Malicious Website Detection

Malicious Website Detection is a computational method designed to identify web resources that exhibit harmful intent or behavior, such as phishing, malware distribution, or fraud, by analyzing structural, content-based, or behavioral features to distinguish them from benign websites.

566

Publications

28.5K

Citations

1.7K

Authors

581

Institutions

Publications per year

2017–2026

292

Authors

1.7K

  1. CK
    Christopher Kruegel

    University of California, Santa Barbara, United States

    13 publications · 2.3K citations

    13

    h-index

  2. GV
    Giovanni Vigna

    University of California, Santa Barbara, United States

    11 publications · 1.9K citations

    11

    h-index

  3. MA
    Mitsuaki Akiyama

    NTT (Japan), Japan

    11 publications · 307 citations

    11

    h-index

  4. TY
    Takeshi Yagi

    NTT (Japan), Japan

    9 publications · 236 citations

    9

    h-index

  5. IW
    Ian Welch

    Victoria University of Wellington, New Zealand

    7 publications · 214 citations

    7

    h-index

1–5 of 1.7K

Venues

  1. Computers & Security

    14 publications · 536 citations

    13

    h-index

  2. arXiv (Cornell University)

    Repository · 12 publications · 681 citations

    12

    h-index

  3. Expert Systems with Applications

    11 publications · 606 citations

    11

    h-index

  4. IEEE Access

    10 publications · 439 citations

    10

    h-index

  5. Security and Communication Networks

    9 publications · 423 citations

    9

    h-index

1–5