The advent of widely-available consumer AI platforms opens up seemingly endless possibilities and potential uses, and as with essentially any new technology or tool throughout history, the ways that people gravitate towards using them is almost always aligned with the individual user and his or her personal proclivities. So for all the good that can potentially come from AI capabilities, the bad actors amongst us are going to steer these new tools towards nefarious ends, because, well…that’s what bad people do.
Cyber security is no exception. AI can allow for the automation of existing cyber protections, protocols, checks, penetration testing, mitigations, and more. But the bad guys are also going to pull apart every bit of code behind those AI automations to look for weaknesses, predictable trends, and vulnerabilities that are often harder to identify in cyber defensive postures constructed by often less-predictable human brains. Worse, those bad guys are already working to subvert AI cyber defenses with their own black hat weaponized AI developed malware and methodologies. Geoffrey Hinton, one of the pioneers in the AI space, resigned from Google earlier this year with a statement that included “It is hard to see how you can prevent the bad actors from using it for bad things.”
Let’s take a look at some of the known potential issues and vulnerabilities as AI is integrated into cyber security models:
Adversarial Attacks: AI systems can be vulnerable to adversarial attacks, where attackers manipulate input data to deceive AI algorithms. For example, an AI-powered intrusion detection system could be fooled by subtly altering malicious code or network traffic to appear benign.
Exploiting AI Vulnerabilities: Just as AI can be used to find vulnerabilities in systems, attackers could also use AI to discover and exploit weaknesses in AI-based defenses. This could lead to more effective and targeted attacks.
Automated Attacks: Malicious actors could harness AI to automate and optimize the execution of cyber attacks. AI-driven malware could adapt and evolve in real time, making it harder to detect and mitigate.
Camouflaging Attacks: Attackers might use AI to craft sophisticated and convincing phishing emails or messages that blend seamlessly with legitimate communication. This could trick users into revealing sensitive information or downloading malicious content.
Algorithmic Bias: AI algorithms are only as good as the data they’re trained on. If these algorithms inherit biases present in the training data, they could inadvertently discriminate against certain groups or make incorrect decisions, leading to vulnerabilities or exploitation.
Data Poisoning: Attackers could manipulate training data used by AI systems to introduce bias or subtly alter the AI’s behavior. This could impact the accuracy and reliability of the system, potentially leading to false positives or negatives in threat detection.
Advanced Social Engineering: AI could be used to analyze vast amounts of publicly available information about individuals, allowing attackers to craft highly targeted and convincing social engineering attacks.
Evasion Techniques: AI-powered attackers might develop evasion techniques specifically designed to bypass AI-based defenses. This could lead to a constant back-and-forth between AI-driven attacks and AI-driven defenses.
Privacy Concerns: The use of AI in cyber security may require analyzing large amounts of sensitive user data. If not handled properly, this could lead to privacy breaches and potential misuse of personal information.
Dependency on AI: Over-reliance on AI-driven security systems could lead to a false sense of security. If AI systems fail to detect new, innovative attack methods, organizations might become more vulnerable.
Regulatory and Ethical Challenges: The use of AI in cyber security introduces complex regulatory and ethical challenges. Decisions made by AI systems, especially those involving automated threat response, might raise legal and ethical questions.
It’s hard not to feel like some sort of digital battlefield has emerged and that a war is being waged in an invisible space that we don’t see or understand until something catastrophic happens. It could be a rash of data breaches, which are closer to an annoyance than a catastrophe and something most of us have been a victim of at one point or another; or it could be entire operational disruptions or shutdowns of industries and critical components of infrastructure. What if all of our banks went offline tomorrow? What if our power grid was shut down? Our GPS satellites stopped transmitting?
There are still humans behind the AI that is creating and sustaining these attacks and defenses, but what happens if the volume of activity in this space increases 10-fold, or 100-fold due to automation and constantly updated, iterative machine-learning? AI-based cyber defense MUST be incorporated to defend against new flavors and the sheer volume of AI-based cyber attacks, but humans are still (for the time being) the most important ingredient in this conflict. Humans still drive the concepts of adversarial AI defense, data quality and diversity, ethical AI practices, adaptive/dynamic defense mechanisms, collaboration and information sharing, R&D investment, and the regulation, policy, education, and training of the humans that operate in this space.
Our cyber security partners at TechFides have long and successful track records of helping organizations protect their operations and assets, and perhaps most importantly, have shown the ability to quickly adapt as the cyber threat landscape evolves over time. Reach out today to have a conversation about your cyber security posture, and our team can provide you with the confidence that the hard work you’ve put into your business is protected and secure from bad actors, both human and machine.
