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Fraud Insight
Although these and other cybercrime statistics cited in the article are staggering, the organisations and individuals fighting cybercrime now have an ally that offers ever-increasing capabilities: artificial intelligence (AI).
Of course, cybercriminals often use AI for their own purposes, including creating new malware and hacking tools, automating phishing attacks, searching for loopholes in security, and using deep fake technology and malicious bots to impersonate people. But at the same time, AI enables us to fight back better than ever before.
How AI works to fight cybercrime
AI uses four main abilities to combat cybercrime in real time:
1. Monitoring and analysing behaviour patterns
AI monitors and analyses behaviour patterns in its assigned areas and identifies anomalies, including new users, unusual login activity and IP addresses, permission changes on files, folders and other resources, and copying or deleting large volumes of data.
2. Predicting outcomes of unusual behaviour
AI compares the anomalies it detects to its knowledge base and predicts the potential next steps and likely outcomes? of the unusual behaviour.
3. Preventing bad actions and outcomes
Once AI identifies a potential threat, it can take prescribed actions such as preventing deletions, logging off suspicious users and notifying operators of the suspected malicious activity. Administrators can then review the findings and take further action if needed.
4. Training and machine learning
AI can be trained to monitor and act against new vulnerabilities, and it can train itself through machine learning (ML) to “remember” previous incidents and actions, thereby improving its ability to identify suspicious activity, predict outcomes and prevent criminal initiatives.
Advantages of using AI in cybersecurity over traditional systems
There are many potential advantages of using AI in cybersecurity over traditional systems. ML is one of the most important advantages because the AI systems train themselves and learn from past “experiences” while predicting and preparing for possible future scenarios. With ML, AI learns as humans learn but without time-consuming human input. The ML capabilities of AI will only improve as developers continually enhance them.
ML and human training also enable AI to better analyse activity and identify ?false positives?? so that the cybersecurity system presents to humans only those issues that require human review.
This helps avoid and correct the common problem of bombarding operators with so many unnecessary alerts that they are unable to review them all. As a result, they ?may miss the important ones and generally burn out on reviewing alerts.
Another important advantage of using AI in cybersecurity is the automation of time-consuming and repetitive tasks, such as monitoring and analysing events, predicting outcomes, taking preventive actions and generating alerts of suspicious behaviours for human review, all of which can be done continuously in real time.
Penetration testing also can be automated with AI, enabling it to be performed daily, rather than once or twice each year.
AI also helps fill the gaps in the human cybersecurity labour force.
Using AI in cybersecurity can also help free your cybersecurity team from mundane initial event monitoring and analysis and allow them to apply their creativity to learning, strategy and decision-making, which adds more value from each employee to the business? as a whole and its bottom line.
Organisations can realise benefits in productivity, utilisation, job satisfaction and threat mitigation when they deploy the optimal mix of AI and human occupation.– forbes.com
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