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  1. AU="Benczúr, András A."
  2. AU="Phillip Hawkins"
  3. AU="Wang, Taihuan"
  4. AU="Hodsman, Anthony B"
  5. AU="Zheng, Bai-Feng"
  6. AU="Lawless, Nathan"
  7. AU="Lim, Ji Young"
  8. AU="Sehdev, Simran"
  9. AU="Del Amor, Francisco M"
  10. AU="Chen, Hanbo"
  11. AU=Song Shiyu
  12. AU="Shen, Chien-Wen"
  13. AU="Philip D King"
  14. AU="Yan, Zhongyu"
  15. AU="Cicalini, Carolina" AU="Cicalini, Carolina"
  16. AU="Magdalena Lange"
  17. AU="Riley, Julie"
  18. AU="Benherrif, Oussama"
  19. AU="Grau, A."
  20. AU=Tao Qiushan
  21. AU="Qin, Guole"
  22. AU="Reis, Jennifer"
  23. AU=Rothstein Eric S
  24. AU="Bruszel, Bella"
  25. AU="Edwin R. Chilvers"
  26. AU="Marco Heredia-R"
  27. AU="Barbora Chladkova"
  28. AU=Chen Yi-Ning
  29. AU="Dirce Maria Lobo Marchioni"
  30. AU="Martínez Fernández, Lidia"
  31. AU="Graham J. T"
  32. AU="Płońska-Gościniak, Edyta"
  33. AU="Shackira, A M"
  34. AU="Fukui, Mototaka"
  35. AU="Jones, Clare A"
  36. AU="Chen, Yonghua"
  37. AU=Das Nilay Kanti
  38. AU="Christine Brittsan"
  39. AU="Skinner, Henry"
  40. AU=Wang Wan-Ying
  41. AU="Ingrid Natalia Muñoz Quijano"
  42. AU="Xu, Jianrong"
  43. AU="Klutts, Abigail"
  44. AU="Corumlu, Ufuk"
  45. AU="Frank Dickmann"
  46. AU="Paz-Priel, Ido"
  47. AU=Budhraja Anshul

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  1. Artikel ; Online: Network embedding aided vaccine skepticism detection.

    Béres, Ferenc / Michaletzky, Tamás Vilmos / Csoma, Rita / Benczúr, András A

    Applied network science

    2023  Band 8, Heft 1, Seite(n) 11

    Abstract: We investigate automatic methods to assess COVID vaccination views in Twitter content. Vaccine skepticism has been a controversial topic of long history that has become more important than ever with the COVID-19 pandemic. Our main goal is to demonstrate ... ...

    Abstract We investigate automatic methods to assess COVID vaccination views in Twitter content. Vaccine skepticism has been a controversial topic of long history that has become more important than ever with the COVID-19 pandemic. Our main goal is to demonstrate the importance of network effects in detecting vaccination skeptic content. Towards this end, we collected and manually labeled vaccination-related Twitter content in the first half of 2021. Our experiments confirm that the network carries information that can be exploited to improve the accuracy of classifying attitudes towards vaccination over content classification as baseline. We evaluate a variety of network embedding algorithms, which we combine with text embedding to obtain classifiers for vaccination skeptic content. In our experiments, by using Walklets, we improve the AUC of the best classifier with no network information by. We publicly release our labels, Tweet IDs and source codes on GitHub.
    Sprache Englisch
    Erscheinungsdatum 2023-02-16
    Erscheinungsland Switzerland
    Dokumenttyp Journal Article
    ISSN 2364-8228
    ISSN (online) 2364-8228
    DOI 10.1007/s41109-023-00534-x
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Buch ; Online: Theoretical Evaluation of Asymmetric Shapley Values for Root-Cause Analysis

    Kelen, Domokos M. / Petreczky, Mihály / Kersch, Péter / Benczúr, András A.

    2023  

    Abstract: In this work, we examine Asymmetric Shapley Values (ASV), a variant of the popular SHAP additive local explanation method. ASV proposes a way to improve model explanations incorporating known causal relations between variables, and is also considered as ... ...

