Artificial intelligence (AI) is becoming a key technology to use within cybersecurity. Businesses are now relying on digital systems, cloud systems, networks and online applications. While these can help increase productivity they can also put businesses at risk of threats. While traditional security is still important, there are more complex threats to deal with. AI can help to provide additional capabilities to identify suspicious activity, analyse information and respond to potential threats.
AI can be used in cybersecurity by using technologies such as machine learning, natural language processing and automated analysis. This can help analyse network activity, identify unusual user behaviour, and identify suspicious emails. However, there can be security risks with using AI. Cyber criminals can use AI to create realistic scams, automate attacks and exploit weaknesses. It is important to understand how beneficial and the limitations of AI can be. While AI can help increase security it cannot replace traditional security measures and trained professionals.
What is AI in Cybersecurity?
AI in cybersecurity refers to using artificial intelligence technologies to identify, prevent, analyse and respond to security threats. This can analyse large amounts of information to identify patterns and identify any suspicious activity. For example, an AI powered platform can be used to monitor network communications and identify any unusual connections or unexpected logins. Machine learning can help identify patterns and natural language processing can help analyse suspicious emails, security reports and other documents.
AI can help cybersecurity professionals by organising alerts, summarising incidents and providing recommendations. However, it can only be as good as the data provided, the accuracy of the models and the knowledge of the people using it. There can be errors in the systems and may miss threats. It should be used as an additional layer of security.
12 Ways AI Can Be Used in Cybersecurity
1. Identify suspicious network activity
AI can help businesses identify unusual activity on their networks. As organisations have a lot of network data from devices, servers, cloud applications and connected systems, AI tools can be used to analyse this. This can help identify any unusual connections, unexpected communications or suspicious activity. This can help professionals identify potential threats.
Machine learning can also help identify patterns of normal network activity and identify any significant changes. However, unusual activity may not always be an attack. This could be due to software updates, new applications or changes to how the business operates. Professionals should always investigate any alerts.
2. Spot phishing attempts
Phishing is a common threat in cybersecurity. Cyber criminals can send deceptive messages to try and get individuals to provide sensitive information or visit fake websites. AI can help identify suspicious emails by analysing the wording, sender details, links, attachments and communications. This can help organisations identify potentially dangerous messages.
AI can also help with email protection by identifying suspicious requests from managers, suppliers and other trusted individuals. However, generative AI can be used to create professional looking phishing emails. Businesses should also train their employees and use email verification, along with AI driven email protection.
3. Analyse logs
Security logs can be used to monitor what is happening on your networks, applications, servers and digital systems. This can provide valuable information on logins, changes to the system, network connections and access requests. However, this can take a long time to analyse manually. AI can help organisations analyse their security logs and identify any unusual patterns.
Businesses can use AI to identify any repeated failed logins, unexpected access and suspicious activity. However, it is important to know how to analyse logs to improve the ability to investigate potential threats. Accurate analysis can only be done if there are accurate records, correct monitoring and human analysis.
4. Identify unusual user behaviour
User behaviour analytics can be used to identify how employees and users typically interact with the business systems. This can analyse login times, where they are logging in from, what applications they are using and how they are interacting with sensitive information. If there is any sudden unusual behaviour on an account an alert can be raised.
This can be useful if criminals have access to genuine accounts and are trying to operate without triggering any traditional security alerts. However, employees may change how they work or what they are responsible for. Security teams should carefully investigate any unusual behaviour whilst respecting employee privacy.
5. Prioritise alerts
Businesses will receive a range of cybersecurity alerts from their firewalls, email protection, endpoint security and network monitoring. This can become overwhelming if there are a lot of notifications. AI can help prioritise alerts based on how serious they may be, how they could affect the business and if they are linked to other suspicious activity.
Some platforms can also group similar alerts together to help professionals understand how they could be linked. However, it is important not to fully rely on the prioritisation scores. Important threats may be overlooked.
