The Dual Impact of AI in Cybersecurity

Author

Michael Ridland

Category

AI, Security

Date

30 / 08 / 2024

According to an Adapt CIO Edge Survey, cybersecurity has become the top initiative for CIOs in 2024. Yet, despite the growing investment, cyber threats continue to evolve, becoming increasingly sophisticated and costly. The average global cost of a data breach surged to USD 4.8 million in 2024, marking a 10% increase from the previous year and the highest figure on record. Such financial implications make it clear that robust cybersecurity measures are not just an IT concern but a crucial aspect of overall business stability.

Artificial Intelligence (AI) presents both immense opportunities and significant risks when it comes to addressing these cybersecurity challenges. On the one hand, AI software development offers the potential to dramatically enhance defences by providing advanced capabilities for threat detection, prevention, and incident response. However, this same technology can also be leveraged by malicious actors to develop more sophisticated attacks, making it a double-edged sword. Businesses must navigate these complexities to safely adopt and leverage AI, ensuring that new technologies do not inadvertently open new attack vectors.

AI-Driven Cybersecurity Improvements

According to a recent survey, 69% of enterprises believe that AI is essential for cybersecurity, largely due to the increasing number and complexity of threats. One of the key strengths of AI is its ability to process vast amounts of data, recognise patterns, and make real-time decisions. This enables more efficient and effective threat detection and response, a crucial factor in preventing data breaches. Using machine learning algorithms, AI can analyse extensive data sets in real time, identifying anomalies and potential threats much faster than traditional methods. This rapid identification process prevents security incidents and minimises the impact of those that do occur. Organisations employing AI have reported a 15% decrease in dwell time, the period between an attacker gaining access to a system and the attack being detected. This reduction is a significant improvement, highlighting the critical role AI plays in early detection and response to cyber threats.

Additionally, AI facilitates enhanced automation of routine security tasks. For instance, AI systems can continuously monitor network traffic, identify vulnerabilities, and apply security patches without human intervention. This automation reduces the risk of human error and ensures that security measures are consistently and accurately applied. The scalability and adaptability of AI systems further enhance their value in cybersecurity. AI can scale to manage increasing data volumes and the growing number of connected devices in modern networks. Moreover, AI systems can adapt and learn from new threat patterns, continuously improving their ability to protect digital environments. This capability is essential as cyberattacks are constantly evolving. And as the digital landscape becomes increasingly complex, the role of AI in safeguarding data and systems will only become more vital.

AI-Driven Cybersecurity Risks

While AI offers significant advantages in enhancing cybersecurity, it also introduces new risks and challenges. According to a report by Sapio Research and Deep Instinct, 75% of security professionals have observed an uptick in attacks over the past year, with 85% attributing this rise to the use of generative AI by malicious actors. 

Attackers are increasingly leveraging AI to craft sophisticated and evasive cyber threats. AI-driven malware, for instance, can adapt to specific target environments, making it exceptionally difficult to detect and mitigate. This adaptability allows malicious software to evolve in real time, evading traditional security measures. Moreover, AI can be employed in social engineering attacks, significantly raising the stakes. Attackers can use AI to generate highly personalised and convincing phishing messages, exploiting individual vulnerabilities with unprecedented precision. The advent of deepfake technology further exacerbates this risk, enabling the creation of realistic but fraudulent audio and video content that can deceive even the most vigilant individuals.

As organisations adopt generative AI and other advanced technologies, cybersecurity leaders warn that these innovations might inadvertently expose them to increased risks. According to CFO.com, nearly half of CFOs believe that generative AI could leave businesses more vulnerable to cyberattacks than before. Key concerns include heightened privacy risks, a rise in undetectable phishing attacks, an overall increase in the volume and velocity of attacks, and the growing use of deepfakes for malicious purposes.

How Secure Are Your AI Systems? 

While AI offers significant potential for addressing complex business challenges, it also brings new cybersecurity risks. Implementing best practices is essential to safeguard your organisation against these emerging threats. Whether your business is currently using AI, planning to integrate it, or embarking on AI mobile app development, consider the following best practices:

  • Define a Controls Framework – establish a comprehensive set of policies, standards, guidelines, and best practices that govern the development, deployment, and use of AI systems within your organisation. This framework sets the foundation for responsible and secure AI usage.
  • Develop Defensible and Secure Architecture – build robust defences around AI assets. This includes creating a secure infrastructure to protect against potential vulnerabilities and threats.
  • Implement Tailored Security Solutions – employ specialised tools for validating, monitoring, and moderating AI systems to ensure their integrity and reliability. Tailored solutions address specific security needs unique to AI technologies.
  • Harness AI Threat Intelligence – adopt a proactive and holistic approach to AI security. This involves staying informed about emerging threats and implementing strategies to mitigate risks associated with AI systems.
  • Practice Continuous Monitoring – regularly monitor AI systems for security vulnerabilities and conduct periodic security assessments and audits. Ongoing evaluation helps in identifying and addressing potential risks before they escalate.
  • Encourage Collaboration and Knowledge Sharing – engage with industry peers and experts to stay updated on emerging threats. Sharing knowledge and best practices within the community enhances collective security and resilience against AI-driven threats.

Securing AI systems requires a strategic blend of policy-making, architectural design, specialised solutions, and threat intelligence. Moreover, it demands continuous effort, vigilance, and adaptation to the evolving landscape of AI and cybersecurity threats. However, by adopting a proactive approach across the whole AI lifecycle,  you can mitigate the risks and maximise the benefits AI can bring to your organisation.