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    The Dual-Edged Sword of AI in Cybersecurity
    Like this cybersecurity blog post? Register for our upcoming webinar, on Wednesday 27 March: Innovations in AI-Enhanced Cybersecurity”.


    In the rapidly advancing tech landscape, Artificial Intelligence (AI) has become a ubiquitous term, often hailed as the modern hero of the tech realm and wielding transformative powers. However, as the saying goes, every hero has its adversary, and AI’s integration into cybersecurity has ushered in both new threats and innovative defence strategies. 

    The Escalating Challenge of Cyber Threats 

    The looming spectre of cyber threats is staggering, projected to escalate from $3 trillion in 2015 to a monumental $10.5 trillion by 2025. Hackers, fuelled by AI capabilities, exploit age-old vulnerabilities and are unleashing a wave of diverse threats. 

    A significant concern is AI-generated malware data poisoning, a technique where training models are corrupted by injecting incorrect data into the dataset and exemplified by tools like Nightshade. This poses a substantial risk and demands vigilant defence measures. 

    AI-enhanced phishing and social engineering amplify the danger, as threat actors utilise AI to meticulously analyse vast datasets, crafting convincing phishing emails and deploying deepfakes for social engineering. Automation capabilities give power to adversaries to orchestrate large-scale cyber-attacks, while AI-generated malware adeptly evades traditional security measures. 

    Leveraging AI as a Shield in Cyber Defence

    Recognising and countering deceptive techniques requires defenders to develop strategies that are equally sophisticated and adaptive. AI becomes a powerful ally in this battle, analysing network traffic and user behaviour to swiftly identify anomalies that may signal adversarial activities.  

    “Defence can’t be at human speed when cyber threats are at machine speed.”

    A real-time approach allows defenders to respond promptly to potential threats. The dynamic nature of AI-powered threats mandates continuous monitoring and refinement of AI models, ensuring AI defences remain adaptive, self-learning, and one step ahead of emerging tactics. 

    How LAB3 is Harnessing AI to Combat Threats 

    At LAB3, we leverage AI to detect fast flux threat actors. These threat actors are akin to chameleons changing their colours faster than the eye can follow.

    So, who are fast flux actors? Fast-flux actors are the shifty characters who change their IP addresses and Fully Qualified Domain Names (FQDNs) to perform malicious activities online. Their elusive manoeuvres aim to outwit security analysts, leaving no lasting footprint and making them hard to identify and pin down. 

    “Most fast flux threat actors can easily evade the traditional OSINT (Open-Source Intelligence) tools, as their chameleon-like activities are not identified as malicious.”

    By incorporating a combination of false positives which, if taken individually, would otherwise indicate it is not a malicious activity, one can lay out a pattern identifying these highly stealthy actors. This provides us a larger detection blast radius. The threat exchange is built by continuous integration of machine learning algorithms into various threat intelligence sources.  

    The paradigm has shifted: it’s no longer a turtle and a hare race, but a falcon and hawk competition  

    Numerous use cases highlight how robust defence strategies can be built through AI applications. Automated investigations, query enhancements, and tailored detections based on constant learning can be facilitated by Large Language Models, transforming defence and response strategies. The paradigm has shifted: it’s no longer a turtle and a hare race, but a falcon and hawk competition. A competition where speed and precision are paramount. 

    Navigating Future Risks in the AI Era 

    Though we are moving towards the forefront of innovation with AI in place, the synergy between human intuition and artificial intelligence emerges as the key to securing our digital future, particularly in the face of AI-driven challenges we are yet to discover. 

    “A significant area warranting attention is that of Human AI Labelling, where a human worker adds labels (and by implication, values) to certain objects to facilitate machine learning.”

    Notably, major AI tech companies outsource the AI labelling work to countries such as The Philippines, Venezuela, Uganda, and Kenya. This externalisation introduces a potential gateway for foreign government interference, raising the spectre of considerable risks on the horizon. 

    As we chart the course into an AI-driven era, it becomes imperative to scrutinise these vectors, recognising the key to a resilient digital future lies in a balanced integration of human discernment and technological prowess.

    Like this cybersecurity blog post? Register for our upcoming webinar, on Wednesday 27 March: Innovations in AI-Enhanced Cybersecurity”.
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    About this author

    Priya is a senior security engineer at LAB3 and an industry supervisor at Federation University. She is a recognised speaker and cyber security advocate, passionately committed to create a secure digital environment.
    Priya Gnanasekaran
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