Preserving Trustworthiness and Confidentiality for Online Multimedia

Technology advancements in areas of mobile computing, social networks, and cloud computing have rapidly changed the way we communicate and interact. The wide adoption of media-oriented mobile devices such as smartphones and tablets enables people to capture information in various media formats, and offers them a rich platform for media consumption. The proliferation of online services and social networks makes it possible to store personal multimedia collection online and share them with family and friends anytime anywhere. Considering the increasing impact of digital multimedia and the trend of cloud computing, this dissertation explores the problem of how to evaluate trustworthiness and preserve confidentiality of online multimedia data. The dissertation consists of two parts. The first part examines the problem of evaluating trustworthiness of multimedia data distributed online. Given the digital nature of multimedia data, editing and tampering of the multimedia content becomes very easy. Therefore, it is important to analyze and reveal the processing history of a multimedia document in order to evaluate its trustworthiness. We propose a new forensic technique called ``Forensic Hash", which draws synergy between two related research areas of image hashing and non-reference multimedia forensics. A forensic hash is a compact signature capturing important information from the original multimedia document to assist forensic analysis and reveal processing history of a multimedia document under question. Our proposed technique is shown to have the advantage of being compact and offering efficient and accurate analysis to forensic questions that cannot be easily answered by convention forensic techniques. The answers that we obtain from the forensic hash provide valuable information on the trustworthiness of online multimedia data. The second part of this dissertation addresses the confidentiality issue of multimedia data stored with online services. The emerging cloud computing paradigm makes it attractive to store private multimedia data online for easy access and sharing. However, the potential of cloud services cannot be fully reached unless the issue of how to preserve confidentiality of sensitive data stored in the cloud is addressed. In this dissertation, we explore techniques that enable confidentiality-preserving search of encrypted multimedia, which can play a critical role in secure online multimedia services. Techniques from image processing, information retrieval, and cryptography are jointly and strategically applied to allow efficient rank-ordered search over encrypted multimedia database and at the same time preserve data confidentiality against malicious intruders and service providers. We demonstrate high efficiency and accuracy of the proposed techniques and provide a quantitative comparative study with conventional techniques based on heavy-weight cryptography primitives

A Review of Hashing based Image Copy Detection Techniques

Images are considered to be natural carriers of information, and a large number of images are created, exchanged and are made available online. Apart from creating new images, the availability of number of duplicate copies of images is a critical problem. Hashing based image copy detection techniques are a promising alternative to address this problem. In this approach, a hash is constructed by using a set of unique features extracted from the image for identification. This article provides a comprehensive review of the state-of-the-art image hashing techniques. The reviewed techniques are categorized by the mechanism used and compared across a set of functional & performance parameters. The article finally highlights the current issues faced by such systems and possible future directions to motivate further research work

Recent Advances in Digital Image and Video Forensics, Anti-forensics and Counter Anti-forensics

Image and video forensics have recently gained increasing attention due to the proliferation of manipulated images and videos, especially on social media platforms, such as Twitter and Instagram, which spread disinformation and fake news. This survey explores image and video identification and forgery detection covering both manipulated digital media and generative media. However, media forgery detection techniques are susceptible to anti-forensics; on the other hand, such anti-forensics techniques can themselves be detected. We therefore further cover both anti-forensics and counter anti-forensics techniques in image and video. Finally, we conclude this survey by highlighting some open problems in this domain

A Novel System for Confidential Medical Data Storage Using Chaskey Encryption and Blockchain Technology

يعد التخزين الآمن للمعلومات الطبية السرية أمرًا بالغ الأهمية لمنظمات الرعاية الصحية التي تسعى إلى حماية خصوصية المريض والامتثال للمتطلبات التنظيمية. في هذا البحث، نقدم نظامًا جديدًا للتخزين الآمن للبيانات الطبية باستخدام تقنية تشفير Chaskey و blockchain. يستخدم النظام تشفير Chaskey لضمان سرية وسلامة البيانات الطبية، وتكنولوجيا blockchain لتوفير حلول تخزين البيانات الطبية بحيث يكون قابل للتطوير ويتميز باللامركزية. يستخدم النظام أيضًا تقنيات Bflow للتجزئة ومنها التجزئة الرأسية لتعزيز قابلية التوسع وإدارة البيانات المخزنة. بالإضافة إلى ذلك، يستخدم النظام العقود الذكية لفرض سياسات التحكم في الوصول والتدابير الأمنية الأخرى. سنقدم وصف للنظام المقترح بالتفصيل ونقدم تحليلاً لخصائصه الأمنية والأداء. تظهر نتائجنا أن النظام يوفر حلاً آمنًا للغاية وقابل للتطوير لتخزين البيانات الطبية السرية، مع تطبيقات محتملة في مجموعة واسعة من إعدادات الرعاية الصحية.Secure storage of confidential medical information is critical to healthcare organizations seeking to protect patient's privacy and comply with regulatory requirements. This paper presents a new scheme for secure storage of medical data using Chaskey cryptography and blockchain technology. The system uses Chaskey encryption to ensure integrity and confidentiality of medical data, blockchain technology to provide a scalable and decentralized storage solution. The system also uses Bflow segmentation and vertical segmentation technologies to enhance scalability and manage the stored data. In addition, the system uses smart contracts to enforce access control policies and other security measures. The description of the system detailing and provide an analysis of its security and performance characteristics. The resulting images were tested against a number of important metrics such as Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), bit error rate (BER), Signal-to-Noise Ratio (SNR), Normalization Correlation (NC) and Structural Similarity Index (SSIM). Our results showing that the system provides a highly secure and scalable solution for storing confidential medical data, with potential applications in a wide range of healthcare settings

Active and passive approaches for image authentication

Ph.DDOCTOR OF PHILOSOPH