An Imbalanced Malicious Domains Detection Method Based on Passive DNS Traffic Analysis. (20th June 2018)

• Record Type: Journal Article
• Authors: Liu, Zhenyan; Zeng, Yifei; Zhang, Pengfei; Xue, Jingfeng; Zhang, Ji; Liu, Jiangtao
• Other Names: Zhang Yuqing Academic Editor.
• Is Part Of: Security and communication networks. Volume 2018(2018)
• Publication Date: 2018-06-20
• Subjects: Computer networks -- Security measures -- Periodicals; Computer security -- Periodicals; Cryptography -- Periodicals; 005.805
• DOI: 10.1155/2018/6510381
• Languages: English
• ISSNs: 1939-0114

Abstract

Abstract : Although existing malicious domains detection techniques have shown great success in many real-world applications, the problem of learning from imbalanced data is rarely concerned with this day. But the actual DNS traffic is inherently imbalanced; thus how to build malicious domains detection model oriented to imbalanced data is a very important issue worthy of study. This paper proposes a novel imbalanced malicious domains detection method based on passive DNS traffic analysis, which can effectively deal with not only the between-class imbalance problem but also the within-class imbalance problem. The experiments show that this proposed method has favorable performance compared to the existing algorithms.