adaptive Multimedia Streaming Quality

Abstract: Adaptive multimedia streaming relies on adjusting the video content's bit-rate meet network conditions in the quest to reduce packet loss and resulting video quality degradations. Current multimedia adaptation schemes uniformly adjust the compression over the entire image area. However, research has shown that user attention is focused mostly on certain image areas, denoted areas of maximum user interest (AMUI), and their interest decreases with the increase in distance to the AMUI. The region of interest-based adaptive multimedia streaming scheme (ROIAS) is introduced to perform bit-rate adaptation to network conditions by adjusting video quality relative to the AMUI location. This paper also extends ROIAS to support multiple areas of maximum user interest within the same video frame. This paper presents the performance analysis of ROIAS in terms of the impact on user perceived video quality measured using subjective video quality assessment techniques based on human subjects. The tests use a wide range of video clips, which differ in terms of spatial and temporal complexity and region of interest location and variation. A comparative evaluation of both subjective and objective video quality test results is performed and demonstrate the benefit of using ROIAS for adaptive video quality delivery.

A Survey on Robust Video Watermarking Algorithms for Copyright Protection

Abstract: With the development and popularization of the Internet and the rise of various live broadcast platforms, digital videos have penetrated into all aspects of people’s life. At the same time, all kinds of pirated videos are also flooding the Internet, which seriously infringe the rights and interests of video copyright owners and hinder the healthy development of the video industry. Therefore, robust video watermarking algorithms for copyright protection have emerged as these times require. In this paper, we review robust video watermarking algorithms for copyright protection based on original videos and compressed videos. Basic models and properties of video watermarking algorithms are described, and the evaluation indexes corresponding to each property are also introduced. To help researchers understand various existing robust watermarking algorithms quickly, some basic information and the quantitative estimation of several performances are analyzed and compared. Finally, we discuss the challenges in the research of robust video watermarking algorithms, and give possible development directions for the future.