User Behavior Analytics: Preventing Security Threats
By Veriato - November 04, 2019
Insider threats have become a much more serious issue since technology has made it easier to transmit, receive, and transport large amounts of data. A shocking statistic from IBM shows that insider threats have an “$8.76 million global average cost” to companies.
The costs are not only from the data loss and penalties but from loss of confidence in the brand, reduced sales, legal fees, and possibly compensation to those affected by the data breach.
What is User Behavior Analytics
User behavior analytics can record and analyze user behavior on the network, and over time, it builds up user-profiles and definitions of each individual’s normal behavior. The longer someone is monitored, the more accurate the system becomes.
User behavior analytics is just one of the tools that are integrated into our Insider Threat Detection and employee monitoring software solution. It collects data about how employees use their company-owned devices. Over time it analyses this data to create custom profiles for each staff member for their usage of devices, apps, the web, and more.
How Can User Behaviour Analytics Prevent Threats?
User behavior analytics can be used to continually monitor all company data and alert management if there is an anomaly or a shift from normal employee behavior. To a large degree, this could help to prevent or reduce the impact of an insider threat. However, this technology has since expanded, now taking into account other factors to create a much more tightly integrated security solution.
User and Entity Behavior Analytics (UEBA) expands the use of behavioral analysis to include other “entities.” This means that user profiles are not the only way that the system can detect a threat. User behavior is instead combined with the analysis and monitoring of IoT devices to provide an even broader view of your organization.
With a full overview of the office environment, the software creates profiles of each user and device usage not only to report events but also to predict and prevent threats. It can even detect more complex attacks where numerous user logins or devices are being exploited.
AI User Behavior Analysis: Cracking Down on Security Threats
While the analysis of user behavior has been around a while now, artificial intelligence is taking detection and prevention to entirely new levels of cybersecurity. Here are a few of the techniques that are used in the AI-driven analysis of users and entities to provide full protection.
- User and Entity Usage Profiles - Overall usage profiles are created for each entity, based on their activities over time. By analyzing all major entities in the office, not only are individual profiles developed but a complete overview of how they interact with each other.
- Web Activities - Normal website usage is monitored and analyzed continuously. Known bad websites can be blocked, and any usage of the dark web reported.
- Email and Chat - Constant recording, content capture, and analysis of all communications result in an effective way to alert incidences and also for investigating any compliance issues.
- Live Writing Analysis - Writing analysis and reports has evolved far beyond that of flagging predefined terms. Instead, AI can analyze writing live and determine the writer’s opinions and sentiment. This can be incredibly useful for flagging employees who are unhappy about their job or maybe experiencing external stresses (such as financial issues).
- Geofencing and Geolocation - By monitoring device location and boundaries, the monitoring system can flag unusual activity, such as a company-owned device leaving the premises or geofence without authorization.
- Files Tracking - As file usage and movement is monitored live, unusual activity or attempted transmission of sensitive data can be flagged or blocked.
- Network Activity - Normal network activity is also profiled, as to allow the AI system to notice any unusual connections and from which device. It can also detect when devices connect to external networks, or when an unauthorized device is attempting to connect to the company network.
Developments in AI mean that all of this can now be monitored live and simultaneously for real-time alerts. AI can even be set up to take action to prevent or block insider threats before they occur. It gives a new level of security to companies, reducing the need to monitor staff manually and allowing everyone to focus on the business while the AI takes care of cybersecurity.
Is Behaviour Analysis Really Required?
You might have doubts about if behavior analysis and employee monitoring software is worthwhile. It may sometimes seem that way before your company has a data breach. However, data breaches are so costly to a company financially and in the form of reputational damage (resulting in lost business and possibly lawsuits), is it really worth the risk?
Employee monitoring software also provides more benefits than just insider threat protection. It can be used to motivate employees, reduce errors, increase efficiency, and increase output. This combines to make powerful changes in how the business operates, as well as making it more profitable for the same amount of employees. In the end, employee monitoring will create savings and increased revenues that normally more than cover its cost.
7 Ways to Make your Workforce More ProductiveMay 07, 2019
Employee Tracking: Uses and BenefitsNovember 22, 2019
5 Tips to Choose the Best Internet Monitoring SoftwareNovember 18, 2019
- Cyber & Data Security
- Employee Monitoring Software
- Insider Threat Detection & Prevention
- Data Loss & Theft Prevention
- User Behavior Analytics
- Ransomware Prevention and Detection
- User Activity Monitoring
- Artificial Intelligence - AI
- Forensic & Employee Investigations
- Machine Learning
- Cyber Security Awareness Month
- higher education