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Two-Stage Classification Technique for Malicious DNS Identification
- Amaizu, Gabriel Chukwunonso;
- Agron, Danielle Jaye S.;
- Lee, Jae-Min;
- Kim, Dong-Seong
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
- 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
- 언어
- ENG