88,773 research outputs found
Data trust framework using blockchain and smart contracts
Lack of trust is the main barrier preventing more widespread data sharing. The lack of transparent and reliable infrastructure for data sharing prevents many data owners from sharing their data.
Data trust is a paradigm that facilitates data sharing by forcing data controllers to be transparent about the process of sharing and reusing data.
Blockchain technology has the potential to present the essential properties for creating a practical and secure data trust framework by transforming current auditing practices and automatic enforcement of smart contracts logic without relying on intermediaries to establish trust.
Blockchain holds an enormous potential to remove the barriers of traditional centralized applications and propose a distributed and transparent administration by employing the involved parties to maintain consensus on the ledger. Furthermore, smart contracts are a programmable component that provides blockchain with more flexible and powerful capabilities. Recent advances in blockchain platforms toward smart contracts' development have revealed the possibility of implementing blockchain-based applications in various domains, such as health care, supply chain and digital identity.
This dissertation investigates the blockchain's potential to present a framework for data trust. It starts with a comprehensive study of smart contracts as the main component of blockchain for developing decentralized data trust.
Interrelated, three decentralized applications that address data sharing and access control problems in various fields, including healthcare data sharing, business process, and physical access control system, have been developed and examined.
In addition, a general-purpose application based on an attribute-based access control model is proposed that can provide trusted auditability required for data sharing and access control systems and, ultimately, a data trust framework. Besides auditing, the system presents a transparency level that both access requesters (data users) and resource owners (data controllers) can benefit from. The proposed solutions have been validated through a use case of independent digital libraries. It also provides a detailed performance analysis of the system implementation.
The performance results have been compared based on different consensus mechanisms and databases, indicating the system's high throughput and low latency.
Finally, this dissertation presents an end-to-end data trust framework based on blockchain technology.
The proposed framework promotes data trustworthiness by assessing input datasets, effectively managing access control, and presenting data provenance and activity monitoring. A trust assessment model that examines the trustworthiness of input data sets and calculates the trust value is presented.
The number of transaction validators is defined adaptively with the trust value.
This research provides solutions for both data owners and data users’ by ensuring the trustworthiness and quality of the data at origin and transparent and secure usage of the data at the end. A comprehensive experimental study indicates the presented system effectively handles a large number of transactions with low latency
Planning as Tabled Logic Programming
This paper describes Picat's planner, its implementation, and planning models
for several domains used in International Planning Competition (IPC) 2014.
Picat's planner is implemented by use of tabling. During search, every state
encountered is tabled, and tabled states are used to effectively perform
resource-bounded search. In Picat, structured data can be used to avoid
enumerating all possible permutations of objects, and term sharing is used to
avoid duplication of common state data. This paper presents several modeling
techniques through the example models, ranging from designing state
representations to facilitate data sharing and symmetry breaking, encoding
actions with operations for efficient precondition checking and state updating,
to incorporating domain knowledge and heuristics. Broadly, this paper
demonstrates the effectiveness of tabled logic programming for planning, and
argues the importance of modeling despite recent significant progress in
domain-independent PDDL planners.Comment: 27 pages in TPLP 201
Language-Based Data Sharing in Web Applications
Cloud development and virtualization of applications is crucially becoming the common
practice in the software engineering industry. Many systems and database tools are
available to support applications with many instances and views, but all the orchestration of data and functionality in the so-called multi-tenant applications comes with a high development and maintenance cost. Due to the high costs of developing and maintaining such applications, there is an increasing need for languages and tools that support the gradual development of software for a highly shared environment, at the developer and user level.
We extend a typed, reactive and incremental programming environment and language
with parameterized modules that increase application modularity, with lenses that
provide a (filtered) data sharing mechanism between modules, and the (dynamic) verification of module access conditions to implement data privacy. The combination of
these mechanisms is a safe and powerful mechanism to design and evolve cloud and web applications.
