Waste Flooding: A Phishing Retaliation Tool

@article{Leite2019WasteFA,
  title={Waste Flooding: A Phishing Retaliation Tool},
  author={Cristoffer Leite and J. Gondim and P. S. Barreto and E. Alchieri},
  journal={2019 IEEE 18th International Symposium on Network Computing and Applications (NCA)},
  year={2019},
  pages={1-8}
}
  • Cristoffer Leite, J. Gondim, +1 author E. Alchieri
  • Published 2019
  • Computer Science
  • 2019 IEEE 18th International Symposium on Network Computing and Applications (NCA)
  • Phishing is a well known attack technique that is still a growing threat in the security area. The Internet popularity and the always connected users increased phishing possibilities by giving attackers new instruments and allowing closer contact to their focus. By applying social engineering methods, phishing thrives on misinformation and because of this, current main phishing response methods focus only on educating users or blocking phishing attempts, without any response to derail the… CONTINUE READING

    References

    SHOWING 1-10 OF 22 REFERENCES
    BogusBiter: A transparent protection against phishing attacks
    • 86
    • PDF
    Humboldt: A distributed phishing disruption system
    • 18
    • PDF
    Tracking Phishing Attacks Over Time
    • 38
    • PDF
    Phighting the Phisher: Using Web Bugs and Honeytokens to Investigate the Source of Phishing Attacks
    • C. M. McRae, R. Vaughn
    • Computer Science, Engineering
    • 2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07)
    • 2007
    • 42
    • PDF
    A survey of phishing attacks: Their types, vectors and technical approaches
    • 76
    A recent review of conventional vs. automated cybersecurity anti-phishing techniques
    • 29
    • PDF
    Examining the impact of website take-down on phishing
    • 193
    • PDF
    A novel anti-phishing framework based on honeypots
    • S. Li, R. Schmitz
    • Business, Computer Science
    • 2009 eCrime Researchers Summit
    • 2009
    • 56
    • PDF
    Exploring susceptibility to phishing in the workplace
    • 50
    • PDF
    CANTINA+: A Feature-Rich Machine Learning Framework for Detecting Phishing Web Sites
    • 339
    • PDF