6. Help with incident response
Incident response involves identifying, investigating, containing and recovering from cybersecurity incidents. AI can help by organising security information, summarising findings and identifying links between suspicious incidents. Some platforms can also automate approved actions to improve security such as temporarily restricting access to a suspected compromised account.
Generative AI can help with creating incident reports for cybersecurity professionals. However, organisations should have approval processes in place before allowing any significant security actions to be automated. Important decisions relating to sensitive information and critical business should be made by humans.
7. Improve endpoint security
Endpoint security protects devices such as computers, laptops, mobile phones and servers. AI powered endpoint detection can analyse activity on devices and identify any unusual behaviour which could indicate malware, unauthorised changes or other threats.
This can also link endpoint alerts to network and account information to help security teams investigate potential incidents. However, businesses should continue to use software updates, endpoint security, access controls and reliable backups.
8. Improve vulnerability management
Vulnerability management involves identifying and fixing any weaknesses in software, applications, hardware and digital systems. AI can help organisations analyse vulnerability reports to identify any important weaknesses and prioritise improving security based on how it could affect the business.
This can help improve the efficiency of vulnerability management, particularly for businesses with complex technology. However, it cannot guarantee all weaknesses will be identified. Regular security checks, software updates and professional testing should be carried out.
9. Improve identity and Access Management
Identity and access management helps to control who has access to business systems. AI can help by identifying any unusual login attempts, suspicious access and potential compromised accounts.
AI can also help businesses review account permissions and identify any unnecessary access. However, organisations should continue to use multifactor authentication, strong passwords, role based access and regular account reviews.
10. Help with threat intelligence
Threat intelligence involves gathering and analysing information about threats. AI can analyse large amounts of information from security reports to help professionals identify patterns and understand potential risks.
AI assisted predictive analysis can help businesses identify areas to improve security. However, predictions are not guaranteed as threats are constantly changing. AI analysis should be combined with current threat intelligence and professional security.
11. Improve cloud security monitoring
Cloud computing can cause security concerns as businesses will have accounts, data, applications and unauthorised access to worry about. AI can help monitor activity on the cloud, identify any unusual access and highlight any suspicious changes to configurations. However, businesses should continue to use encryption, appropriate access controls, regular security checks and reliable backups. AI cannot compensate for poorly configured systems.
12. Automate security
Cybersecurity teams often have to complete repetitive tasks such as reviewing alerts, creating incident reports, analysing reports and monitoring. AI can help automate some of these tasks by organising alerts, summarising security information and assisting with traditional investigation methods.
Generative AI can help analysts understand technical reports. However, inaccuracies can occur and recommendations may not be appropriate. Businesses should continue to have human oversight and clear rules in place for any findings.
Emerging Risks of Using AI in Cybersecurity
1. Scams and phishing
Generative AI can be abused by cyber criminals to create realistic emails, fake messages and impersonation. These messages may look very professional and similar to genuine business communications.
AI can also help create synthetic voices and images for impersonation scams. Businesses should train employees to independently verify any sensitive requests.
2. Automated attacks
AI can help criminals automate certain activities. This can help organise information and create more deceptive messages. This may cause an increase in suspicious messages.
However, not all attacks will be successful and other technical capabilities will still be needed. Businesses should continue to have effective monitoring, access controls, software updates and incident response.
3. Exploit weaknesses
Criminals may abuse the research and analysis capabilities of AI to identify weaknesses in poorly maintained digital systems. This could include outdated software, incorrectly configured applications and poor access controls.
Businesses should regularly update their software, check for vulnerabilities, review system configurations and improve access controls to reduce the risk.
4. False positives and negatives
AI security systems can identify legitimate activity as a threat (false positives) or fail to identify real security incidents (false negatives).
This can cause too many unnecessary alerts and threats can be missed. Organisations should regularly review how well the AI is working and ensure important findings are reviewed by professionals.
