Why is industrial cybersecurity critical in manufacturing?


Why is the manufacturing sector facing cybersecurity challenges?

Over the next five years, cybersecurity in the manufacturing sector is expected to see robust growth, with estimates predicting that the sector will be worth approximately $22.9 billion by 2027. With help from researchers, investigations into increasing attacks on manufacturing facilities such as OT systems, and increasing interest from business and government, the industry has previously amassed an arsenal of awareness and surveillance offerings. With that in mind, now is the time to take a look at how cybersecurity in the manufacturing sector will expand further and what challenges it will face in the coming future so that the industry can use this information to shape their security strategies. or to regulate. We’ve seen many cases last year where cybersecurity failed, cybercriminals tried to add toxic substances to Florida’s water supply by hacking into the fabric of a city. An aircraft manufacturer’s confidential customer data files were breached and leaked on the Internet. At the same time, more and more services are moving to connected operations to authorize the latest efficiencies. Now the question arises of how we can keep our facilities within these increasing dangers and opportunities. One answer could be threat intelligence?

To recognize where the industry is heading, it is vital to examine the modern state of affairs. Protecting industrial infrastructure is a complicated task as it means using many tools for every level, including field devices and controls to monitor ICS and corporate IT. These are technologies for controllers from different manufacturers, networks, computer security and the overall protection control for enterprises. The number one cybersecurity in the manufacturing sector is the timely detection and removal of threats to endpoints and the network to protect the perimeter. If the commercial site has complex automation and control systems, it is vital to protect it from accidental failures and planned cyber-attacks. Some examples are substation or power plant automation, discrete or continuous process automation, distributed or centralized control systems, field, supervisory or remote control systems. It is vital to apply special tools to detect small deviations in general performance indicators, for example an indicator of the pressure in an oil refinery tank or power plant, in order to act before a failure occurs.

As operational technology (OT systems) becomes more complex with all kinds of devices, distant connections and geographically dispersed facilities, so does security. Different tools work for special needs. Some require integration and each has its own control panel. As a result, dealing with security for the entire system becomes the most challenging undertaking for enterprises. Configuring each tool sequentially and handling everything manually can be hard work and can ultimately lower the level of safety if it’s miles ineffective. Different responses do not share threat intelligence with each other and there is no visibility across the entire OT system.

Addressing this difficult approach by bringing all security elements together in one place, growing an ecosystem that gives customers access to all possible answers and services, and adapting to the tasks of small, medium and large enterprises. It should provide a single platform to handle all security tasks, including those of third-party services. For example, all teams involved in OT security could be able to access the essential facts and processes. A key feature of the platform should be to monitor and process security activities from exceptional sources, be it an anti-malware agent on endpoints, EDR, threat intelligence, SIEM or any other tool, and correlate them with activities in the IT environment. network.

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Analytics Insight

Analytics Insight is an influential platform dedicated to insights, trends and opinions from the world of data-driven technologies. It tracks developments, recognition and performance of companies in the fields of artificial intelligence, big data and analytics around the world.

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