References of "Ferreira Torres, Christof 50014996"
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See detailWhispering Botnet Command and Control Instructions
Steichen, Mathis UL; Ferreira Torres, Christof UL; Fiz Pontiveros, Beltran UL et al

in 2nd Crypto Valley Conference on Blockchain Technology, Zug 24-26 June 2019 (2019, June 25)

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See detailThe Art of The Scam: Demystifying Honeypots in Ethereum Smart Contracts
Ferreira Torres, Christof UL; Steichen, Mathis UL; State, Radu UL

in USENIX Security Symposium, Santa Clara, 14-16 August 2019 (2019)

Modern blockchains, such as Ethereum, enable the execution of so-called smart contracts - programs that are executed across a decentralised network of nodes. As smart contracts become more popular and ... [more ▼]

Modern blockchains, such as Ethereum, enable the execution of so-called smart contracts - programs that are executed across a decentralised network of nodes. As smart contracts become more popular and carry more value, they become more of an interesting target for attackers. In the past few years, several smart contracts have been exploited by attackers. However, a new trend towards a more proactive approach seems to be on the rise, where attackers do not search for vulnerable contracts anymore. Instead, they try to lure their victims into traps by deploying seemingly vulnerable contracts that contain hidden traps. This new type of contracts is commonly referred to as honeypots. In this paper, we present the first systematic analysis of honeypot smart contracts, by investigating their prevalence, behaviour and impact on the Ethereum blockchain. We develop a taxonomy of honeypot techniques and use this to build HoneyBadger - a tool that employs symbolic execution and well defined heuristics to expose honeypots. We perform a large-scale analysis on more than 2 million smart contracts and show that our tool not only achieves high precision, but is also highly efficient. We identify 690 honeypot smart contracts as well as 240 victims in the wild, with an accumulated profit of more than $90,000 for the honeypot creators. Our manual validation shows that 87% of the reported contracts are indeed honeypots. [less ▲]

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See detailOsiris: Hunting for Integer Bugs in Ethereum Smart Contracts
Ferreira Torres, Christof UL; Schütte, Julian; State, Radu UL

in 34th Annual Computer Security Applications Conference (ACSAC ’18), San Juan, Puerto Rico, USA, December 3-7, 2018 (2018, December)

The capability of executing so-called smart contracts in a decentralised manner is one of the compelling features of modern blockchains. Smart contracts are fully fledged programs which cannot be changed ... [more ▼]

The capability of executing so-called smart contracts in a decentralised manner is one of the compelling features of modern blockchains. Smart contracts are fully fledged programs which cannot be changed once deployed to the blockchain. They typically implement the business logic of distributed apps and carry billions of dollars worth of coins. In that respect, it is imperative that smart contracts are correct and have no vulnerabilities or bugs. However, research has identified different classes of vulnerabilities in smart contracts, some of which led to prominent multi-million dollar fraud cases. In this paper we focus on vulnerabilities related to integer bugs, a class of bugs that is particularly difficult to avoid due to some characteristics of the Ethereum Virtual Machine and the Solidity programming language. In this paper we introduce Osiris – a framework that combines symbolic execution and taint analysis, in order to accurately find integer bugs in Ethereum smart contracts. Osiris detects a greater range of bugs than existing tools, while providing a better specificity of its detection. We have evaluated its performance on a large experimental dataset containing more than 1.2 million smart contracts. We found that 42,108 contracts contain integer bugs. Be- sides being able to identify several vulnerabilities that have been reported in the past few months, we were also able to identify a yet unknown critical vulnerability in a couple of smart contracts that are currently deployed on the Ethereum blockchain. [less ▲]

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See detailInvestigating Fingerprinters and Fingerprinting-Alike Behaviour of Android Applications
Ferreira Torres, Christof UL; Jonker, Hugo

in 23rd European Symposium on Research in Computer Security, Barcelona, Spain, September 3-7, 2018 (2018)

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See detailTackling the IFP Problem with the Preference-Based Genetic Algorithm
Nielsen, Sune Steinbjorn UL; Ferreira Torres, Christof UL; Danoy, Grégoire UL et al

in Proceedings of the Genetic and Evolutionary Computation Conference 2016 (2016)

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See detailThe Fréchet/Manhattan distance and the trajectory anonymisation problem
Ferreira Torres, Christof UL; Trujillo Rasua, Rolando UL

in Proceedings of Data and Applications Security and Privacy - 30th Annual IFIP WG 11.3 Conference (DBSec 2016) (2016)

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See detailPreference-Based Genetic Algorithm for Solving the Bio-Inspired NK Landscape Benchmark
Ferreira Torres, Christof UL; Nielsen, Sune Steinbjorn UL; Danoy, Grégoire UL et al

in 7th European Symposium on Computational Intelligence and Mathematics (ESCIM) (2015, October)

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See detailFP-Block: Usable Web Privacy by Controlling Browser Fingerprinting
Ferreira Torres, Christof UL; Jonker, Hugo; Mauw, Sjouke UL

in Pernul, Günther; Y A Ryan, Peter; Weippl, Edgar (Eds.) Computer Security -- ESORICS 2015 (2015)

Online tracking of users is used for benign goals, such as detecting fraudulent logins, but also to invade user privacy. We posit that for non-oppressed users, tracking within one website does not have a ... [more ▼]

Online tracking of users is used for benign goals, such as detecting fraudulent logins, but also to invade user privacy. We posit that for non-oppressed users, tracking within one website does not have a substantial negative impact on privacy, while it enables legitimate benefits. In contrast, cross-domain tracking negatively impacts user privacy, while being of little benefit to the user. Existing methods to counter fingerprint-based tracking treat cross-domain tracking and regular tracking the same. This often results in hampering or disabling desired functionality, such as embedded videos. By distinguishing between regular and cross-domain tracking, more desired functionality can be preserved. We have developed a prototype tool, FP-Block, that counters cross-domain fingerprint-based tracking while still allowing regular tracking. FP-Block ensures that any embedded party will see a different, unrelatable fingerprint for each site on which it is embedded. Thus, the user’s fingerprint can no longer be tracked across the web, while desired functionality is better preserved compared to existing methods. [less ▲]

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