ANOMALY DETECTION MODULE
WHAT IS A DATA ANOMALY?
It is any Data event that does not fall within the results you consider “normal”. For example, if your user has a 9 to 5 job yet consumes 95% of their data between the hours of Midnight to 5 AM, that is a Data Anomaly.
The Anomaly Module is the software component that tracks the mobile data usage on the device and compares it in real-time to configured anomalies and then alerts the appropriate person inside the carrier or on the user side of these anomalous events. These events can be critical for cost, security or marketing reasons. Once these anomalies are configured the Anomaly Module will compare the real time user data generated on the devices against the configured anomalies and trigger the necessary alarms to ensure you are alerted of these events as quickly as necessary. This module can be tracked for your own purposes or re-sold as a service to your Enterprise customers.
Consider the following example. A company has two employees who use their corporate laptop with USB modem to connect to a Public Network while at a Coffee Shop at 2 AM and upload 200Mb of data. The first employee is the Sales Representative for the Asian Pacific territory doing his job by sending his customers product presentations. The second employee is a senior software developer uploading raw source code files to Google Docs.
These are completely different data events that would go undetected by Enterprises.
The Anomaly module would immediately alert the Administrator at the Enterprise of this event, store the event log in the Audit Trail and allow the company to run reports on the frequency of these events.
“OUT OF THE BOX” PRE-CONFIGURED ANOMALY ALERTS FOR:
- Off hour usage
- Unusually large file transfers
- Device inactivity
- Unusual network interface usage (LAN, Wi-Fi, Cellular)
- Work vs. personal usage
- Projected telecom overage charges
- Device roaming
- Dramatic increases or decreases in activity
- Usage of non-sanctioned / new devices
Please see a sample Anomaly report table below:
