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Semantics derived automatically from language corpora contain human-like biases
It is shown that machines can learn word associations from written texts and that these associations mirror those learned by humans, as measured by the Implicit Association Test (IAT), and that applying machine learning to ordinary human language results in human-like semantic biases.
De-anonymizing Social Networks
- A. Narayanan, Vitaly Shmatikov
- Computer Science30th IEEE Symposium on Security and Privacy
- 18 March 2009
A framework for analyzing privacy and anonymity in social networks is presented and a new re-identification algorithm targeting anonymized social-network graphs is developed, showing that a third of the users who can be verified to have accounts on both Twitter and Flickr can be re-identified in the anonymous Twitter graph.
Online Tracking: A 1-million-site Measurement and Analysis
The largest and most detailed measurement of online tracking conducted to date, based on a crawl of the top 1 million websites, is presented, which demonstrates the OpenWPM platform's strength in enabling researchers to rapidly detect, quantify, and characterize emerging online tracking behaviors.
Robust De-anonymization of Large Sparse Datasets
- A. Narayanan, Vitaly Shmatikov
- Computer Science, EconomicsIEEE Symposium on Security and Privacy (sp )
- 18 May 2008
This work applies the de-anonymization methodology to the Netflix Prize dataset, which contains anonymous movie ratings of 500,000 subscribers of Netflix, the world's largest online movie rental service, and demonstrates that an adversary who knows only a little bit about an individual subscriber can easily identify this subscriber's record in the dataset.
SoK: Research Perspectives and Challenges for Bitcoin and Cryptocurrencies
- Joseph Bonneau, Andrew K. Miller, Jeremy Clark, A. Narayanan, Joshua A. Kroll, E. Felten
- Computer ScienceIEEE Symposium on Security and Privacy
- 17 May 2015
This work identifies three key components of Bit coin's design that can be decoupled, and maps the design space for numerous proposed modifications, providing comparative analyses for alternative consensus mechanisms, currency allocation mechanisms, computational puzzles, and key management tools.
Bitcoin and Cryptocurrency Technologies - A Comprehensive Introduction
- A. Narayanan, Joseph Bonneau, E. Felten, Andrew K. Miller, Steven Goldfeder
- Computer Science
- 19 July 2016
The history and development of Bitcoin and cryptocurrencies are traced, and the conceptual and practical foundations you need to engineer secure software that interacts with the Bitcoin network are given as well as to integrate ideas from Bitcoin into your own projects.
The Web Never Forgets: Persistent Tracking Mechanisms in the Wild
- Gunes Acar, Christian Eubank, S. Englehardt, Marc Juárez, A. Narayanan, Claudia Díaz
- Computer ScienceCCS
- 3 November 2014
The evaluation of the defensive techniques used by privacy-aware users finds that there exist subtle pitfalls --- such as failing to clear state on multiple browsers at once - in which a single lapse in judgement can shatter privacy defenses.
De-anonymizing Programmers via Code Stylometry
- Aylin Caliskan, Richard E. Harang, R. Greenstadt
- Computer ScienceUSENIX Security Symposium
- 12 August 2015
This work investigates machine learning methods to de-anonymize source code authors of C/C++ using coding style using random forest and abstract syntax tree-based approach, and finds that the code resulting from difficult programming tasks is easier to attribute than easier tasks and skilled programmers are easier to attributes than less skilled programmers.
Adnostic: Privacy Preserving Targeted Advertising
This paper proposes a practical architecture that enables targeting without compromising user privacy, and implements the core targeting system as a Firefox extension and reports on its effectiveness.
Fast dictionary attacks on passwords using time-space tradeoff
It is demonstrated that as long as passwords remain human-memorable, they are vulnerable to "smart-dictionary" attacks even when the space of potential passwords is large, calling into question viability of human- Memorable character-sequence passwords as an authentication mechanism.