Cybercrime is on the rise, and asset protection is of increasing global importance. According to McAfee and the Center for Strategic and International Studies, it’s estimated that global cybercrime costs soared to an estimated $600 Billion. As enterprise security races to transform itself to meet the ever-changing threat to cybercrime, attackers are becoming more sophisticated and identifying new ways to infiltrate an enterprise to take advantage of new weak spots – both physical and digital. And while greater connectivity has brought greater risk along with it, enterprises need to adopt a unified approach to address both fronts if they hope to get ahead of malicious attacks.
Past enterprise systems relied on onsite security and digital systems to protect data, but these systems did not always work together, creating silos that limited the analytic potential and value of data. The changing cybersecurity landscape is demanding a different approach that will bridge the strength of leading network security, alongside new advanced digital technologies. However, monitoring these environments is complex, as large quantities of data spanning physical and digital needs to be processed, analyzed and managed.
Enterprises need to change their approach to protecting their valuable data. Initial reluctance to provide a coordinated approach to security may stem from the habit of segmenting data at the department level, which was once used to drive business decisions. Today, most organizations still need to develop a coordinated, converged approach to incorporate security measures across the board for all their data. This means adopting a new mindset, from the defense to offense.
In today’s world, adopting advanced technologies can not only help detect threats as they occur, but even predict future attacks. Artificial Intelligence (AI), Edge analytics, Predictive and Reactive analytics, Machine learning algorithms, and wireless features like RFID, are creating new opportunities to take a proactive stance. As these technologies converge into unified solutions, companies are finding new value in the data they can harness to help fight crime and improve overall security and situational awareness.
As companies apply video intelligence alongside AI, machine learning and video analytics to bridge the physical and digital security gap, they will set their teams up for future success and enable better collaboration across several business streams. Thankfully, there’s no need to recreate the wheel.
AI for video analytics is already showing promising results in the global marketplace for crime prevention and security, including the ability to catch suspicious activities or predict them before they happen. In the case of a recent major Asian cyber bank heist, over $60 Million and various assets were recovered within three days thanks to technology convergence. At the core of these capabilities is the Internet of Things (IoT), which enables access to data in real time, alongside scalability and video analytics. According to IHS forecasts, the IoT market will grow to an installed base of 75.4 billion by 2025, with analysts predicting security and industrial asset management among the biggest drivers.
When cyber and network security technologies converge, it has the potential to change the future of cybersecurity. Together, these technologies can not only detect threats and stop them but predict patterns of suspicious activity and prevent future attacks before they occur. This kind of convergence is successfully stopping crime in markets around the world by tapping multiple data streams from mobile, CCTV, IP and geo location information, and harnessing facial recognition and AI-powered edge computing.
Cybersecurity convergence is the future, and the best way to prevent malicious attacks. In some cases, it can be used to access and analyze suspicious activity and stop crime before it happens. By coupling the best in network excellence and technology advancements, there is great promise of how a unified approach can be both shield and sword in the battle against cybercrime.
By-line by Dr. Spincer Koh, Gorilla Technology
A thirty-year technology veteran, Dr. Spincer Koh is the CEO and co-founder of Gorilla Technology, a provider of video intelligence and IoT Big Data solutions that support a wide range of video-centric and content management applications for retail, enterprise and surveillance. Gorilla Technology’s machine learning and deep learning video analytics help to identify, analyze and extract information from digital content to drive business intelligence solutions and automation. Before founding Gorilla Technology, Dr. Koh was the deputy director at the Institute of Information Technology CSIST, Taiwan, as well as a director at the Research Center for Information Technology Innovation, CSIST, the highest research and development authority for Ministry of National Defense, Taiwan.