With BOTS saturating internet traffic and BOT attacks on the rise, organizations need to be able to detect, identify and manage BOTS. Bot attacks can not only take hours to detect, but are costly to fix: according to Forbes, 1 in 4 companies find that a single malicious bot attack can cost their organization more than $500,000.
BOTS are becoming increasingly sophisticated and difficult to detect, with third and fourth generation BOTS capable of mimicking human-like behaviour making up 37% of bad BOTS in 2019. Fourth-generation BOTS are particularly sophisticated with the ability to record real user interactions, such as taps and swipes, on hijacked or malware-laden mobile apps, so they can be replicated to “blend in” with human traffic and circumvent security measures.
A BOT management tool is key to mitigating the rise in BOTS, but it must strike a balance between protection and the user experience.
Join the third episode of our three-part series to learn:
● Why bad BOTS can be difficult to detect
● The ways bad BOTs mimic good BOT traffic
● The key features a BOT management solution should address
● How machine-learning capabilities enhance user experience