    Abstract In this work, we examine Asymmetric Shapley Values (ASV), a variant of the popular SHAP additive local explanation method. ASV proposes a way to improve model explanations incorporating known causal relations between variables, and is also considered as a way to test for unfair discrimination in model predictions. Unexplored in previous literature, relaxing symmetry in Shapley values can have counter-intuitive consequences for model explanation. To better understand the method, we first show how local contributions correspond to global contributions of variance reduction. Using variance, we demonstrate multiple cases where ASV yields counter-intuitive attributions, arguably producing incorrect results for root-cause analysis. Second, we identify generalized additive models (GAM) as a restricted class for which ASV exhibits desirable properties. We support our arguments by proving multiple theoretical results about the method. Finally, we demonstrate the use of asymmetric attributions on multiple real-world datasets, comparing the results with and without restricted model families using gradient boosting and deep learning models.

    Comment: 10 pages, 6 figures, to be published in IEEE ICDM 2023
    Schlagwörter Computer Science - Machine Learning ; Statistics - Methodology
    Thema/Rubrik (Code) 006
    Erscheinungsdatum 2023-10-15
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  3. Buch ; Online: ethp2psim

    Béres, Ferenc / Seres, István András / Kelen, Domokos M. / Benczúr, András A.

    Evaluating and deploying privacy-enhanced peer-to-peer routing protocols for the Ethereum network

    2023  

    Abstract: Network-level privacy is the Achilles heel of financial privacy in cryptocurrencies. Financial privacy amounts to achieving and maintaining blockchain- and network-level privacy. Blockchain-level privacy recently received substantial attention. ... ...

    Abstract Network-level privacy is the Achilles heel of financial privacy in cryptocurrencies. Financial privacy amounts to achieving and maintaining blockchain- and network-level privacy. Blockchain-level privacy recently received substantial attention. Specifically, several privacy-enhancing technologies were proposed and deployed to enhance blockchain-level privacy. On the other hand, network-level privacy, i.e., privacy on the peer-to-peer layer, has seen far less attention and development. In this work, we aim to provide a peer-to-peer network simulator, ethp2psim, that allows researchers to evaluate the privacy guarantees of privacy-enhanced broadcast and message routing algorithms. Our goal is two-fold. First, we want to enable researchers to implement their proposed protocols in our modular simulator framework. Second, our simulator allows researchers to evaluate the privacy guarantees of privacy-enhanced routing algorithms. Finally, ethp2psim can help choose the right protocol parameters for efficient, robust, and private deployment.
    Schlagwörter Computer Science - Cryptography and Security ; Computer Science - Networking and Internet Architecture
    Thema/Rubrik (Code) 303 ; 005
    Erscheinungsdatum 2023-06-26
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  4. Buch ; Online: Vaccine skepticism detection by network embedding

    Béres, Ferenc / Csoma, Rita / Michaletzky, Tamás Vilmos / Benczúr, András A.

    2021  

    Abstract: We demonstrate the applicability of network embedding to vaccine skepticism, a controversial topic of long-past history. With the Covid-19 pandemic outbreak at the end of 2019, the topic is more important than ever. Only a year after the first ... ...

    Abstract We demonstrate the applicability of network embedding to vaccine skepticism, a controversial topic of long-past history. With the Covid-19 pandemic outbreak at the end of 2019, the topic is more important than ever. Only a year after the first international cases were registered, multiple vaccines were developed and passed clinical testing. Besides the challenges of development, testing, and logistics, another factor that might play a significant role in the fight against the pandemic are people who are hesitant to get vaccinated, or even state that they will refuse any vaccine offered to them. Two groups of people commonly referred to as a) pro-vaxxer, those who support vaccinating people b) vax-skeptic, those who question vaccine efficacy or the need for general vaccination against Covid-19. It is very difficult to tell exactly how many people share each of these views. It is even more difficult to understand all the reasoning why vax-skeptic opinions are getting more popular. In this work, our intention was to develop techniques that are able to efficiently differentiate between pro-vaxxer and vax-skeptic content. After multiple data preprocessing steps, we analyzed the tweet text as well as the structure of user interactions on Twitter. We deployed several node embedding and community detection models that scale well for graphs with millions of edges.

    Comment: The data and the source code are available on GitHub: https://github.com/ferencberes/covid-vaccine-network
    Schlagwörter Computer Science - Social and Information Networks ; Computer Science - Machine Learning
    Erscheinungsdatum 2021-10-20
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  5. Buch ; Online: A Cryptoeconomic Traffic Analysis of Bitcoin's Lightning Network

    Beres, Ferenc / Seres, Istvan Andras / Benczur, Andras A.

