Will artificial intelligence be the future of industrial cybersecurity?

A technological revolution called Industry 4.0 is driving the digital transformation of industry. Traditional processes and technologies are being replaced by smart devices, automated machines, and advanced forms of computing. Enterprises have invested billions of dollars in artificial intelligence and automation. Relevant data shows that by 2025, the Industrial Internet of Things (IIoT) alone will become a market worth 500 billion U.S. dollars.

However, while companies are connected to the outside world through the Industrial Internet of Things, they also provide opportunities for cybercriminals. The integration of IT/OT (the integration of information technology IT systems and operational technology OT systems) may even cause security disasters. The US Cyber ​​Security and Infrastructure Agency (CISA) stated that due to IT/OT integration and the resulting threats This has led to an increasing number of ransomware attacks.

Challenges of Industrial Cybersecurity

Data shows that 41% of ransomware attacks in 2020 are directed at OT (Operational Technology, referred to as “OT”); during the new crown pneumonia pandemic, Internet of Things (Internet of Things, referred to as “IoT”) attacks have soared by 700 %, the number of infected IoT devices has increased by 100%.

Here are five reasons why IoT and OT devices have become popular targets for cybercriminals:

1. OT lacks sufficient security: OT and IoT devices lack strict security, and their security is usually considered after the fact, which makes them attractive targets for ransomware attacks. More than half of manufacturers believe that OT assets are vulnerable to cyber attacks.

2. Lack of updates and software patches: Researchers estimate that there are millions of unpatched IoT and OT devices on the market. In addition, traditional devices also lack the ability to update firmware, which puts IoT devices at risk of permanent use.

3. The gap between talents and resources is getting bigger and bigger: There is a shortage of people with OT security skills and knowledge. Usually, security teams have to face massive amounts of security data, and the workload far exceeds the capabilities of employees.

4. Possibility of causing widespread damage: The ransomware attack on Colonial Pipeline shows the potential destructive power of cyber attacks on OT infrastructure. Its attacks may cause production interruption, supply chain interruption, and cause widespread panic and uncertainty . According to Gartner, cyber attacks may even cause casualties.

5. Increased spending by attackers and high bargaining power: Every minute of business interruption may cause huge losses, and paying the ransom seems to be a prudent choice. Because of the important value of the target, cybercriminals often make aggressive demands and successfully force the victim to pay.

AI empowers industrial cyber security

Network security in Industry 4.0 cannot copy traditional computing environment solutions, because the magnitude of equipment and related challenges in industrial networks are much higher, which provides a place for artificial intelligence (AI) and machine learning (ML).

Artificial intelligence and machine learning can be used to build lightweight endpoint detection technologies. Machine learning can make up for the deficiencies of security teams and help monitor incoming and outgoing traffic to understand any behavioral deviations in the IoT ecosystem; artificial intelligence can help discover devices And hidden mode, processing large amounts of data at the same time. This is an indispensable solution when IoT devices lack processing capabilities and require behavior-based detection capabilities.

At the same time, artificial intelligence and machine learning technology are also a double-edged sword: attackers can weaponize artificial intelligence to automatically perform tasks such as target selection or attack time to avoid detection. Deep forgery, human imitation, and artificial intelligence-driven password guessing have also become important threats. The abuse of artificial intelligence and machine learning is a worrying trend, and with its adoption in the business world, this trend seems to grow at the same time.

Companies need to pay special attention to any potential malicious use of their own artificial intelligence systems. For example, cybercriminals have been able to copy the machine learning model of Proofpoint email protection and manipulate it to allow malicious emails to pass through filters. All in all, organizations must carefully consider safety-related issues in order to successfully embark on the journey of Industry 4.0. As networked devices take over traditional technologies, it will become increasingly difficult to counter cyber threats without the help of advanced artificial intelligence technology.

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