Bridging the Gap Between Physical and Digital Security Using AI

Cybercrime is on the rise. In 2017, it’s estimated cybercrime cost the world about $600Bn. While enterprise security is transforming to meet the growing threat of cybercrimes, harnessing the power of new technologies can help provide the highest degree of protection from sophisticated threats that may be hard to detect through conventional security means.

Network and data security can fight cybercrime, but there must be convergence of existing security approaches, alongside new advancing technologies, as the way forward. Artificial intelligence (AI) for video analytics shows great promise in global markets for crime and security, including the ability to catch suspicious activities or predict them before they happen.

Monitoring the network environment is becoming increasingly complex, as ever-larger quantities of video and IoT sensor-related data needs to be processed, analyzed and managed in context. However, this data can often become siloed, limiting its analytic potential and value.

When working together, real-time analytics and AI can help identify threats that are much harder to discern, by accessing large and diverse data sets in real time. Commonly referred to as “unknown unknowns”, AI goes beyond traditional security layers to extract suspicious activity and identify data that is aligned with attack structures. This is the great promise of AI and can be the shield and sword in the battle against cybercrime.

Enterprises are beginning to realize the promise in AI in their security solution. ESG research reports 12 percent of organizations have already deployed AI-based security analytics, and 27 percent having deployed AI-based security analytics on a limited basis. The momentum gained so far this year is impressive, with continued growth expected.

Incident detection and response is the primary concern among enterprises when it comes to cybersecurity. Traditional security systems haven’t been the best at early detection, hence the skyrocketing loss in revenue experienced due to major cybersecurity attacks in recent years. However, AI, when working in tandem with video intelligence, IoT technology and machine learning with video analytics, can help identify, analyze and extract information in real-time and turn into decision-enabling data, which in turn is helping to fight crime and improve overall security and situational awareness – in real time. This is huge as it can stop the criminal activity in real time, while providing a greater view into the enterprise’s entire system and halt additional activity, as its happening, in its tracks.

The same report from ESG also suggests that while only 30 percent of cybersecurity professionals report feeling knowledgeable about AI/machine learning, and its application to cybersecurity analytics, the reality is AI is truly at the forefront at being the technology that can promise better security and an improved operational efficiency. As machine learning continues to evolve however, convergent security — coupling the best in network excellence and technology advancements — will lead the way helping to combat 21^st century cybercrime. The easier data is to access and analyze, the quicker suspicious activity can be flagged, and nefarious activity stopped before it happens. This can only happen when true integration of core technology such as AI, multiple threat feeds and cloud scale computing come together.  

At Gorilla Technology, we are aiming to dramatically disrupt the security market by applying video intelligence and IoT technology alongside AI and machine learning with video analytics, to help identify, analyze and extract information in real time and turn it into decision-enabling data. Thanks to the growing convergence of IoT and advancing technologies, we are now better able to intelligently analyze petabytes of structured and unstructured data, helping organizations not only predict suspicious activities before they occur, but help crack down on local and cross-border cybercrimes, such as in the case where we were able to foil a major Asian bank heist — recovering $60M within three days.

Moving ahead, the easier data is to access and analyze, the quicker suspicious activity can be flagged, and crime stopped before it occurs. Convergent security is the future, with AI at the heart of its potential.

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