It is more important than ever to ensure robust cybersecurity measures are in place when it comes to protecting organizations, and even governments and nations, against digital threats.
As society’s reliance on digital platforms, online connectivity, and data transfer and storage has increased, so has the number of potential attack vectors. Phishing, identity theft, and ransomware attacks are all becoming more common and widespread.
Now, AI has been added to the mix, particularly generative AI. But even though this revolutionary technology creates new risksit also creates new opportunities.
Cybersecurity analysts, engineers, architects and ethical hackers are on the front lines of this fight. Increasingly, their work will involve collaboration with intelligent machines and generative AI technologies to combat the new wave of threats.
So if you work – or plan to work – in cybersecurity and want to know how the rise of AI will impact your role and the future of your profession, read on.
Generative AI and cybersecurity
THE Certified Information Systems Security Professional (CISSP) defines eight key areas of cybersecurity. Broadly speaking, these can be used to categorize the key tasks that security professionals are responsible for. It’s not hard to see that generative AI has implications for all of them:
Security and risk management involves identifying specific threats, such as phishing or denial of service attacks. Here, generative AI can be used to perform real-time risk assessments and automatically report recommendations and mitigation strategies.
Asset security focuses on implementing system and data protection measures. Generative AI tools can be used to automate the classification of sensitive information and identify weak points in the security infrastructure.
Security architecture and engineering refers to work that involves the design and implementation of security measures. Generative AI can be used to suggest security implementations as well as simulate attacks to test their effectiveness.
Communications and network security involves ensuring the security of data transfer across networks. Machine learning algorithms monitor traffic and look for patterns that suggest suspicious activity, while generative AI tools create real-time reports that flag potential violations.
Identity and access management is about ensuring that authorized users have access to the systems and data they need while keeping out potential intruders. AI can track user behavior and access patterns to identify anomalies or detect phishing attacks by analyzing the content, tone and structure of emails or voice communications. It can also create simulated phishing attacks to scan for vulnerabilities.
Security assessment and testing implements processes to perform routine testing across the entire spectrum of cybersecurity infrastructure. GenAI can automate the creation of test schedules and reporting of results, as well as generate recommendations for corrective actions.
Security operations refers to the procedures in place to detect and respond to ongoing security incidents. Generative AI tools can be used to create automatic incident response plans or conduct simulated attacks, allowing organizations to reduce the time it takes to respond to breaches.
Software development security ensures that software vulnerabilities are identified early in the development phase. Generative AI tools can automate code review and test plan writing, as well as analyze code repositories to ensure their security.
By understanding how generative AI can be integrated into these areas, cybersecurity professionals can develop a solid understanding of how this technology can help them detect and respond to threats, as well as proactively strengthen defenses of their organizations.
How the role of cybersecurity professionals will change
I believe generative AI will impact almost every job, profession, and career path, and the in demand the field of cybersecurity is no exception.
Those who have the ability to work with generative AI will find it easier to automate many elements of their daily activities. This will free up their precious time to spend on activities that are not so easy to delegate to machines.
This may include working face-to-face with colleagues to help them understand their own cybersecurity responsibilities, tasks involving high-level strategic decision-making, or identifying new threats that may not are not well recognized and documented.
Another thing that even the best AIs aren’t yet able to do as well as humans is understand specific weaknesses in a particular organization’s culture and how they create or mitigate security threats. This could include management’s attitude towards security, the quality of training policies in place and levels of compliance with IT codes of practice.
Just as is the case for professionals in other fields, those who are able to reskill and upskill in the face of this upheaval in responsibilities and priorities will find that they are more likely to thrive.
The challenges and opportunities facing cybersecurity professionals will undoubtedly evolve, and the growing prevalence of AI will be a key driver.
Adaptability will be essential, as tomorrow’s threats will be different from those of today. Consider, for example, the threats that quantum computing poses to encryption standards or the data protection risks arising from the digitization and storage online of an increasing amount of our personal information.
This will mean that cybersecurity professionals will become increasingly critical to the security of not only their organizations, but society as a whole, as we move forward into the digital age.