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Documents authored by Sanders, William


Found 2 Possible Name Variants:

Sanders, William H.

Document
Randomized Timed and Hybrid Models for Critical Infrastructures (Dagstuhl Seminar 14031)

Authors: Erika Ábrahám, Alberto Avritzer, Anne Remke, and William H. Sanders

Published in: Dagstuhl Reports, Volume 4, Issue 1 (2014)


Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 14031 "Randomized Timed and Hybrid Models for Critical Infrastructures". Critical Infrastructures, such as power grid and water and gas distribution networks, are essential for the functioning of our society and economy. Randomized Timed and Hybrid Models appear as a natural choice for their modeling, and come with existing algorithms and tool support for their analysis. However, on the one hand, the Critical Infrastructures community does not yet make full use of recent advances for Randomized Timed and Hybrid Models. On the other hand, existing algorithms are not yet readily applicable to the special kind of problems arising in Critical Infrastructures. This seminar brought together researchers from these fields to communicate with each other and to exchange knowledge, experiences and needs.

Cite as

Erika Ábrahám, Alberto Avritzer, Anne Remke, and William H. Sanders. Randomized Timed and Hybrid Models for Critical Infrastructures (Dagstuhl Seminar 14031). In Dagstuhl Reports, Volume 4, Issue 1, pp. 36-82, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


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@Article{abraham_et_al:DagRep.4.1.36,
  author =	{\'{A}brah\'{a}m, Erika and Avritzer, Alberto and Remke, Anne and Sanders, William H.},
  title =	{{Randomized Timed and Hybrid Models for Critical Infrastructures (Dagstuhl Seminar 14031)}},
  pages =	{36--82},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2014},
  volume =	{4},
  number =	{1},
  editor =	{\'{A}brah\'{a}m, Erika and Avritzer, Alberto and Remke, Anne and Sanders, William H.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.4.1.36},
  URN =		{urn:nbn:de:0030-drops-45355},
  doi =		{10.4230/DagRep.4.1.36},
  annote =	{Keywords: Critical Infrastructures, Smart Grids, Modeling, Randomized Timed and Hybrid Models, Analysis}
}

Sanders, William

Document
Parasite Chain Detection in the IOTA Protocol

Authors: Andreas Penzkofer, Bartosz Kusmierz, Angelo Capossele, William Sanders, and Olivia Saa

Published in: OASIcs, Volume 82, 2nd International Conference on Blockchain Economics, Security and Protocols (Tokenomics 2020)


Abstract
In recent years several distributed ledger technologies based on directed acyclic graphs (DAGs) have appeared on the market. Similar to blockchain technologies, DAG-based systems aim to build an immutable ledger and are faced with security concerns regarding the irreversibility of the ledger state. However, due to their more complex nature and recent popularity, the study of adversarial actions has received little attention so far. In this paper we are concerned with a particular type of attack on the IOTA cryptocurrency, more specifically a Parasite Chain attack that attempts to revert the history stored in the DAG structure, also called the Tangle. In order to improve the security of the Tangle, we present a detection mechanism for this type of attack. In this mechanism, we embrace the complexity of the DAG structure by sampling certain aspects of it, more particularly the distribution of the number of approvers. We initially describe models that predict the distribution that should be expected for a Tangle without any malicious actors. We then introduce metrics that compare this reference distribution with the measured distribution. Upon detection, measures can then be taken to render the attack unsuccessful. We show that due to a form of the Parasite Chain that is different from the main Tangle it is possible to detect certain types of malicious chains. We also show that although the attacker may change the structure of the Parasite Chain to avoid detection, this is done so at a significant cost since the attack is rendered less efficient.

Cite as

Andreas Penzkofer, Bartosz Kusmierz, Angelo Capossele, William Sanders, and Olivia Saa. Parasite Chain Detection in the IOTA Protocol. In 2nd International Conference on Blockchain Economics, Security and Protocols (Tokenomics 2020). Open Access Series in Informatics (OASIcs), Volume 82, pp. 8:1-8:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{penzkofer_et_al:OASIcs.Tokenomics.2020.8,
  author =	{Penzkofer, Andreas and Kusmierz, Bartosz and Capossele, Angelo and Sanders, William and Saa, Olivia},
  title =	{{Parasite Chain Detection in the IOTA Protocol}},
  booktitle =	{2nd International Conference on Blockchain Economics, Security and Protocols (Tokenomics 2020)},
  pages =	{8:1--8:18},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-157-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{82},
  editor =	{Anceaume, Emmanuelle and Bisi\`{e}re, Christophe and Bouvard, Matthieu and Bramas, Quentin and Casamatta, Catherine},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Tokenomics.2020.8},
  URN =		{urn:nbn:de:0030-drops-135306},
  doi =		{10.4230/OASIcs.Tokenomics.2020.8},
  annote =	{Keywords: Distributed ledger technology, cryptocurrency, directed acyclic graph, security, attack detection algorithm}
}
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