We present a pragmatic programming language supported by a deployed prototype
where several examples of applications illustrate this new programming paradigm. We
also provide a largerweb application example as a means of showing how the combination of the introduced mechanisms allows for the development of multi-tenant applications, and to compare it against implementations in modern frameworks
Adversarial Data Programming: Using GANs to Relax the Bottleneck of Curated Labeled Data
Paucity of large curated hand-labeled training data for every
domain-of-interest forms a major bottleneck in the deployment of machine
learning models in computer vision and other fields. Recent work (Data
Programming) has shown how distant supervision signals in the form of labeling
functions can be used to obtain labels for given data in near-constant time. In
this work, we present Adversarial Data Programming (ADP), which presents an
adversarial methodology to generate data as well as a curated aggregated label
has given a set of weak labeling functions. We validated our method on the
MNIST, Fashion MNIST, CIFAR 10 and SVHN datasets, and it outperformed many
state-of-the-art models. We conducted extensive experiments to study its
usefulness, as well as showed how the proposed ADP framework can be used for
transfer learning as well as multi-task learning, where data from two domains
are generated simultaneously using the framework along with the label
information. Our future work will involve understanding the theoretical
implications of this new framework from a game-theoretic perspective, as well
as explore the performance of the method on more complex datasets.Comment: CVPR 2018 main conference pape
SWISH: SWI-Prolog for Sharing
Recently, we see a new type of interfaces for programmers based on web
technology. For example, JSFiddle, IPython Notebook and R-studio. Web
technology enables cloud-based solutions, embedding in tutorial web pages,
atractive rendering of results, web-scale cooperative development, etc. This
article describes SWISH, a web front-end for Prolog. A public website exposes
SWI-Prolog using SWISH, which is used to run small Prolog programs for
demonstration, experimentation and education. We connected SWISH to the
ClioPatria semantic web toolkit, where it allows for collaborative development
of programs and queries related to a dataset as well as performing maintenance
tasks on the running server and we embedded SWISH in the Learn Prolog Now!
online Prolog book.Comment: International Workshop on User-Oriented Logic Programming (IULP
2015), co-located with the 31st International Conference on Logic Programming
(ICLP 2015), Proceedings of the International Workshop on User-Oriented Logic
Programming (IULP 2015), Editors: Stefan Ellmauthaler and Claudia Schulz,
pages 99-113, August 201
RNeXML: a package for reading and writing richly annotated phylogenetic, character, and trait data in R
NeXML is a powerful and extensible exchange standard recently proposed to
better meet the expanding needs for phylogenetic data and metadata sharing.
Here we present the RNeXML package, which provides users of the R programming
language with easy-to-use tools for reading and writing NeXML documents,
including rich metadata, in a way that interfaces seamlessly with the extensive
library of phylogenetic tools already available in the R ecosystem
Data Sharing and Access Using Aggregate Key Concept
Cloud Storage is a capacity of information online in the cloud, which is available from different and associated assets. Distributed storage can provide high availability and consistent quality, reliable assurance, debacle free restoration, and reduced expense. Distributed storage has imperative usefulness, i.e., safely, proficiently, adaptably offering information to others. Data privacy is essential in the cloud to ensure that the user’s identity is not leaked to unauthorized persons. Using the cloud, anyone can share and store the data, as much as they want. To share the data in a secure way, cryptography is very useful. By using different encryption techniques, a user can store data in the cloud. Encryption and decryption keys are created for unique data that the user provides. Only a particular set of decryption keys are shared so that the data can be decrypted. A public–key encryption system which is called a Key-Aggregate cryptosystem (KAC) is presented. This system produces constant size ciphertexts. Any arrangement of secret keys can be aggregated and make them into a single key, which has the same power of the keys that are being used. This total key can then be sent to the others for decoding of a ciphertext set and remaining encoded documents outside the set stays private. The project presented in this paper is an implementation of the proposed system
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