How AI is Tackling Cyber Threats on the Dark Web
The dark web is where the most sinister elements of the cyber world lurk—malware, data breaches, ransomware services, and phishing kits, all hidden from plain sight. To stay ahead of cybercriminals, law enforcement agencies, governments, and companies constantly monitor the dark web, searching for warning signs amidst the chaos.
But navigating the dark web is no easy task. Although dark web monitoring services have been around for a while, artificial intelligence (AI) is now stepping up to revolutionize this process.
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A Growing Dark Web Market
The global market for dark web threat intelligence is booming. A report from Data Intelligence estimates that this market will reach $1.7 billion by 2030. Companies like ZeroFox, CrowdStrike, Digital Shadows, Flare, and IBMX-force are investing heavily in AI to build the next generation of dark web monitoring tools.
One company leading the charge is Flare, which recently introduced an AI-driven dark web solution called "Threat Flow." This tool uses a blend of AI technologies to provide timely and reliable reports on dark web activities. According to Mark MacDonald, Senior Product Marketing Manager at Flare, their approach combines different AI tools for specific tasks—like natural language processing for tracking discussions on forums and machine learning for prioritizing potential threats.
Can AI Fall into the Wrong Hands?
Flare’s MacDonald acknowledges the possibility that cybercriminals could try to reverse-engineer AI technology, but he believes the risk is low. However, the potential for criminals to use AI to identify undercover law enforcement is a concern.
Dane Sherrets, Solutions Architect at HackerOne, warns that cybercriminals could use AI to sift through vast amounts of dark web data more efficiently, making it easier for them to find and exploit vulnerabilities.
AI: A Powerful, But Limited Tool
Shawn Waldman, CEO and Founder of Secure Cyber, notes that while AI can greatly enhance dark web monitoring by processing more data faster than humans, it still has limitations. Human expertise is essential for understanding the broader context and making informed decisions based on the data AI provides.
AI's role in dark web monitoring is to assist humans by quickly identifying relevant information and providing context, but ultimately, it’s up to humans to decide how to act on that information.
Traditional Monitoring vs. AI-Driven Monitoring
Traditional dark web monitoring involves analysts using keywords to search through massive databases. AI changes this by narrowing down searches to specific events or elements that are particularly relevant to a company’s interests. AI can also find what traditional methods might miss, such as posts in different languages or with spelling errors.
Flare’s AI doesn’t need to scrape through unindexed onion addresses to be effective. MacDonald explains that most criminal activity on the dark web happens in a few well-known forums, much like how the legitimate internet operates.
The Dark Web: Not as Mysterious as It Seems
Michael Nizich, Ph.D., Director of the Entrepreneurship & Technology Innovation Center at NYIT, explains that the dark web is just another data source that AI can analyze. AI can quickly spot anomalies that would take humans years to detect, making dark web monitoring more effective.
In the end, while AI tools for dark web monitoring are still developing, they are making significant strides. These advancements could disrupt the way cybercriminals operate, making it harder for them to hide in the shadows.
The battle against cybercrime continues, but with AI on our side, we are better equipped than ever before.
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