Two-Stage Classification Technique for Malicious DNS Identification

초록

Cyber-security for years has been a challenging topic for the research community and most or these attacks have been directed at one of the most critical Internet infrastructure, the domain name system (DNS). DNS attacks are usually catastrophic and often results in loss of sensitive information, hence this paper aims at proffering a solution to these type of attacks. In this paper, a two-stage classification process is proposed for mitigating DNS attacks. The proposed scheme employs long short-term memory in the first stage a convolutional neural network at the second stage. Simulation results show a good classification accuracy for both stages of the proposed scheme.

제목
Two-Stage Classification Technique for Malicious DNS Identification
저자
Amaizu, Gabriel Chukwunonso; Agron, Danielle Jaye S.; Lee, Jae-Min; Kim, Dong-Seong
DOI
10.1109/ICAIIC51459.2021.9415225
발행일
2021-04
학회명
3rd International Conference on Artificial Intelligence in Information and Communication (IEEE ICAIIC)
개최지
SOUTH KOREA
개최국가
대한민국
학회 개최일
2021-04-13 ~ 2021-04-16