10 research outputs found
Using Markov Models and Statistics to Learn, Extract, Fuse, and Detect Patterns in Raw Data
Many systems are partially stochastic in nature. We have derived data driven
approaches for extracting stochastic state machines (Markov models) directly
from observed data. This chapter provides an overview of our approach with
numerous practical applications. We have used this approach for inferring
shipping patterns, exploiting computer system side-channel information, and
detecting botnet activities. For contrast, we include a related data-driven
statistical inferencing approach that detects and localizes radiation sources.Comment: Accepted by 2017 International Symposium on Sensor Networks, Systems
and Securit
Utilizing Public Blockchains for the Sybil-Resistant Bootstrapping of Distributed Anonymity Services
Distributed anonymity services, such as onion routing networks or
cryptocurrency tumblers, promise privacy protection without trusted third
parties. While the security of these services is often well-researched,
security implications of their required bootstrapping processes are usually
neglected: Users either jointly conduct the anonymization themselves, or they
need to rely on a set of non-colluding privacy peers. However, the typically
small number of privacy peers enable single adversaries to mimic distributed
services. We thus present AnonBoot, a Sybil-resistant medium to securely
bootstrap distributed anonymity services via public blockchains. AnonBoot
enforces that peers periodically create a small proof of work to refresh their
eligibility for providing secure anonymity services. A pseudo-random, locally
replicable bootstrapping process using on-chain entropy then prevents biasing
the election of eligible peers. Our evaluation using Bitcoin as AnonBoot's
underlying blockchain shows its feasibility to maintain a trustworthy
repository of 1000 peers with only a small storage footprint while supporting
arbitrarily large user bases on top of most blockchains.Comment: To be published in the proceedings of the 15th ACM ASIA Conference on
Computer and Communications Security (ACM ASIACCS'20
Structure and Anonymity of the Bitcoin Transaction Graph
The Bitcoin network of decentralized payment transactions has attracted a lot of attention from both Internet users and researchers in recent years. Bitcoin utilizes a peer-to-peer network to issue anonymous payment transactions between different users. In the currently used Bitcoin clients, the full transaction history is available at each node of the network to prevent double spending without the need for a central authority, forming a valuable source for empirical research on network structure, network dynamics, and the implied anonymity challenges, as well as guidance on the future evolution of complex payment systems. We found dynamical effects of which some increase anonymity while others decrease it. Most importantly, several parameters of the Bitcoin transaction graph seem to have become stationary over the last 12â18 months. We discuss the implications
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Many trace elements like Mn, Fe, Co, Ni, Cu and Zn are essential for marine life, some trace elements are of concern as pollutants, e.g. Pb and Hg, while others, together with a diverse array of isotopes, are used to assess modern-ocean processes and the role of the ocean in past climate change. GEOTRACES is an international program that aims to measure the distribution of trace elements and isotopes throughout the world oceans to improve our understanding of their marine biogeochemical cycles. To contribute to GEOTRACES a new sampler system was developed at NIOZ allowing efficient sampling of large volumes of seawater under ultraclean conditions. The 24 "PRISTINE" samplers each with a volume of 24.4 L are made of a high-purity polymer Polyvinylidene Fluoride (PVDF) and are opened and closed using a butterfly-valve closing mechanism. The samplers are mounted on an all-titanium frame and deployed using a poly-aramide hydrowire (Super Aram) with internal power/signal conductors. Upon recovery the complete frame is immediately placed in its own clean-air laboratory unit. Samplers are (i) always closed when onboard, (ii) always mounted on the frame without the need for hand-carrying heavy samplers, and (iii) can be deployed again with minimal (manual) preparation. The PRISTINE ultraclean sampling system was used for the first time during the GA02 GEOTRACES cruises in the West Atlantic Ocean (2010-2012). During 60 full ocean depth stations all 24 samplers closed with a 100% success rate. Sampling proved to be much faster, less labor intensive, and ultraclean. A comparison of salinity, temperature, nutrient and oxygen data collected with the rectangular titanium frame with PRISTINE samplers and a traditional CTD frame with Niskin samplers showed that the CTD systems functioned equally well, that the PRISTINE samplers took discrete seawater samples without any inward leakage of seawater during the up-cast, and that no atmospheric oxygen contaminated the seawater samples in the PRISTINE samplers after return on deck. The excellent agreement between 13 trace elements sampled with PRISTINE and sampled during the cross over occupation of US-GEOTRACES at the Bermuda BATS site (32 degrees N, 64 degrees W) shows its suitability for ultraclean trace element and isotope sampling (see accompanying paper). (C) 2015 Elsevier B.V. All rights reserved
