A technological revolution known as Industry 4.0 is promoting the digital transformation of industry. Traditional processes and technologies are being replaced by intelligent devices, automated machines and advanced computing forms. Enterprises have invested billions of dollars in artificial intelligence and automation. Relevant data shows that the Industrial Internet of Things (IIoT) alone will become a market worth 500 billion dollars by 2025.
However, while enterprises connect with the outside world through the industrial Internet of Things, they also bring opportunities for cybercriminals. The integration of IT/OT (the integration of IT systems of information technology and OT systems of operational technology) may even lead to security disasters. The United States Network Security and Infrastructure Administration (CISA) said that due to the integration of IT/OT and the resulting expanded threat surface, blackmail software attacks are increasing.
Challenges of industrial network security
According to the data, 41% of extortion software attacks in 2020 are targeted at OT (Operational Technology, referred to as “OT”); During the COVID-19 pandemic, Internet of Things (IoT) attacks increased by 700%, and infected IoT devices increased by 100%.
Here are five reasons why IoT and OT devices have become popular targets of cyber criminals:
1. OT lacks sufficient security: OT and IoT devices lack strict security. Their security is usually considered after the fact, which makes them attractive targets for blackmail 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 makes IoT devices face the risk of being permanently utilized.
3. The gap between talents and resources is becoming larger and larger: there is a shortage of personnel with OT security skills and knowledge. Usually, the security team has to face massive security data, and the workload far exceeds the ability of employees.
4. Possibility of causing widespread damage: The blackmail attack on Colonial Pipeline shows the potential damage of network attacks on OT infrastructure. Its attack may cause production disruption and supply chain disruption, causing widespread panic and uncertainty. Gartner said that cyber attacks may even cause casualties.
5. Attackers’ increased spending and high bargaining power: every minute of business interruption may lead to huge losses, and paying ransom seems to be a prudent choice. Because of the important value of the target, cybercriminals often make radical demands and successfully force the victim to pay.
AI enables industrial network security
Network security in Industry 4.0 cannot copy traditional computing environment solutions, because the order of magnitude of equipment and related challenges in industrial networks is 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 technology. Machine learning can make up for the shortcomings of security teams, help monitor incoming and outgoing traffic, and understand any behavioral deviation in the IoT ecosystem; AI can help discover devices and hidden patterns, and process a large amount of data at the same time. This is an indispensable solution when IoT equipment lacks processing capacity and needs behavior-based detection capability.
At the same time, AI and machine learning technology are also a double-edged sword: attackers can weaponize AI to automatically perform tasks such as target selection or attack time to avoid detection. Deep forgery, human imitation and AI driven password guessing have also become important threats. The abuse of AI and machine learning is a worrying trend. With its adoption in the business world, this trend seems to grow synchronously.
Enterprises need to pay special attention to any potential malicious use of their own AI systems. For example, cybercriminals have been able to copy the Proofpoint e-mail protection machine learning model and manipulate it to allow malicious e-mail to pass through the filter. To sum up, the organization must carefully consider safety-related issues in order to successfully start the journey of Industry 4.0. As networked devices take over traditional technologies, it will become more and more difficult to combat network threats without the help of advanced AI technology.
