Trusted Cloud Computing with Secure Resources and Data Coloring
TL;DR: The authors suggest using a trust-overlay network over multiple data centers to implement a reputation system for establishing trust between service providers and data owners.
Abstract: Trust and security have prevented businesses from fully accepting cloud platforms. To protect clouds, providers must first secure virtualized data center resources, uphold user privacy, and preserve data integrity. The authors suggest using a trust-overlay network over multiple data centers to implement a reputation system for establishing trust between service providers and data owners. Data coloring and software watermarking techniques protect shared data objects and massively distributed software modules. These techniques safeguard multi-way authentications, enable single sign-on in the cloud, and tighten access control for sensitive data in both public and private clouds.
Citations
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TL;DR: This paper proposes a novel method by reserving room before encryption with a traditional RDH algorithm, and thus it is easy for the data hider to reversibly embed data in the encrypted image.
Abstract: Recently, more and more attention is paid to reversible data hiding (RDH) in encrypted images, since it maintains the excellent property that the original cover can be losslessly recovered after embedded data is extracted while protecting the image content's confidentiality. All previous methods embed data by reversibly vacating room from the encrypted images, which may be subject to some errors on data extraction and/or image restoration. In this paper, we propose a novel method by reserving room before encryption with a traditional RDH algorithm, and thus it is easy for the data hider to reversibly embed data in the encrypted image. The proposed method can achieve real reversibility, that is, data extraction and image recovery are free of any error. Experiments show that this novel method can embed more than 10 times as large payloads for the same image quality as the previous methods, such as for PSNR=40 dB.
610Â citations
Cites background from "Trusted Cloud Computing with Secure..."
...Digital Object Identifier 10.1109/TIFS.2013.2248725 the equivalence between data compression and RDH for binary covers....
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TL;DR: In this paper, the various RDH algorithms and researches have been classified into the following six categories: 1) RDH into image spatial domain; 2) RD h into image compressed domain (e.g., JPEG); 3) RDh suitable for image semi-fragile authentication; 4)RDH with image contrast enhancement; 5) RD H into encrypted images, which is expected to have wide application in the cloud computation; and 6) RDD into video and into audio.
Abstract: In the past two decades, reversible data hiding (RDH), also referred to as lossless or invertible data hiding, has gradually become a very active research area in the field of data hiding. This has been verified by more and more papers on increasingly wide-spread subjects in the field of RDH research that have been published these days. In this paper, the various RDH algorithms and researches have been classified into the following six categories: 1) RDH into image spatial domain; 2) RDH into image compressed domain (e.g., JPEG); 3) RDH suitable for image semi-fragile authentication; 4) RDH with image contrast enhancement; 5) RDH into encrypted images, which is expected to have wide application in the cloud computation; and 6) RDH into video and into audio. For each of these six categories, the history of technical developments, the current state of the arts, and the possible future researches are presented and discussed. It is expected that the RDH technology and its applications in the real word will continue to move ahead.
432Â citations
Cites background from "Trusted Cloud Computing with Secure..."
...ing [11], [12], vector map recovery in CAD (computer-aided design) engineering graphics [13], [14], and data coloring in the cloud [15], etc....
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TL;DR: A novel reversible data hiding technique in encrypted images where some pixels are estimated before encryption so that additional data can be embedded in the estimating errors and the data extraction and image recovery are free of errors.
345Â citations
Cites background or methods from "Trusted Cloud Computing with Secure..."
...Nowadays with the increasing demand of privacy protection, the ability to embed information in encrypted data will be useful in cloud computing [18]....
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...Into the encrypted images, the cloud server embedded some notation, including the identities of the images' owner and the cloud server and time stamps, to manage the encrypted images, as proposed in [18]....
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TL;DR: Experimental results show that the proposed RDH method outperforms the conventional PEE and its miscellaneous extensions including both one- or two-dimensional PEH-based ones.
