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The Double-Edged Sword of Artificial Intelligence (AI) in Cybersecurity
May 23, 2024 | 4 min read
Lorri Janssen-Anessi
Director, External Cyber Assessments
![Janssen anessi](/assets/imager/imagess3/152150/janssen-anessi_d2448492f1f17e3bf43a2e2b9f1c45e4.jpeg 100w, /assets/imager/imagess3/152150/janssen-anessi_fc4267e5cc2c64c601bf2ad9abb5c180.jpeg 200w)
A Look at the Role of AI for Attackers and Defenders
As artificial intelligence (AI) continues to advance, its impact on cybersecurity grows more significant. AI is an incredibly powerful tool in the hands of both cyber attackers and defenders, playing a pivotal role in the evolving landscape of digital threats and security defense mechanisms. In this blog, let’s explore the ways AI is employed by attackers to conduct cyber attacks, and how defenders are using AI to deter and counter threats.
The Role of AI in Cyber Attacks
Improved Social Engineering
The incorporation of AI into malicious social engineering campaigns creates a new era where cyber threat actors are more convincingly deceptive. With access to a vast amount of data, cyber threat actors can both increase the success and effectiveness of large-scale phishing campaigns or use this access to huge amounts of data to spread disinformation online. Correlating massive volumes of data enables cyber threat actors to provide more convincing narratives targeted at specific users by considering time zones, keywords, geographical information, and language nuances. The resulting messages are more sophisticated, with fewer grammatical errors, and are highly believable. AI also allows for the creation of highly targeted messages aimed at the most vulnerable individuals. Cyber threat actors can easily translate messages into targets’ native language or use personal information gleaned from social media sources, for example, to craft compelling stories. The emergence of deepfakes, hyper-realistic audiovisual fabrications powered by AI, creates novel avenues for deceiving targets, marking a dangerous evolution in the arsenal available to cyber adversaries.
Automated Reconnaissance and Exploitation
AI enables ease of automation, reconnaissance, and exploitation. The exploitation of vulnerable systems has become more efficient due to the incorporation of AI into the cyber attack kill chain (referring to MITREs Attack Framework) Automated tools can scan for weaknesses with malicious intent, aiding in the rapid development of exploits, zero-day attacks, and malicious software. The sheer volume of scanning that AI enables increases the likelihood of attackers gathering the information they need to carry out their attacks, and successfully orchestrate a malicious event.
Increased Sophistication
AI has significantly raised the bar for attacker techniques and sophistication. For instance, threat actors are using search engine ads as vectors for phishing attacks, directing victims to malicious websites that impersonate major financial institutions in various regions, including the United States, United Kingdom, and Eastern Europe. The increase of exploits development and the discovery of vulnerabilities could also be an indicator of the overall increased sophistication due to AI use incorporated into cyber threat actor targeting.
Data Manipulation
By manipulating AI algorithms cyber threat actors are also manipulating data consumed by AI algorithms. By inserting incorrect information into legitimate but compromised sources, they can "poison" AI systems, causing them to error out or export bad information. This sort of adversarial attack involves feeding AI systems bad data to subvert their intended purpose. Intentional corruption of code and data represents a significant challenge, as developers have yet to devise a foolproof defense. As it stands for any machine learning — bad data in equals bad data out.
The Role of AI in Cyber Defense
In an increasingly connected world, the role of AI in cyber defense has become crucial in safeguarding against sophisticated cyber threats. AI in cyber defense is not just a trend, it is a necessity.
Enhanced Network Analysis
While attackers are leveraging AI to craft more sophisticated attacks, cybersecurity professionals are employing AI to bolster defenses. AI-driven security systems can also analyze vast amounts of data to identify patterns indicative of cyber threats, providing a proactive approach to threat detection. Machine learning algorithms are being trained to recognize the signs of an intrusion, to identify them before any significant damage is done.
Specifically, enhanced AI systems are adept at monitoring networks for unusual activities that could indicate a security breach. By continuously analyzing network traffic, these systems can detect anomalies that deviate from normal patterns, such as unusual login times, high data traffic, or unrecognized IP addresses. Machine learning algorithms within these systems learn over time, reducing false positives and increasing their accuracy in identifying genuine threats.
Automated Threat Detection
Cyber defenders can use AI's game-changing predictive capabilities for cybersecurity. By leveraging predictive analytics, AI can forecast potential vulnerabilities and attack vectors before they are exploited. This allows organizations to patch security gaps and reinforce their defenses proactively, ahead of attackers discovering these weak spots.
Predictive Analysis
AI-driven behavioral analytics take threat detection a step further by understanding the normal behavior of users and entities within a network. This deep learning aspect of AI can distinguish between legitimate user actions and potential threats by detecting behavioral anomalies, such as sudden changes in file access patterns or data transfer volumes, which could signify a compromised account or an insider threat.
Cyber Triage
AI can’t replace human cybersecurity experts; but it can absolutely enhance and increase cyber defender capabilities and triaging. By sifting through massive datasets and identifying threats, AI frees up human analysts to focus on more complex tasks such as threat hunting, forensic analysis, automatically combining different source information, and strategic security planning. This collaboration between human intelligence and artificial intelligence will most assuredly result in a more robust cyber defensive posture.
Conclusion
The arms race between cyber attackers and defenders continues to accelerate with the integration of AI into their arsenals. While AI presents formidable challenges in the form of more sophisticated and targeted cyber attacks, it also offers powerful tools for cybersecurity professionals to protect digital assets, networks, and systems. As we navigate this new landscape, it is imperative that we continue to develop innovative AI-driven solutions to stay ahead of threats and safeguard against the malicious use of this technology.
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