Development of the domain name system
SIGCOMM '88 Symposium proceedings on Communications architectures and protocols
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Automatic retrieval and clustering of similar words
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Noun classification from predicate-argument structures
ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
Evaluating WordNet-based Measures of Lexical Semantic Relatedness
Computational Linguistics
Context-aware clustering of DNS query traffic
Proceedings of the 8th ACM SIGCOMM conference on Internet measurement
Kwyjibo: automatic domain name generation
Software—Practice & Experience
Global Internet Monitoring Using Passive DNS
CATCH '09 Proceedings of the 2009 Cybersecurity Applications & Technology Conference for Homeland Security
Password Cracking Using Probabilistic Context-Free Grammars
SP '09 Proceedings of the 2009 30th IEEE Symposium on Security and Privacy
Detecting Malicious Flux Service Networks through Passive Analysis of Recursive DNS Traces
ACSAC '09 Proceedings of the 2009 Annual Computer Security Applications Conference
Detecting algorithmically generated malicious domain names
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
A centralized monitoring infrastructure for improving DNS security
RAID'10 Proceedings of the 13th international conference on Recent advances in intrusion detection
Proactive discovery of phishing related domain names
RAID'12 Proceedings of the 15th international conference on Research in Attacks, Intrusions, and Defenses
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The DNS structure discloses useful information about the organization and the operation of an enterprise network, which can be used for designing attacks as well as monitoring domains supporting malicious activities. Thus, this paper introduces a new method for exploring the DNS domains. Although our previous work described a tool to generate existing DNS names accurately in order to probe a domain automatically, the approach is extended by leveraging semantic analysis of domain names. In particular, the semantic distributional similarity and relatedness of sub-domains are considered as well as sequential patterns. The evaluation shows that the discovery is highly improved while the overhead remains low, comparing with non semantic DNS probing tools including ours and others.