Melis, L;
Pyrgelis, A;
De Cristofaro, E;
(2018)
On Collaborative Predictive Blacklisting.
ACM SIGCOMM Computer Communication Review
, 48
(5)
pp. 9-20.
10.1145/3310165.3310168.
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Abstract
Collaborative predictive blacklisting (CPB) allows to forecast future attack sources based on logs and alerts contributed by multiple organizations. Unfortunately, however, research on CPB has only focused on increasing the number of predicted attacks but has not considered the impact on false positives and false negatives. Moreover, sharing alerts is often hindered by confidentiality, trust, and liability issues, which motivates the need for privacy-preserving approaches to the problem. In this paper, we present a measurement study of state-of-the-art CPB techniques, aiming to shed light on the actual impact of collaboration. To this end, we reproduce and measure two systems: a non privacy-friendly one that uses a trusted coordinating party with access to all alerts [12] and a peer-to-peer one using privacy-preserving data sharing [8]. We show that, while collaboration boosts the number of predicted attacks, it also yields high false positives, ultimately leading to poor accuracy. This motivates us to present a hybrid approach, using a semi-trusted central entity, aiming to increase utility from collaboration while, at the same time, limiting information disclosure and false positives. This leads to a better trade-off of true and false positive rates, while at the same time addressing privacy concerns.
| Type: | Article |
|---|---|
| Title: | On Collaborative Predictive Blacklisting |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3310165.3310168 |
| Publisher version: | https://doi.org/10.1145/3310165.3310168 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Collaborative Predictive Blacklisting; Privacy; Threat Mitigation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10061779 |
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