Bad Bots, Good Bots, and Humans: Quantifying the Risk of Bad Bots

  • ID: 4036479
  • Report
  • Region: Global
  • 14 Pages
  • Aberdeen Group
1 of 3

Just over half of all web traffic in 2015 was actual human users — the rest was comprised of bots, both benign (27%) and malicious (18.6%). This simple Monte Carlo model will help information security professionals to understand and quantify the risk represented by bad bots. The report will also explore how an investment in an advanced bot detection and mitigation solution quantifiably reduces that risk.

The Vulnerabilities and Exploits of Bad Bots:

  • Website security
    • Brute force logins; account takeovers; fraudulent account creation
    • Man-in-the-browser attacks
    • Reconnaissance attacks; application coding exploits
    • Application denial of service
    • Email spam; phishing attacks
  • Website scraping
    • Content theft
    • Price scraping
    • API scraping
    • Competitive data mining
  • Waste, abuse, and fraud
    • Website performance (both downtime, and slowdown)
    • Negative search engine optimization (SEO)
    • Skewed website analytics
    • Fraudulent transactions
    • Digital ad fraud
Note: Product cover images may vary from those shown
2 of 3
  • Bad Bots, Bad Bots, Watcha Gonna Do When They Come for You?
  • Bad Bots are a Legitimate Threat, But What’s the Risk?
  • Estimating the Likelihood and Business Impact of Bad Bots
  • Factoring for the Risk of Bad Bots Used in Aberdeen’s Simple Monte Carlo Model
  • Quantifying the Risk of Bad Bots, Under the Status Quo
  • Quantifying the Business Value of Bad Bot Countermeasures
  • Quantifying the Risk of Bad Bots, and the
  • Business Value of Advanced Bot Detection and Mitigation
  • Summary and Key Takeaways
Note: Product cover images may vary from those shown
3 of 3

Loading
LOADING...

4 of 3
Note: Product cover images may vary from those shown
Adroll
adroll