    2019  

    Abstract: Lightning Network (LN) is designed to amend the scalability and privacy issues of Bitcoin. It's a payment channel network where Bitcoin transactions are issued off chain, onion routed through a private payment path with the aim to settle transactions in ... ...

    Abstract Lightning Network (LN) is designed to amend the scalability and privacy issues of Bitcoin. It's a payment channel network where Bitcoin transactions are issued off chain, onion routed through a private payment path with the aim to settle transactions in a faster, cheaper, and private manner, as they're not recorded in a costly-to-maintain, slow, and public ledger. In this work, we design a traffic simulator to empirically study LN's transaction fees and privacy provisions. The simulator relies on publicly available data of the network structure and generates transactions under assumptions we attempt to validate based on information spread by certain blog posts of LN node owners. Our findings on the estimated revenue from transaction fees are in line with widespread opinion that participation is economically irrational for the majority of large routing nodes who currently hold the network together. Either traffic or transaction fees must increase by orders of magnitude to make payment routing economically viable. We give worst-case estimates for the potential fee increase by assuming strong price competition among the routers. We estimate how current channel structures and pricing policies respond to a potential increase in traffic, how reduction in locked funds on channels would affect the network, and show examples of nodes who are estimated to operate with economically feasible revenue. Even if transactions are onion routed, strong statistical evidence on payment source and destination can be inferred, as many transaction paths only consist of a single intermediary by the side effect of LN's small-world nature. Based on our simulation experiments, we quantitatively characterize the privacy shortcomings of current LN operation, and propose a method to inject additional hops in routing paths to demonstrate how privacy can be strengthened with very little additional transactional cost.

    Comment: Cryptoeconomic Systems (CES) '20 Journal & Conference 7-8 March 2020, MIT, Cambridge, MA
    Schlagwörter Computer Science - Cryptography and Security
    Thema/Rubrik (Code) 303
    Erscheinungsdatum 2019-11-21
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  6. Buch ; Online: Blockchain is Watching You

    Béres, Ferenc / Seres, István András / Benczúr, András A. / Quintyne-Collins, Mikerah

    Profiling and Deanonymizing Ethereum Users

    2020  

    Abstract: Ethereum is the largest public blockchain by usage. It applies an account-based model, which is inferior to Bitcoin's unspent transaction output model from a privacy perspective. Due to its privacy shortcomings, recently several privacy-enhancing ... ...

    Abstract Ethereum is the largest public blockchain by usage. It applies an account-based model, which is inferior to Bitcoin's unspent transaction output model from a privacy perspective. Due to its privacy shortcomings, recently several privacy-enhancing overlays have been deployed on Ethereum, such as non-custodial, trustless coin mixers and confidential transactions. In our privacy analysis of Ethereum's account-based model, we describe several patterns that characterize only a limited set of users and successfully apply these quasi-identifiers in address deanonymization tasks. Using Ethereum Name Service identifiers as ground truth information, we quantitatively compare algorithms in recent branch of machine learning, the so-called graph representation learning, as well as time-of-day activity and transaction fee based user profiling techniques. As an application, we rigorously assess the privacy guarantees of the Tornado Cash coin mixer by discovering strong heuristics to link the mixing parties. To the best of our knowledge, we are the first to propose and implement Ethereum user profiling techniques based on quasi-identifiers. Finally, we describe a malicious value-fingerprinting attack, a variant of the Danaan-gift attack, applicable for the confidential transaction overlays on Ethereum. By incorporating user activity statistics from our data set, we estimate the success probability of such an attack.

    Comment: 19 pages
    Schlagwörter Computer Science - Cryptography and Security ; Computer Science - Computers and Society
    Thema/Rubrik (Code) 005
    Erscheinungsdatum 2020-05-28
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  7. Artikel ; Online: Temporal walk based centrality metric for graph streams.

    Béres, Ferenc / Pálovics, Róbert / Oláh, Anna / Benczúr, András A

    Applied network science

    2018  Band 3, Heft 1, Seite(n) 32

    Abstract: A plethora of centrality measures or rankings have been proposed to account for the importance of the nodes of a network. In the seminal study of Boldi and Vigna (2014), the comparative evaluation of centrality measures was termed a difficult, arduous ... ...

