With the increased use of automation, the variation between human and machine intelligence is becoming more unclear.
With the pandemic induced new normal, people have been using more time on the internet and managing daily chores from online stores. With consumers changing their online habits and usage patterns, the difference between human and robot behavior becomes highly blurred.
This is now putting cyber-security teams with a significant challenge than before, especially when distinguishing humans from bots or good bot actions from bad ones. Earlier, businesses have been blocking all bot activities, and that strategy does not work in this era.
Lately, companies are finding a way of navigating the current automation landscape. If not, they would risk blocking good bots and genuine customers. This could even make bots taking over the customer accounts and ruining the brand reputation.
What is the setback for enterprises with bad bots?
Are bad bots really ‘bad’? Usually, they are being created by the malicious actors to maximize their gain from attacks – with the techniques including card cracking, credential stuffing etc. and are used across different sectors. After buying a range of leaked passwords, the malicious actors then place the bot with the input on different sites to gain access.
With studies revealing most online users reuse the same password for multiple sites – it is a good possibility of success for the hackers. A robot can try on thousands of credentials every minute, and the seized user accounts are found to be used to commit fraud, online scams, etc.
Furthermore, card cracking bots are used to create fake profiles and buy products with stolen credit card information. However, doing this manually is not possible, and machines can do such work effortlessly in real-time.
These techniques generally cause reputational damage for a brand, even if a business is not subject to a data breach. Besides, it affects consumers’ loyalty and trust, creating a negative brand perception.
As this robotic ecosystem becomes more complex, brands should analyze how a regular user journey looks like. With that, they can infer the unusual activities. For e-commerce companies, customers generally look for stock levels in many different postcodes. However, if a particular user searches for every postcode in the UK – this could be a bot behavior.
Basically, human users may forget their username, password, or the combination a couple of times – and not some ten thousand times! Hence, the “block all bots” approach cannot work in this modern digitized marketplace.
Undoubtedly, businesses need to focus on the intent of the website traffic via user journeys. This would help brands to differentiate between the good and bad bot behavior, and also the human and non-human traffic.