Generative AI is a subset of artificial intelligence that can be used as the subject or object of a new generation of cyber attacks.
The Future of Cybersecurity: How Generative AI is Transforming Cybercrime
WRITTEN BY
SAMER AOUDI
EDITED BY
EZOZA SUPIKHODJAEVA
Multiple disruptive technologies are currently reshaping our world. In the ICT domain alone, we have numerous innovations such as Artificial Intelligence (AI), Blockchain, Quantum Computing, 5G, and IoT to name a few. The cyberspace around us is rapidly expanding; some say at an alarming rate, others, at an exciting, rate. Every new innovation brings opportunities and threats. One of the threats is the malicious use or application of the technology in question.
The rapid spread of computers brought about computer crime. The explosive popularity of the Internet propagated cybercrime. And recent advancements in AI is giving rise to, you guessed it, AI crime.
This is by no means a criticism of AI or any other innovation. When the first automobiles were invented, people met them with a great deal of skepticism. Many believed that they were dangerous, unreliable, and too expensive. Some critics even said that they would never catch on.
Generative AI is a subset of artificial intelligence that focuses on creating new data or content that is similar to, but distinct from, existing data. Unlike traditional AI, which is often used for specific tasks and follows pre-defined rules, generative AI can produce original output by learning patterns and features from a given dataset.
AI can be the subject of an attack (i.e., an AI algorithm attacked by criminals), or the object of an attack (i.e., misused to launch attacks). Expert attackers fight AI-based systems directly or indirectly, by exploiting weak points in ML techniques, leading, for instance, to false outputs.
An also be misused to enable novice (non-tech savvy) attackers and empower seasoned criminals, by generating attack vectors and exploitation tools.
While spreading false information (e.g., Fake News) does not necessarily need technology, the proliferation of Social Media expanded the surface of attack with more reach, making it a very serious modern-age problem. Generative AI allows the generation of more realistic fabricated content such as news articles and social media posts, enabling anyone to launch more believable disinformation campaigns.
We are all bombarded with tons of Phishing emails and other Social Engineering attacks that prey on our fear, greed, and other social and behavioral traits. While these scams are dangerous, most are easily detectable with little awareness and vigilance. Most of the messages used in these scams are poorly written and straight-out ridiculous. Not all, though! Generative AI is capable of producing professionally written content that can match any style you can think of. Scammers are starting to use Generative AI to create highly realistic phishing emails, messages, or even voice calls that mimic trusted entities such as banks, businesses, or individuals. By generating convincing content, cybercriminals can trick users into disclosing sensitive information, compromising their accounts, or installing malware.
AI-powered tools can generate and optimize attack vectors, allowing cybercriminals to launch more sophisticated and efficient attacks. Generative AI can automate the process of finding vulnerabilities in systems and even generate attack scripts, exploit codes, and difficult-to-detect malware.
Novice hackers often use existing tools that work on well-known vulnerabilities (i.e., most likely already patched). With Generative AI, novice hackers can now launch advanced Zerod-Day attacks.
Synthetic Media refers to any form of media content, such as images, videos, audio, and text, that is artificially generated or manipulated using computer algorithms and, more recently, AI techniques.
Deepfake refers to a type of synthetic media that involves the use of AI, particularly Generative AI techniques, to create realistic and often deceptive audio, video, or images. The term "deepfake" is derived from "deep learning" (a subfield of artificial intelligence) and "fake."
Deepfakes have become a significant concern because of their potential to spread misinformation, manipulate public opinion, and defame people by making it appear as if they did or said things they never actually did. The technology can also be used for entertainment and creative purposes, such as creating realistic CGI characters, altering scenes in movies, or generating songs by known artists.
With the rise of deepfake technology, there is a growing need for detecting and mitigating the impact of malicious deepfakes. There are many efforts to develop deepfake detection methods and raise awareness about the existence of manipulative media.
I cannot stress enough that it is not all dark and gloomy. Generative AI can produce original and diverse content, that can be incredibly useful for creative professionals, marketers, and content creators. Furthermore, AI can generate content at a much faster rate than humans, saving time and reducing costs. In cybersecurity, AI can be a valuable tool in threat detection and prediction, vulnerability assessment, network traffic analysis, automated incident response, and more.
Cybersecurity awareness matters more than ever because it empowers a new generation of citizens capable of protecting themselves in the digital realm.
Most cyber threats discussed in this post target human behavior through tactics like phishing and social engineering. By raising awareness about these tactics, individuals can become more cautious and vigilant, reducing the likelihood of falling for such scams. Being aware of the latest threats helps people recognize unusual or suspicious activities, allowing them to respond appropriately and quickly. Always remember, awareness, vigilance, and common sense can empower you to protect yourself.
Apr 2023: The Future of Cybersecurity: How Generative AI is Transforming Cybercrime
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