Title:
Mimicry Attacks Against DNS Reputation Systems
Mimicry Attacks Against DNS Reputation Systems
| dc.contributor.advisor | Antonakakis, Manos | |
| dc.contributor.author | Galloway, Tillson Thomas | |
| dc.contributor.committeeMember | Keromytis, Angelos | |
| dc.contributor.department | Computer Science | |
| dc.date.accessioned | 2022-05-27T14:38:14Z | |
| dc.date.available | 2022-05-27T14:38:14Z | |
| dc.date.created | 2022-05 | |
| dc.date.issued | 2022-05 | |
| dc.date.submitted | May 2022 | |
| dc.date.updated | 2022-05-27T14:38:14Z | |
| dc.description.abstract | The Domain Name System (DNS) has been an essential component of the Internet since 1985, mapping domain names that are easy to remember (e.g. google.com) to IPs that computers use to communicate (e.g. 30.3.5.2). DNS Reputation Systems use machine learning to identify malicious domains using large datasets containing DNS queries. We analyze the robustness of these reputation systems to attack and propose Mimicry Attacks, a novel technique that allows malicious domains to hide by mimicking the behavior of benign network infrastructure. This attack achieves an 85% success rate against active DNS datasets while coming at a low financial cost to the attacker. | |
| dc.description.degree | Undergraduate | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/1853/66739 | |
| dc.language.iso | en_US | |
| dc.publisher | Georgia Institute of Technology | |
| dc.subject | Domain name system | |
| dc.subject | Adversarial machine learning | |
| dc.subject | DNS Reputation Systems | |
| dc.subject | Network security | |
| dc.title | Mimicry Attacks Against DNS Reputation Systems | |
| dc.type | Text | |
| dc.type.genre | Undergraduate Thesis | |
| dspace.entity.type | Publication | |
| local.contributor.corporatename | College of Computing | |
| local.contributor.corporatename | School of Computer Science | |
| local.contributor.corporatename | Undergraduate Research Opportunities Program | |
| local.relation.ispartofseries | Undergraduate Research Option Theses | |
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| relation.isSeriesOfPublication | e1a827bd-cf25-4b83-ba24-70848b7036ac | |
| thesis.degree.level | Undergraduate |