Risk Based Authentication
Published By: https://accelerite.com/products/neuro/
Identity fraud is the major security concern for most of the organizations doing Internet businesses today. It has an influence on the cost of doing business, increasing customer anxiety and thereby inviting government regulation. The best way to prevent identity fraud would be to adopt a layered approach to security. Fraud detection would be a critical security layer, which would include Risk-based Authentication as a mechanism for fraud detection.Checkout Accelerite Neuro for more info.
Risk-based authentication is a technique that uses both contextual and historical user information, along with data supplied during Internet transaction, to assess the probability of whether a user interaction is authentic or not. Let us see what contextual and historical user information mean. The contextual information typically includes the traditional username and password in addition to the following information like who the user is, from where they are logging in (IP addresses, location information - city the user is actually in at the time of communication), what kind of device they are using. Historical user data includes specific attributes provided from the session as well as user behavior and transaction patterns. This information represents an additional authentication factor that supplements the username and password, making this an enticing multifactor authentication technique.
The risk-based authentication model is built on a rule engine that takes into account multiple combination of parameters such as IP address, location etc. as described above. This data can be used to create a pattern to compare with those in future authorization attempts. The rule engine checks each transaction to see if it matches any pre-determined pattern for fraudulent transactions. Since online fraud patterns evolve rapidly, the rule engine must deploy automatic pattern recognition and self-learning capabilities, in order to quickly find new patterns to prevent fraud. A machine learning, anomalydetection system can also be used to address the shortcomings of rule-based systems. https://accelerite.com/products/neuro/
In risk-based authentication, much of the contextual data is susceptible to fraud. Although it is difficult to replicate the contextual data, a fraudster could try and spoof with the intention of fooling the authentication system in which case the fraudster would have to know all the specific attributes that the authentication algorithms and then painstakingly replicate the attributes. Fortunately, the difficulties in exploiting this, along with the availability of historical data that cannot be spoofed, make riskbased authentication more effective. Click here.
Risk-based authentication enables Internet businesses to assess security risks and use out-of-band challenge and response mechanism as a second factor authentication only when necessary. Risk-based authentication works behind-the-scenes and has a minimal impact on users. Risk-based authentication can occur at initial log in and may also be performed at subsequent interactions during secure sessions as well as during high-risk transactions.
Summary: Accelerite Neuro are a software provider that has set out to "Simplify and Secure the Enterprise Infrastructure". Neuro works with your existing SSO and MFA solutions, treating them as authentication options. Visit this site to learn more: https://accelerite.com/products/neuro/