Abstract: Prediction-error expansion (PEE) is the most successful reversible data hiding (RDH) technique, and existing PEE-based RDH methods are mainly based on the modification of one- or two-dimensional prediction-error histogram (PEH). The two-dimensional PEH-based methods perform generally better than those based on one-dimensional PEH; however, their performance is still unsatisfactory since the PEH modification manner is fixed and independent of image content. In this paper, we propose a new RDH method based on PEE for multiple histograms. Unlike the previous methods, we consider in this paper a sequence of histograms and devise a new embedding mechanism based on multiple histograms modification (MHM). A complexity measurement is computed for each pixel according to its context, and the pixels with a given complexity are collected together to generate a PEH. By varying the complexity to cover the whole image, a sequence of histograms can be generated. Then, two expansion bins are selected in each generated histogram and data embedding is realized based on MHM. Here, the expansion bins are adaptively selected considering the image content such that the embedding distortion is minimized. With such selected expansion bins, the proposed MHM-based RDH method works well. Experimental results show that the proposed method outperforms the conventional PEE and its miscellaneous extensions including both one- or two-dimensional PEH-based ones.
307Â citations
Book•
31 Oct 2011
TL;DR: This book will teach you how to create high-performance, scalable, reliable systems, providing comprehensive coverage of distributed and cloud computing, including: Facilitating management, debugging, migration, and disaster recovery through virtualization
Abstract: From the leading minds in the field, Distributed and Cloud Computing is the first modern, up-to-date distributed systems textbook Starting with an overview of modern distributed models, the book exposes the design principles, systems architecture, and innovative applications of parallel, distributed, and cloud computing systems It will teach you how to create high-performance, scalable, reliable systems, providing comprehensive coverage of distributed and cloud computing, including: Facilitating management, debugging, migration, and disaster recovery through virtualization Clustered systems for research or ecommerce applications Designing systems as web services Social networking systems using peer-to-peer computing Principles of cloud computing using examples from open-source and commercial applications Using examples from open-source and commercial vendors, the text describes cloud-based systems for research, e-commerce, social networking and more Complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing Includes case studies from the leading distributed computing vendors: Amazon, Microsoft, Google, and more Designed to meet the needs of students taking a distributed systems course, each chapter includes exercises and further reading, with lecture slides and solutions available online
307Â citations
Cites background or methods from "Trusted Cloud Computing with Secure..."
...5 Five Major Cloud Platforms and Their Service Offerings [36]...
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...For virtual storage, readers are referred to the literature [27,36,43,48,76,79]....
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...Multicore CPUs and many-core GPU processors were discussed in [15,32,36]....
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...To support trusted cloud services, Hwang and Li [36] have suggested building a trust overlay network to model trust relationships among data-center modules....
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...(Courtesy of Hwang and Li [36] ) 250 CHAPTER 4 Cloud Platform Architecture over Virtualized Data Centers...
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References
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02 May 2005
TL;DR: The design options for migrating OSes running services with liveness constraints are considered, the concept of writable working set is introduced, and the design, implementation and evaluation of high-performance OS migration built on top of the Xen VMM are presented.
Abstract: Migrating operating system instances across distinct physical hosts is a useful tool for administrators of data centers and clusters: It allows a clean separation between hard-ware and software, and facilitates fault management, load balancing, and low-level system maintenance.By carrying out the majority of migration while OSes continue to run, we achieve impressive performance with minimal service downtimes; we demonstrate the migration of entire OS instances on a commodity cluster, recording service downtimes as low as 60ms. We show that that our performance is sufficient to make live migration a practical tool even for servers running interactive loads.In this paper we consider the design options for migrating OSes running services with liveness constraints, focusing on data center and cluster environments. We introduce and analyze the concept of writable working set, and present the design, implementation and evaluation of high-performance OS migration built on top of the Xen VMM.
3,186Â citations
TL;DR: PeerTrust is presented - a reputation-based trust supporting framework, which includes a coherent adaptive trust model for quantifying and comparing the trustworthiness of peers based on a transaction-based feedback system, and a decentralized implementation of such a model over a structured P2P network.
