Skip to: contents, mainnavigation

DetACT for Online Banking

Banks are confronted with the reality of successful attacks on their online channel, through vectors such as phishing and online banking trojans. The proven DetACT for Online Banking technology provides an important new tool to Financial Institutions to thwart these malicious attacks. Instead of unsuccessfully trying to close the gaps in inherently insecure client systems and browsers, it delivers real-time automatic detection of fraudulent online banking transactions. Multiple metrics are extracted from the raw transaction data and scored for their suspiciousness by an expert system. This system is constantly improved by intelligence gathered from the digital underworld and attack patterns learned from Fox-IT’s fraud investigations. When a fraudulent transaction is detected, DetACT for Online Banking can help to abort the transaction and serves as a rich source of data to support further investigations. DetACT for Online Banking provides for a care free online banking experience for consumers.

Internet banking is now an everyday affair and we cannot imagine life without it. Is it actually safe? Consumers believe it is. Secure HTTPS connections, TAN codes, tokens and other methods secure the online banking channel. Cybercriminals have actually adapted their methods, so that a number of these measures are being bypassed. They focus their phishing activities and malware on the unsuspecting customer, whose PC, laptop, iPad or smartphone is difficult to secure fully. Cybercriminals manipulate the transactions customers carry out with online banking, by quietly hitching a ride on connections with the bank’s webservers. Very quickly and unnoticed, they siphon money out through fraudulent transactions, via accounts of so-called money mules

Analysing communications, detecting anomalies

With online banking the TCP/IP communication channel contains a wealth of details. That’s why DetACT-OB taps into the raw data, extracts dozens of features from the traffic streams and stores the information in databases. Then it carries out a direct – real-time – analysis of the transactions. DetACT-OB searches for anomalies which (might) indicate fraud, by testing against a multiplicity of features. The more anomalous features, which switch from green to red, as it were, the stronger the fraud signal. It can be compared to a spam filter which regards an e-mail as spam if it meets a number of characteristics.All sorts of characteristics could indicate fraud; it’s often not just a single parameter, but a combination of them. Several examples might be:

  • The customer is suddenly using a different operating system, a different screen resolution, a different browser, or is banking from a different country than usual.
  • The way in which the online banking website is being browsed, or the speed at which this is happening, is a signal that it’s not a flesh and blood person who is banking but an automated ‘bot’ or virus.
  • A transaction is using a known money mule account, fields are completed a little differently than usual, or a suspicious IP address is used.

In this way DetACT-OB holds every anomaly for inspection and the system triggers an alert when it suspects a transaction of being ‘fraudulent’. This sometimes even occurs before the customer, or the cybercriminal, has actually authorised the transaction! With its ‘live view’ feature DetACTOB offers the ability to make real-time notifications, subject to human interpretation, because experience has taught us that the human eye is extremely efficient and effective in drawing the distinction as to whether a transaction is fraudulent or not.

More information

Need more information? Please download the productsheet DetACT for Online Banking here.

For more information please contact Eward Driehuis, productmanager DetACT, via driehuis@fox-it.com or by telephone via +31 (0) 15 2847 999

Whitepaper

A comprehensive whitepaper on the DetACT solution is readily available. Request your copy now by sending an email to detact-sales@fox-it.com