Digitalisation and the growing network of industrial machines and systems mean an increased risk of cyber attacks on companies and organisations around the world, as well as an increase in the accuracy and complexity of these attacks. According to the Allianz Risk Barometer, cyber incidents have risen to 1st position to become the most important business risk in 2020.
But Artificial Intelligence (AI) is changing the game for cyber security. Do you know what Cyber-Resilience is? It is the ability of organisations to prepare for, protect against, detect, respond to, and recover from potential cyber threats (internal or external).
AI technologies help companies and security analysts with limited resources in this area to address this danger with confidence and speed, pushing them to become more cyber-resilient.
The lack of preparation of companies
As a general rule, companies are unprotected against this type of attack, mainly for the following reasons:
- Lack of training or resources to deal with them.
- Lack of evidence to test the real capacity of prevention and/or reaction.
- Lack of specific technical measures to mitigate them.
- Lack of quality systems to stop sophisticated attacks
One of the most common targets of so-called Malwares (“malicious software”) in the business environment is information theft, identity theft and the paralysis of computer networks. Companies increasingly accumulate highly sensitive data in their hyperconnected information systems (lloT), which work together with data from strategic partners to drive the digital economy.
This increases the dependency of organizations on Internet-based technologies, exposing businesses in all sectors to an increasingly large and volatile threat environment.
Large companies have already been victims of security breaches in the past, but the digital transformation has made companies of all sizes potential victims of cybercrime. For this reason, today’s businesses need to invest in cyber defense systems that protect them from highly damaging situations.
AI and cyber security in context
There have been four main factors that have boosted the popularity of these two factors working hand in hand in today’s business environment:
- Emergence of new disruptive technologies (Artificial Intelligence and Machine Learning)
- The increase in cases of cyberthreats.
- Increased data protection concerns.
- More vulnerable wifi networks
These factors facilitate the commercialisation of new, smarter and more effective threats that can only be fought with new AI technologies.
How is IA strengthening cyber security in the industrial field?
AI tools help to anticipate and neutralise threats and to manage cyber security incidents with greater responsiveness and effectiveness through the analysis of large amounts of contextual information and without the need for highly specialised human intervention.
These techniques can track the steps of attackers through chains such as Cyber Kill Chain and sophisticated systems capable of learning from the environment, reasoning to identify relationships between threats and making critical decisions.
AI’s involvement in cyber security has four basic objectives:
- Massive information management: AI prioritises which situations and attacks have management priority and which are false threats, unblocking the workload of the systems.
- Real-time response: AI allows immediate action to be taken in response to attacks to minimise risk, based on infinite data and context.
- Automation: Automation of response to many of the threats, minimising their cost in terms of detection and response.
- Prediction: AI helps to improve forensic analysis of previous attacks, which translates into improved defenses.
These objectives are applicable to different areas where AI on cyber security is being applied, some of which are:
- Intrusion Management
- Anti-malware protection
- Fraud management
- Cyber-intelligence
- Identity and Access Management
- Malicious mail prevention
To implement a good AI strategy in cyber security, companies should have a strategic plan to follow, which should go through the following stages:
- Create a data platform: Identify data sources and create data platforms to implement AI.
- Select high-impact use cases: Select a set of relevant use cases to accelerate and maximise benefits.
- Collaborate externally: Collaborate with strategic partners to improve threat intelligence
- Implement SOAR: Implement security orchestration, automation, and response to improve security management
- Train Cyber-Analysts: Train cyber-analysts to master IA.
- Effective Governance: Establish a model for managing AI in cyber security to deliver long-term improvements in a transparent and ethical manner.
IA: The Basis of Today’s Cyber security
Cyber security analysts are overwhelmed by the massive volume of information units they must monitor to combat intrusions, and the volume and complexity of cyber attacks has grown considerably in recent years. For this and other reasons, the MarketsandMarkets report “Artificial Intelligence in the Cybersecurity Market: Global Forecast to 2026” concludes that the artificial intelligence sector in cybersecurity will reach $38.2 billion by 2026, representing an average annual growth of 23.3%.
The inability of traditional equipment to cope with IT risks shows that only with AI can companies strengthen their defence systems and cyber security can become smarter than cyber attacks. This need is opening the way to platforms that manage industrial systems in an integrated manner and ensure the cyber security of their customers.
A secure IIOT platform for your company
Nexus Integra is an integrated integration platform with industrial systems integration capabilities, capable of generating a global operations and monitoring environment for large-scale industrial asset management. Nexus Integra complies with the National Security Scheme (ENS) Medium category that guarantees the security of the processed information. In addition, the platform ensures the security of communication of all its layers by applying secure encrypted security protocols such as HTTPS or binary encrypted channels that require authentication. Likewise, the Nexus Integra platform has a tool that allows for the centralisation of logs and their joint visualisation.
This allows the activation of alarms based, for example, on failed logging attempts or massive data export, which could become cyber attacks.
Do you want to implement a secure IIoT platform? Start now with Nexus Integra
