Artificial Intelligence Trends in Security for 2018

2018 looks poised to be a breakout year for artificial intelligence (AI) in the security field. And it’s likely just the tip of the iceberg. Gartner Research anticipates the widespread adoption of AI technologies in core business areas across all sectors over the next 2-5 years.

Artificial Intelligence sounds like an intimidating topic, but it’s actually quite straightforward. AI is any kind of software or computer algorithm that is able to complete what people would consider an ‘intelligent’ task. Many tools already in use by security teams actually fall under the AI umbrella. For example, video analytics tools for facial recognition or motion detection in use today are actually quite sophisticated forms of AI.

Over 2018 and beyond we’re going to see security teams at all sized institutions use AI technologies to enable the kind of security presences previously only possible with an enterprise-scale budget.

New AI tools will offer valuable insight into our security and operational environments, automate even more tasks so your staff can focus on core security objectives, and give rookie security officers the technologically-powered expertise to function like your most experienced veterans.

AI is poised to become a powerful force multiplier for many security practices: 

Advanced Analytics

Security analytics are driven almost completely by AI technologies, and in 2018 we can expect to see even more advanced analytics applications appear in security systems. Advanced behavioral analytics currently in development will be able to identify changes in an individual’s actions from data culled from access logs and video feeds. This analysis will be pre-processed for your security officers, so the data is ready and waiting for them to review and determine threat responses.

Other analytics tools in development will improve forensic responses. These tools can automatically search back through log or video archives to analyze past behavior for any notable events and automatically add them to case files.

One of the primary purposes for implementing AI systems is the automation of routine or fatiguing tasks so staff can focus on the most productive security efforts. This could include video searches as described above, as well as live feed monitoring. Instead of staff dividing their attention among all feeds, and potentially misidentifying something half-seen out of the corner of an operator’s eye, AI analytics packages are able to devote full attention to every feed  simultaneously and alert human operators to the items they actually need to see.

Managing Information

Side-by-side with the rise of AI tools in coming years, we’re going to see a rise in Big Data techniques. Fortunately, managing the flow of large volumes of data is another area where AI can tackle busy work for security teams.

The catchphrase ‘Big Data’ refers to the collection and analysis of very large data sets that has only become possible with the rise of high-volume digital storage devices. Big Data analytics techniques are powerful, but cumbersome. AI tools will aid human analysts in taming this information flow, detect patterns, and create actionable intelligence.

We will also see AI ‘machine learning’ aid in reporting. AI algorithms can monitor search queries, even repeated sorting and filtering activities, and automatically complete them for analysts.

Optimizing Work

This key strength of artificial intelligence systems—their ability to process large volumes of data faster than people—will also help organizations more effectively deploy various kinds of resources.

Solutions are already in development for physical asset management or for fleet management, where it’s best practice for vehicles or assets to follow a balanced or rotated use schedule.

Fleet supervisors are quite familiar with the tendency for drivers to select a fleet’s newest vehicles. This can wreak havoc on maintenance schedules, but it takes a considerable amount of manual effort for a supervisor to track vehicle usage in a way that creates an effective rotation schedule. New fleet management dashboards could include an AI agent that could analyze usage against maintenance and depreciation schedules and rotate vehicle selections on the fly.

In high security settings where randomized guard tours are needed, AI tools may even soon help balance optimal patrol routes with sufficient randomness. Many enterprise activities that we now measure using business intelligence techniques will become further supported by AI tools. If an activity can be measured, analyzed, and optimized, machine learning systems will come to have a place.

Future Directions

Video analytics is certainly an area that will continue to improve, with more advanced motion and object recognition becoming available. Advanced behavioral analysis tools are just now reaching the production stage. Some law enforcement agencies even piloted ‘predictive policing’ tools recently that helped them target high-risk areas for future crime. The initial results were positive enough that we will certainly hear more about this in the future.

AI’s future in security operations looks bright, and it will likely only get brighter.

Contact Real Time Networks today to learn where new security AI can take your organization.