Starlikeness of Libera transformation (II) (Applications of Complex Function Theory to Differential Equations)
The GEOTRACES Intermediate Data Product 2017 (IDP2017) is the second publicly available data product of the international GEOTRACES programme, and contains data measured and quality controlled before the end of 2016. The IDP2017 includes data from the Atlantic, Pacific, Arctic, Southern and Indian oceans, with about twice the data volume of the previous IDP2014. For the first time, the IDP2017 contains data for a large suite of biogeochemical parameters as well as aerosol and rain data characterising atmospheric trace element and isotope (TEI) sources. The TEI data in the IDP2017 are quality controlled by careful assessment of intercalibration results and multi-laboratory data comparisons at crossover stations. The IDP2017 consists of two parts: (1) a compilation of digital data for more than 450 TEIs as well as standard hydrographic parameters, and (2) the eGEOTRACES Electronic Atlas providing an on-line atlas that includes more than 590 section plots and 130 animated 3D scenes. The digital data are provided in several formats, including ASCII, Excel spreadsheet, netCDF, and Ocean Data View collection. Users can download the full data packages or make their own custom selections with a new on-line data extraction service. In addition to the actual data values, the IDP2017 also contains data quality flags and 1-Ï data error values where available. Quality flags and error values are useful for data filtering and for statistical analysis. Metadata about data originators, analytical methods and original publications related to the data are linked in an easily accessible way. The eGEOTRACES Electronic Atlas is the visual representation of the IDP2017 as section plots and rotating 3D scenes. The basin-wide 3D scenes combine data from many cruises and provide quick overviews of large-scale tracer distributions. These 3D scenes provide geographical and bathymetric context that is crucial for the interpretation and assessment of tracer plumes near ocean margins or along ridges. The IDP2017 is the result of a truly international effort involving 326 researchers from 25 countries. This publication provides the critical reference for unpublished data, as well as for studies that make use of a large cross-section of data from the IDP2017. This article is part of a special issue entitled: Conway GEOTRACES - edited by Tim M. Conway, Tristan Horner, Yves Plancherel, and Aridane G. GonzĂĄlez
The GEOTRACES Intermediate Data Product 2017
Unidad de excelencia MarĂa de Maeztu MdM-2015-0552The GEOTRACES Intermediate Data Product 2017 (IDP2017) is the second publicly available data product of the international GEOTRACES programme, and contains data measured and quality controlled before the end of 2016. The IDP2017 includes data from the Atlantic, Pacific, Arctic, Southern and Indian oceans, with about twice the data volume of the previous IDP2014. For the first time, the IDP2017 contains data for a large suite of biogeochemical parameters as well as aerosol and rain data characterising atmospheric trace element and isotope (TEI) sources. The TEI data in the IDP2017 are quality controlled by careful assessment of intercalibration results and multi-laboratory data comparisons at crossover stations. The IDP2017 consists of two parts: (1) a compilation of digital data for more than 450 TEIs as well as standard hydrographic parameters, and (2) the eGEOTRACES Electronic Atlas providing an on-line atlas that includes more than 590 section plots and 130 animated 3D scenes. The digital data are provided in several formats, including ASCII, Excel spreadsheet, netCDF, and Ocean Data View collection. Users can download the full data packages or make their own custom selections with a new on-line data extraction service. In addition to the actual data values, the IDP2017 also contains data quality flags and 1-Ï data error values where available. Quality flags and error values are useful for data filtering and for statistical analysis. Metadata about data originators, analytical methods and original publications related to the data are linked in an easily accessible way. The eGEOTRACES Electronic Atlas is the visual representation of the IDP2017 as section plots and rotating 3D scenes. The basin-wide 3D scenes combine data from many cruises and provide quick overviews of large-scale tracer distributions. These 3D scenes provide geographical and bathymetric context that is crucial for the interpretation and assessment of tracer plumes near ocean margins or along ridges. The IDP2017 is the result of a truly international effort involving 326 researchers from 25 countries. This publication provides the critical reference for unpublished data, as well as for studies that make use of a large cross-section of data from the IDP2017. This article is part of a special issue entitled: Conway GEOTRACES - edited by Tim M. Conway, Tristan Horner, Yves Plancherel, and Aridane G. GonzĂĄlez