5. Expose sensitive data
AI in cybersecurity can help businesses identify suspicious activity and monitor sensitive information, but organisations must ensure that the data handled by these systems is properly protected. AI security platforms may process employee records, customer data, security logs and internal documents. If information is not managed properly or there are poor access controls, sensitive business information could be exposed. Businesses should establish clear rules for using AI, implement encryption and access controls, and regularly review how technology providers collect, store and process information. They should also follow appropriate data protection and privacy practices to reduce the risk of unauthorised access and protect confidential business information. Employees should never provide confidential business information to unapproved AI applications.
Businesses should have clear rules in place for using AI, encryption, access controls and review how data is collected and stored by technology providers. Employees should not provide confidential business information to unapproved AI applications.
6. Costly to implement and monitor
Implementing AI cybersecurity solutions can be costly. This can include costs for software, infrastructure, integration, maintenance and training. Some services will also have ongoing subscription or usage costs.
Before investing in advanced technologies, organisations should review their security needs. Choosing tools to target specific risks can help keep costs down.
7. Over reliance and lack of skilled professionals
Over relying on AI can cause security issues. Businesses may believe that AI will identify and resolve all threats. However, AI can make mistakes, miss new attacks and provide inappropriate recommendations.
Skilled cybersecurity professionals are still essential to investigate incidents, assess risks and manage security. Businesses should invest in developing professionals and training employees. AI should be used to reduce repetitive tasks.
How Businesses Can Use AI in Cybersecurity Responsibly
1. Have strong cybersecurity measures in place
Before heavily relying on AI businesses should have essential security measures in place. This includes multifactor authentication, encryption, firewalls, regular software updates, endpoint security, access controls and reliable backups.
This will provide important protection if the AI fails to identify suspicious activity. Regular reviews should be carried out to address any weaknesses.
2. Choose the right AI security tools
Identify the most important cybersecurity issues for your business. Some businesses may want to focus on email protection whilst others may need network monitoring, endpoint security or cloud security. Companies should review how accurate the tool is, how well it integrates, how it protects privacy, how scalable it is and any ongoing costs. Testing can help determine if the solution provides real security benefits.
3. Have human oversight
Important alerts should be reviewed by cybersecurity professionals. Significant findings should be verified and recommendations from automation should be assessed. Organisations should have approval processes in place for any actions that may affect critical systems or sensitive data. Regular reviews should be carried out to identify any inaccurate alerts. Human judgement can help ensure AI is being used to help with security.
4. Train employees
Employees should be aware of common cybersecurity threats such as phishing, impersonation scams, suspicious attachments and unauthorised access requests. AI in cybersecurity can help organisations identify suspicious communications, but employees must also understand how criminals may abuse artificial intelligence to create realistic fraudulent messages. Businesses should therefore invest in regular security awareness training and develop a security-first culture where employees understand how to recognise threats, protect sensitive information and report suspicious activity. This helps combine intelligent security technologies with employee awareness to strengthen overall business protection.
Clear reporting processes should be in place and employees should verify any unusual requests. Employee awareness is an important part of effective cybersecurity.
The Future of AI in Cybersecurity
As businesses use more cloud services, connected devices and digital applications AI is likely to become a more integrated part of cybersecurity. Intelligent systems may help with monitoring, investigating incidents, managing alerts and analysing large amounts of information.
However, cyber criminals may continue to abuse AI to create realistic scams and automate attacks. Businesses will need to improve their security practices. AI should be used alongside professionals, employee awareness and traditional security.
Conclusion
AI is transforming cybersecurity by helping identify suspicious network activity, phishing attempts, analysing logs, identifying unusual user behaviour, prioritising alerts and assisting with incident response. AI can also be used for endpoint protection, vulnerability management, cloud monitoring, threat intelligence and security automation. This can help improve monitoring efficiency and help businesses manage increasingly complex digital environments.
However, there are risks involved with using AI. This can include fraudulent communications, automated attacks, false positives, exposing sensitive data and costs to implement. Businesses should use AI responsibly and continue to use traditional cybersecurity measures. Investing in skilled professionals is important. Ultimately AI should be used as a compliment to human knowledge. By combining intelligent security technologies with effective policies, employee training and ongoing monitoring organisations can improve their defences against evolving threats.
