User Threat Quotient (UTQ)

Prevent users
from turning hostile
User Threat Quotient
Security intelligence to spot risky users at a glance
Today s network attacks center on the user, making users the weakest link in the security chain. Statistics reveal that 80%
of security risks are caused by network users. A network generates huge amount of data. This data contains enough cues
to offer patterns of human behavior that can be used to predict and prevent attacks. However, comprehending and corelating data out of various logs and reports to get meaningful information requires time and skills. Besides, it carries the
risk of human oversight. Organizations need a security model to harness this information and start interpreting network
traf c as user-generated traf c comprising of intentional and unintentional acts.
The User Threat Quotient (UTQ) harnesses information derived out of network traf c and offers patterns of user behavior
to determine risky users in a network. UTQ is available on Cyberoam s Next-Generation Firewall and UTM appliances.
Spot Risky Users at a glance with the User Threat Quotient
User Threat Quotient (UTQ) is a score assigned to each network user which provides actionable intelligence to IT security managers on
risky users and their network activities that pose a risk to the network. IT security managers can further investigate the cause and take
appropriate actions like ne-tuning security policies and controls, imparting security awareness training, warning, cleaning the
infected machine, and more to stop or remediate security attacks.
The UTQ graph showing users who pose High risk, Medium risk, Low risk
In its current phase, Cyberoam s User Threat Quotient (UTQ) studies the web behavior of users by analyzing massive data of allowed
and denied web traf c for web categories like IP Address, P2P, Phishing and Fraud, Porn, SPAM URL, Spyware, URL Translation Sites
and more that pose security and legal risks. The UTQ graph offers details on web behavior of users to the IT security managers.
A simple click on a bubble, which represents a user, provides information on websites visited, number of attempts, and website
categories all of which contributes to a user s Threat Quotient.
Here are a few examples of a user s web behavior that leads to a high User Threat Quotient :
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The user unknowingly visits a malware-infected website, which infects the user s machine
The user is led in to visiting a Phishing or fraud website or a Spam URL
The user visits IP addresses instead of a URL
The user visits a P2P website or URL translation site to conceal activities or bypass the rewall
The user visits a gambling website/adult website, which poses a legal or compliance risk to the organization
The User Threat Quotient helps CSOs / IT security managers by:
Spotting risky users at a glance without manual efforts to co-relate network logs and reports
Eliminating the risk of error and oversight while dealing with huge amount of data contained in network logs and reports
Removing complexity in analyzing terabytes of logs to identify user behavior by making actionable security
intelligence readily available
Facilitating corrective actions by ne-tuning user policies and managing risks arising from privileged users
Eliminating the need for SMBs to invest in separate SIEM tools to spot risky users
Enabling investigation into the spread of risk within the network with useful insights into network
activities of risky users
Allowing administrators to identify and educate users who pose security risks
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