Botnet attacks mean high stakes for companies in cybersecurity war over online data
Remember that old game from back in the day – Rock ‘Em Sock ‘Em Robots?
These days, the financial industry is involved with its own, similar game – only this time there’s no “ro” in “robots” and the stakes are higher. There is a battle of the bots and it’s quickly escalating.
It’s important to understand that not all bots are bad. Halloween is coming up, so forgive the incoming metaphor, but just like witches, there are good bots and there are bad bots. Distinguishing between the two isn’t nearly as simple as a wardrobe change. Bad bots are becoming increasingly sophisticated, making it easier to evade detection.
In the simplest terms, bots run automated tasks over the Internet and perform simple and repetitive tasks much faster than your average person could. That includes things like chat bots and personal assistant bots. This isn’t a new phenomenon, but advances in machine learning and processing have made them more popular. The most sophisticated bots can mimic humans, “understand” personal preferences and even respond on your behalf. For the banking industry in particular, the adoption of bots and automation is helping them connect with millennials. It’s exciting stuff, but there’s also the scary parts, too.
What happens when bots that have become so good at mimicking humans are used for ill means? Think ticket scalping, price scraping, or content theft. Ticket scalping bots in particular, have drawn the ire of fans and politicians alike – from proposed bans in New York State to those put forth in Ontario. The advertising industry also has been hit hard by bots, with online ad fraud costing advertisers an estimated $7.2 billion globally this year.
The Internal Revenue Service fell victim to a bot earlier this year too, when hackers used an automated bot and stolen social security numbers to try to establish accounts with IRS systems.
No one is immune to these types of attacks and attempts, but there is a way to protect organizations from the bad ones – a way to easily determine whether the entity on the other side of the screen is a good user or an auto-scripted bot orchestrated by a bad actor.
With behavioral biometrics (BB), you can distinguish good users from bad actors and bad bots from good bots without causing customer friction. We can even tell when bad bots are hiding within good bots (as they sometimes do). By leveraging BB, users’ reliance on the convenience of good bots isn’t being interrupted or disrupted. When you implement this type of security system, everyone wins – except for the bad guys and the bad bots.
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