38,238 research outputs found
All liaisons are dangerous when all your friends are known to us
Online Social Networks (OSNs) are used by millions of users worldwide.
Academically speaking, there is little doubt about the usefulness of
demographic studies conducted on OSNs and, hence, methods to label unknown
users from small labeled samples are very useful. However, from the general
public point of view, this can be a serious privacy concern. Thus, both topics
are tackled in this paper: First, a new algorithm to perform user profiling in
social networks is described, and its performance is reported and discussed.
Secondly, the experiments --conducted on information usually considered
sensitive-- reveal that by just publicizing one's contacts privacy is at risk
and, thus, measures to minimize privacy leaks due to social graph data mining
are outlined.Comment: 10 pages, 5 table
From Social Data Mining to Forecasting Socio-Economic Crisis
Socio-economic data mining has a great potential in terms of gaining a better
understanding of problems that our economy and society are facing, such as
financial instability, shortages of resources, or conflicts. Without
large-scale data mining, progress in these areas seems hard or impossible.
Therefore, a suitable, distributed data mining infrastructure and research
centers should be built in Europe. It also appears appropriate to build a
network of Crisis Observatories. They can be imagined as laboratories devoted
to the gathering and processing of enormous volumes of data on both natural
systems such as the Earth and its ecosystem, as well as on human
techno-socio-economic systems, so as to gain early warnings of impending
events. Reality mining provides the chance to adapt more quickly and more
accurately to changing situations. Further opportunities arise by individually
customized services, which however should be provided in a privacy-respecting
way. This requires the development of novel ICT (such as a self- organizing
Web), but most likely new legal regulations and suitable institutions as well.
As long as such regulations are lacking on a world-wide scale, it is in the
public interest that scientists explore what can be done with the huge data
available. Big data do have the potential to change or even threaten democratic
societies. The same applies to sudden and large-scale failures of ICT systems.
Therefore, dealing with data must be done with a large degree of responsibility
and care. Self-interests of individuals, companies or institutions have limits,
where the public interest is affected, and public interest is not a sufficient
justification to violate human rights of individuals. Privacy is a high good,
as confidentiality is, and damaging it would have serious side effects for
society.Comment: 65 pages, 1 figure, Visioneer White Paper, see
http://www.visioneer.ethz.c
An Analysis and Enumeration of the Blockchain and Future Implications
The blockchain is a relatively new technology that has grown in interest and potential research since its inception. Blockchain technology is dominated by cryptocurrency in terms of usage. Research conducted in the past few years, however, reveals blockchain has the potential to revolutionize several different industries. The blockchain consists of three major technologies: a peer-to-peer network, a distributed database, and asymmetrically encrypted transactions. The peer-to-peer network enables a decentralized, consensus-based network structure where various nodes contribute to the overall network performance. A distributed database adds additional security and immutability to the network. The process of cryptographically securing individual transactions forms a core service of the blockchain and enables semi-anonymous user network presence
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Anonymity in Bitcoin and Bitmessage
This report describes two projects created by the author which are based on ideas which originate from the Bitcoin community. The first, bmd, is a re-implementation of the Bitmessage protocol in go. Bitmessage is an anonymous and secure messaging system invented by Jonathan Warren, who was inspired by the design of Bitcoin's p2p network. [WARR1] The second is Shufflepuff, an implementation of a protocol called CoinShuffle[RUFF1] which allows several people to construct a Bitcoin transaction with an input and an output for each participant without any participant knowing who owns which output. CoinShuffle was invented by Tim Ruffing et al, and it is an upgrade of a protocol called CoinJoin, invented by Gregory Maxwell. This paper discusses the background, properties, applications, and design of bmd and Shufflepuff. There is also a report of a performance analysis on bmd.Electrical and Computer Engineerin
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