560 research outputs found
Big Data Security (Volume 3)
After a short description of the key concepts of big data the book explores on the secrecy and security threats posed especially by cloud based data storage. It delivers conceptual frameworks and models along with case studies of recent technology
PriPeARL: A Framework for Privacy-Preserving Analytics and Reporting at LinkedIn
Preserving privacy of users is a key requirement of web-scale analytics and
reporting applications, and has witnessed a renewed focus in light of recent
data breaches and new regulations such as GDPR. We focus on the problem of
computing robust, reliable analytics in a privacy-preserving manner, while
satisfying product requirements. We present PriPeARL, a framework for
privacy-preserving analytics and reporting, inspired by differential privacy.
We describe the overall design and architecture, and the key modeling
components, focusing on the unique challenges associated with privacy,
coverage, utility, and consistency. We perform an experimental study in the
context of ads analytics and reporting at LinkedIn, thereby demonstrating the
tradeoffs between privacy and utility needs, and the applicability of
privacy-preserving mechanisms to real-world data. We also highlight the lessons
learned from the production deployment of our system at LinkedIn.Comment: Conference information: ACM International Conference on Information
and Knowledge Management (CIKM 2018
User's Privacy in Recommendation Systems Applying Online Social Network Data, A Survey and Taxonomy
Recommender systems have become an integral part of many social networks and
extract knowledge from a user's personal and sensitive data both explicitly,
with the user's knowledge, and implicitly. This trend has created major privacy
concerns as users are mostly unaware of what data and how much data is being
used and how securely it is used. In this context, several works have been done
to address privacy concerns for usage in online social network data and by
recommender systems. This paper surveys the main privacy concerns, measurements
and privacy-preserving techniques used in large-scale online social networks
and recommender systems. It is based on historical works on security,
privacy-preserving, statistical modeling, and datasets to provide an overview
of the technical difficulties and problems associated with privacy preserving
in online social networks.Comment: 26 pages, IET book chapter on big data recommender system
Cybersecurity applications of Blockchain technologies
With the increase in connectivity, the popularization of cloud services, and the rise
of the Internet of Things (IoT), decentralized approaches for trust management
are gaining momentum. Since blockchain technologies provide a distributed ledger,
they are receiving massive attention from the research community in different application
fields. However, this technology does not provide cybersecurity by itself.
Thus, this thesis first aims to provide a comprehensive review of techniques and
elements that have been proposed to achieve cybersecurity in blockchain-based systems.
The analysis is intended to target area researchers, cybersecurity specialists
and blockchain developers. We present a series of lessons learned as well. One of
them is the rise of Ethereum as one of the most used technologies.
Furthermore, some intrinsic characteristics of the blockchain, like permanent
availability and immutability made it interesting for other ends, namely as covert
channels and malicious purposes.
On the one hand, the use of blockchains by malwares has not been characterized
yet. Therefore, this thesis also analyzes the current state of the art in this area. One
of the lessons learned is that covert communications have received little attention.
On the other hand, although previous works have analyzed the feasibility of
covert channels in a particular blockchain technology called Bitcoin, no previous
work has explored the use of Ethereum to establish a covert channel considering all
transaction fields and smart contracts.
To foster further defence-oriented research, two novel mechanisms are presented
on this thesis. First, Zephyrus takes advantage of all Ethereum fields and smartcontract
bytecode. Second, Smart-Zephyrus is built to complement Zephyrus by
leveraging smart contracts written in Solidity. We also assess the mechanisms feasibility
and cost. Our experiments show that Zephyrus, in the best case, can embed
40 Kbits in 0.57 s. for US 1.82 per bit), the provided stealthiness might be worth the price for attackers. Furthermore,
these two mechanisms can be combined to increase capacity and reduce
costs.Debido al aumento de la conectividad, la popularización de los servicios en la nube
y el auge del Internet de las cosas (IoT), los enfoques descentralizados para la
gestión de la confianza están cobrando impulso. Dado que las tecnologÃas de cadena
de bloques (blockchain) proporcionan un archivo distribuido, están recibiendo
una atención masiva por parte de la comunidad investigadora en diferentes campos
de aplicación. Sin embargo, esta tecnologÃa no proporciona ciberseguridad por sÃ
misma. Por lo tanto, esta tesis tiene como primer objetivo proporcionar una revisión
exhaustiva de las técnicas y elementos que se han propuesto para lograr la ciberseguridad
en los sistemas basados en blockchain. Este análisis está dirigido a investigadores
del área, especialistas en ciberseguridad y desarrolladores de blockchain. A
su vez, se presentan una serie de lecciones aprendidas, siendo una de ellas el auge
de Ethereum como una de las tecnologÃas más utilizadas.
Asimismo, algunas caracterÃsticas intrÃnsecas de la blockchain, como la disponibilidad
permanente y la inmutabilidad, la hacen interesante para otros fines, concretamente
como canal encubierto y con fines maliciosos.
Por una parte, aún no se ha caracterizado el uso de la blockchain por parte
de malwares. Por ello, esta tesis también analiza el actual estado del arte en este
ámbito. Una de las lecciones aprendidas al analizar los datos es que las comunicaciones
encubiertas han recibido poca atención.
Por otro lado, aunque trabajos anteriores han analizado la viabilidad de los
canales encubiertos en una tecnologÃa blockchain concreta llamada Bitcoin, ningún
trabajo anterior ha explorado el uso de Ethereum para establecer un canal encubierto
considerando todos los campos de transacción y contratos inteligentes.
Con el objetivo de fomentar una mayor investigación orientada a la defensa,
en esta tesis se presentan dos mecanismos novedosos. En primer lugar, Zephyrus
aprovecha todos los campos de Ethereum y el bytecode de los contratos inteligentes.
En segundo lugar, Smart-Zephyrus complementa Zephyrus aprovechando los contratos inteligentes escritos en Solidity. Se evalúa, también, la viabilidad y el coste
de ambos mecanismos. Los resultados muestran que Zephyrus, en el mejor de los
casos, puede ocultar 40 Kbits en 0,57 s. por 1,64 US$, y recuperarlos en 2,8 s.
Smart-Zephyrus, por su parte, es capaz de ocultar un secreto de 4 Kb en 41 s. Si
bien es cierto que es caro (alrededor de 1,82 dólares por bit), el sigilo proporcionado
podrÃa valer la pena para los atacantes. Además, estos dos mecanismos pueden
combinarse para aumentar la capacidad y reducir los costesPrograma de Doctorado en Ciencia y TecnologÃa Informática por la Universidad Carlos III de MadridPresidente: José Manuel Estévez Tapiador.- Secretario: Jorge Blasco AlÃs.- Vocal: Luis Hernández Encina
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