    Abstract A plethora of centrality measures or rankings have been proposed to account for the importance of the nodes of a network. In the seminal study of Boldi and Vigna (2014), the comparative evaluation of centrality measures was termed a difficult, arduous task. In networks with fast dynamics, such as the Twitter mention or retweet graphs, predicting emerging centrality is even more challenging. Our main result is a new, temporal walk based dynamic centrality measure that models temporal information propagation by considering the order of edge creation. Dynamic centrality measures have already started to emerge in publications; however, their empirical evaluation is limited. One of our main contributions is creating a quantitative experiment to assess temporal centrality metrics. In this experiment, our new measure outperforms graph snapshot based static and other recently proposed dynamic centrality measures in assigning the highest time-aware centrality to the actually relevant nodes of the network. Additional experiments over different data sets show that our method perform well for detecting concept drift in the process that generates the graphs.
    Sprache Englisch
    Erscheinungsdatum 2018-08-14
    Erscheinungsland Switzerland
    Dokumenttyp Journal Article
    ISSN 2364-8228
    ISSN (online) 2364-8228
    DOI 10.1007/s41109-018-0080-5
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  8. Buch ; Online: Temporal influence over the Last.fm social network

    Pálovics, Róbert / Benczúr, András A.

    2013  

    Abstract: Several recent results show the influence of social contacts to spread certain properties over the network, but others question the methodology of these experiments by proposing that the measured effects may be due to homophily or a shared environment. ... ...

    Abstract Several recent results show the influence of social contacts to spread certain properties over the network, but others question the methodology of these experiments by proposing that the measured effects may be due to homophily or a shared environment. In this paper we justify the existence of the social influence by considering the temporal behavior of Last.fm users. In order to clearly distinguish between friends sharing the same interest, especially since Last.fm recommends friends based on similarity of taste, we separated the timeless effect of similar taste from the temporal impulses of immediately listening to the same artist after a friend. We measured strong increase of listening to a completely new artist in a few hours period after a friend compared to non-friends representing a simple trend or external influence. In our experiment to eliminate network independent elements of taste, we improved collaborative filtering and trend based methods by blending with simple time aware recommendations based on the influence of friends. Our experiments are carried over the two-year "scrobble" history of 70,000 Last.fm users.

    Comment: 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013
    Schlagwörter Computer Science - Social and Information Networks ; Physics - Physics and Society
    Thema/Rubrik (Code) 306
    Erscheinungsdatum 2013-07-28
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  9. Buch ; Online: M\'{e}todos para la Selecci\'{o}n y el Ajuste de Caracter\'{i}sticas en el Problema de la Detecci\'{o}n de Spam

    Lorenzetti, Carlos M. / Cecchini, Rocío L. / Maguitman, Ana G. / Benczúr, András A.

    2010  

    Abstract: The email is used daily by millions of people to communicate around the globe and it is a mission-critical application for many businesses. Over the last decade, unsolicited bulk email has become a major problem for email users. An overwhelming amount of ...

    Abstract The email is used daily by millions of people to communicate around the globe and it is a mission-critical application for many businesses. Over the last decade, unsolicited bulk email has become a major problem for email users. An overwhelming amount of spam is flowing into users' mailboxes daily. In 2004, an estimated 62% of all email was attributed to spam. Spam is not only frustrating for most email users, it strains the IT infrastructure of organizations and costs businesses billions of dollars in lost productivity. In recent years, spam has evolved from an annoyance into a serious security threat, and is now a prime medium for phishing of sensitive information, as well the spread of malicious software. This work presents a first approach to attack the spam problem. We propose an algorithm that will improve a classifier's results by adjusting its training set data. It improves the document's vocabulary representation by detecting good topic descriptors and discriminators.

    Comment: 5 pages, 1 figure, Workshop de Investigadores en Ciencias de la Computaci\'{o}n, WICC 2010, pp 48-52
    Schlagwörter Computer Science - Information Retrieval ; Computer Science - Artificial Intelligence ; 68P20 ; H.3.3
    Thema/Rubrik (Code) 303
    Erscheinungsdatum 2010-06-01
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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