Abstract: Peer-to-peer (P2P) online communities are commonly perceived as an environment offering both opportunities and threats. One way to minimize threats in such communities is to use community-based reputations to help estimate the trustworthiness of peers. We present PeerTrust - a reputation-based trust supporting framework, which includes a coherent adaptive trust model for quantifying and comparing the trustworthiness of peers based on a transaction-based feedback system, and a decentralized implementation of such a model over a structured P2P network. PeerTrust model has two main features. First, we introduce three basic trust parameters and two adaptive factors in computing trustworthiness of peers, namely, feedback a peer receives from other peers, the total number of transactions a peer performs, the credibility of the feedback sources, transaction context factor, and the community context factor. Second, we define a general trust metric to combine these parameters. Other contributions of the paper include strategies used for implementing the trust model in a decentralized P2P environment, evaluation mechanisms to validate the effectiveness and cost of PeerTrust model, and a set of experiments that show the feasibility and benefit of our approach.
1,847Â citations
TL;DR: Three types of attack on the intellectual property contained in software and three corresponding technical defenses are identified, including obfuscation, watermarking, and tamper-proofing.
Abstract: We identify three types of attack on the intellectual property contained in software and three corresponding technical defenses. A defense against reverse engineering is obfuscation, a process that renders software unintelligible but still functional. A defense against software piracy is watermarking, a process that makes it possible to determine the origin of software. A defense against tampering is tamper-proofing, so that unauthorized modifications to software (for example, to remove a watermark) will result in nonfunctional code. We briefly survey the available technology for each type of defense.
803Â citations
TL;DR: A new fair scheduling technique, called OCGRR (output controlled grant-based round robin), for the support of DiffServ traffic in a core router, which reduces the intertransmission time from the same stream and achieves a smaller jitter and startup latency.
Abstract: Peer-to-Peer (P2P) reputation systems are essential to evaluate the trustworthiness of participating peers and to combat the selfish, dishonest, and malicious peer behaviors. The system collects locally-generated peer feedbacks and aggregates them to yield the global reputation scores. Surprisingly, most previous work ignored the distribution of peer feedbacks. We use a trust overlay network (TON) to model the trust relationships among peers. After examining the eBay transaction trace of over 10,000 users, we discover a power-law distribution in user feedbacks. Our mathematical analysis justifies that power-law distribution is applicable to any dynamically growing P2P systems, either structured or unstructured. We develop a robust and scalable P2P reputation system, PowerTrust, to leverage the power-law feedback characteristics. The PowerTrust system dynamically selects small number of power nodes that are most reputable using a distributed ranking mechanism. By using a look-ahead random walk strategy and leveraging the power nodes, PowerTrust significantly improves in global reputation accuracy and aggregation speed. PowerTrust is adaptable to dynamics in peer joining and leaving and robust to disturbance by malicious peers. Through P2P network simulation experiments, we find significant performance gains in using PowerTrust. This power-law guided reputation system design proves to achieve high query success rate in P2P file-sharing applications. The system also reduces the total job makespan and failure rate in large-scale, parameter-sweeping P2P Grid applications.
759Â citations
Book•
27 Sep 2007TL;DR: This book develops a framework that shows how uncertainty in AI expands and generalizes traditional AI, and describes the cloud model, its uncertainties of randomness and fuzziness, and the correlation between them.
Abstract: The information deluge currently assaulting us in the 21st century is having a profound impact on our lifestyles and how we work. We must constantly separate trustworthy and required information from the massive amount of data we encounter each day. Through mathematical theories, models, and experimental computations, Artificial Intelligence with Uncertainty explores the uncertainties of knowledge and intelligence that occur during the cognitive processes of human beings. The authors focus on the importance of natural language-the carrier of knowledge and intelligence-for artificial intelligence (AI) study. This book develops a framework that shows how uncertainty in AI expands and generalizes traditional AI. It describes the cloud model, its uncertainties of randomness and fuzziness, and the correlation between them. The book also centers on other physical methods for data mining, such as the data field and knowledge discovery state space. In addition, it presents an inverted pendulum example to discuss reasoning and control with uncertain knowledge as well as provides a cognitive physics model to visualize human thinking with hierarchy. With in-depth discussions on the fundamentals, methodologies, and uncertainties in AI, this book explains and simulates human thinking, leading to a better understanding of cognitive processes.
662Â citations