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Aberdeen Automated Attacks on Your Website

Learn about the changing threat landscape of bots and botnets. Our bot detection & bot mitigation white papers show how to address them with Distil Networks.

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A bot refers to software that provides remote control over the resources of its host system, which is commonly harnessed in conjunction with hundreds or thousands of other bots (a botnet) to work together towards some common objective. Understanding the Risk of Bad Bots — Expressed Properly, in Terms of Likelihood and Business Impact Based on its analysis of web traffic for hundreds of sites, the Distil Networks 2016 Bad Bots Landscape Report (BBLR) found that just over half (54.4%) of all web traffic in 2015 was from actual human users. The other 45.6% was comprised not of humans, but of bots. In the aggregate, good bots represented 27% of all web traffic, and bad bots accounted for the remaining 18.6%. To analyze the business impact of bad bots, Aberdeen Group developed a simple Monte Carlo model which makes simple estimates for the lower bound, upper bound, and distribution of three high-level factors: additional website costs incurred because of bad bots; data breaches related to bad bots; and the loss of website current revenue as a result of bad bots. In addition to these factors, Aberdeen's simple Monte Carlo model requires estimates for just two more inputs: the effectiveness of detecting and mitigating bad bots for three alternative approaches (manual blocking, web application THE RISK OF BAD BOTS: THE IMPACT OF AUTOMATED ATTACKS ON YOUR WEBSITE July 2016 Bots with malicious intent represent a significant percentage of web traffic, and information security professionals need to understand and quantify the risk represented by automated attacks against web applications. Aberdeen Group's analysis shows how addressing the business impact of bad bots has a material impact on a website's financial results. Derek E. Brink, CISSP, Vice President and Research Fellow, Information Security and IT GRC Read the full report: Bad Bots, Good Bots, and Humans: Quantifying the Risk of Bad Bots

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