Visible to the public Biblio

Filters: Keyword is anonymous networks  [Clear All Filters]
2021-12-21
Kowalski, Dariusz R., Mosteiro, Miguel A..  2021.  Time and Communication Complexity of Leader Election in Anonymous Networks. 2021 IEEE 41st International Conference on Distributed Computing Systems (ICDCS). :449–460.
We study the problem of randomized Leader Election in synchronous distributed networks with indistinguishable nodes. We consider algorithms that work on networks of arbitrary topology in two settings, depending on whether the size of the network, i.e., the number of nodes \$n\$, is known or not. In the former setting, we present a new Leader Election protocol that improves over previous work by lowering message complexity and making it close to a lower bound by a factor in \$$\backslash$widetildeO($\backslash$sqrtt\_mix$\backslash$sqrt$\backslash$Phi)\$, where $\Phi$ is the conductance and \textsubscriptmix is the mixing time of the network graph. We then show that lacking the network size no Leader Election algorithm can guarantee that the election is final with constant probability, even with unbounded communication. Hence, we further classify the problem as Leader Election (the classic one, requiring knowledge of \$n\$ - as is our first protocol) or Revocable Leader Election, and present a new polynomial time and message complexity Revocable Leader Election algorithm in the setting without knowledge of network size. We analyze time and message complexity of our protocols in the CONGEST model of communication.
2019-01-16
Jia, Z., Cui, X., Liu, Q., Wang, X., Liu, C..  2018.  Micro-Honeypot: Using Browser Fingerprinting to Track Attackers. 2018 IEEE Third International Conference on Data Science in Cyberspace (DSC). :197–204.
Web attacks have proliferated across the whole Internet in recent years. To protect websites, security vendors and researchers collect attack information using web honeypots. However, web attackers can hide themselves by using stepping stones (e.g., VPN, encrypted proxy) or anonymous networks (e.g., Tor network). Conventional web honeypots lack an effective way to gather information about an attacker's identity, which raises a big obstacle for cybercrime traceability and forensics. Traditional forensics methods are based on traffic analysis; it requires that defenders gain access to the entire network. It is not suitable for honeypots. In this paper, we present the design, implementation, and deployment of the Micro-Honeypot, which aims to use the browser fingerprinting technique to track a web attacker. Traditional honeypot lure attackers and records attacker's activity. Micro-Honeypot is deployed in a honeypot. It will run and gather identity information when an attacker visits the honeypot. Our preliminary results show that Micro-Honeypot could collect more information and track attackers although they might have used proxies or anonymous networks to hide themselves.