Survey on relational database watermarking techniques

Digital watermarking has been in multimedia data use over the past years. Recently it has become applicable in relational database system not only to secure copyright ownership but also to ensure data contents integrity. Further, it is used in locating tampered and modified places. However, the watermarking relational database has its own requirements, challenges, attacks and limitations. This paper, surveys recent database watermarking techniques focusing on the importance of watermarking relational database, the difference between watermarking relational database and multimedia objects, the issues in watermarking relational database, type of attacks on watermarked database, classifications, distortion introduced and the embedded information. The comparative study shows that watermarking relational database can be an effective tool for copyright protection, tampered detection, and hacker tracing while maintaining the integrity of data contents. In addition, this study explores the current issues in watermarking relational database as well as the significant differences between watermarking multimedia data and relational database contents. Finally, it provides a classification of database watermarking techniques according to the way of selecting the candidate key attributes and tuples, distortion introduced and decoding methods used

Design and Analysis of an Intelligent Integrity Checking Watermarking Scheme for Ubiquitous Database Access

As a result of the highly distributed nature of ubiquitous database accessing, it is essential to develop security mechanisms that lend themselves well to the delicate properties of outsourcing databases integrity and copyright protection. Researchers have begun to study how watermarking computing can make ubiquitous databases accessing more confident work environments. One area where database context may help is in supporting content integrity. Initially, most of the research effort in this field was depending on distortion based watermark while the few remaining studies concentrated on distortion-free. But there are many disadvantages in previous studies; most notably some rely on adding watermark as an extra attributes or tuples, which increase the size of the database. Other techniques such as permutation and abstract interpretation framework require much effort to verify the watermark. The idea of this research is to adapt an optimized distortion free watermarking based on fake tuples that are embedded into a separate file not within the database to validate the content integrity for ubiquitous database accessing. The proposed system utilizes the GA, which boils down its role to create the values of the fake tuples as watermark to be the closest to real values. So that it's very hard to any attacker to guess the watermark. The proposed technique achieves more imperceptibility and security. Experimental outcomes confirm that the proposed algorithm is feasible, effective and robust against a large number of attacks

Digital Identity and the Blockchain: Universal Identity Management and the Concept of the “Self-Sovereign” Individual

While “classical” human identity has kept philosophers busy since millennia, “Digital Identity” seems primarily machine related. Telephone numbers, E-Mail inboxes, or Internet Protocol (IP)-addresses are irrelevant to define us as human beings at first glance. However, with the omnipresence of digital space the digital aspects of identity gain importance. In this submission, we aim to put recent developments in context and provide a categorization to frame the landscape as developments proceed rapidly. First, we present selected philosophical perspectives on identity. Secondly, we explore how the legal landscape is approaching identity from a traditional dogmatic perspective both in national and international law. After blending the insights from those sections together in a third step, we will go on to describe and discuss current developments that are driven by the emergence of new tools such as “Distributed Ledger Technology” and “Zero Knowledge Proof.” One of our main findings is that the management of digital identity is transforming from a purpose driven necessity toward a self-standing activity that becomes a resource for many digital applications. In other words, whereas traditionally identity is addressed in a predominantly sectoral fashion whenever necessary, new technologies transform digital identity management into a basic infrastructural service, sometimes even a commodity. This coincides with a trend to take the “control” over identity away from governmental institutions and corporate actors to “self-sovereign individuals,” who have now the opportunity to manage their digital self autonomously. To make our conceptual statements more relevant, we present several already existing use cases in the public and private sector. Subsequently, we discuss potential risks that should be mitigated in order to create a desirable relationship between the individual, public institutions, and the private sector in a world where self-sovereign identity management has become the norm. We will illustrate these issues along the discussion around privacy, as well as the development of backup mechanisms for digital identities. Despite the undeniable potential for the management of identity, we suggest that particularly at this point in time there is a clear need to make detailed (non-technological) governance decisions impacting the general design and implementation of self-sovereign identity systems

A Survey on ChatGPT: AI-Generated Contents, Challenges, and Solutions

With the widespread use of large artificial intelligence (AI) models such as ChatGPT, AI-generated content (AIGC) has garnered increasing attention and is leading a paradigm shift in content creation and knowledge representation. AIGC uses generative large AI algorithms to assist or replace humans in creating massive, high-quality, and human-like content at a faster pace and lower cost, based on user-provided prompts. Despite the recent significant progress in AIGC, security, privacy, ethical, and legal challenges still need to be addressed. This paper presents an in-depth survey of working principles, security and privacy threats, state-of-the-art solutions, and future challenges of the AIGC paradigm. Specifically, we first explore the enabling technologies, general architecture of AIGC, and discuss its working modes and key characteristics. Then, we investigate the taxonomy of security and privacy threats to AIGC and highlight the ethical and societal implications of GPT and AIGC technologies. Furthermore, we review the state-of-the-art AIGC watermarking approaches for regulatable AIGC paradigms regarding the AIGC model and its produced content. Finally, we identify future challenges and open research directions related to AIGC.Comment: 20 pages, 6 figures, 4 table

Active data-centric framework for data protection in cloud environment

Cloud computing is an emerging evolutionary computing model that provides highly scalable services over highspeed Internet on a pay-as-usage model. However, cloud-based solutions still have not been widely deployed in some sensitive areas, such as banking and healthcare. The lack of widespread development is related to users&rsquo; concern that their confidential data or privacy would leak out in the cloud&rsquo;s outsourced environment. To address this problem, we propose a novel active data-centric framework to ultimately improve the transparency and accountability of actual usage of the users&rsquo; data in cloud. Our data-centric framework emphasizes &ldquo;active&rdquo; feature which packages the raw data with active properties that enforce data usage with active defending and protection capability. To achieve the active scheme, we devise the Triggerable Data File Structure (TDFS). Moreover, we employ the zero-knowledge proof scheme to verify the request&rsquo;s identification without revealing any vital information. Our experimental outcomes demonstrate the efficiency, dependability, and scalability of our framework.<br /