Cybercrime is becoming increasingly sophisticated, and artificial intelligence (AI) is increasingly being used to augment attacks. While AI is being used to protect systems, cybercriminals are also adapting, automating their attacks with AI to make them more effective. In this article, we will consider the current trends in the use of AI in cybercrime, examples of attacks and possible methods of protection against them.
Phishing attacks remain one of the most common types of cybercrime, and the use of AI makes them even more effective. Using artificial intelligence, attackers can collect information about users, including their social media activity and online habits, to create the most convincing and personalized phishing emails. Thanks to automated systems and advanced algorithms, these messages are increasingly difficult to distinguish from the real thing.
Example: In 2023, malicious phishing emails increased by 1.265% after the launch of tools like WormGPT. WormGPT is a dark analogue of artificial intelligence designed specifically to help cybercriminals create phishing emails and fake websites.
Protection: Organizations can use multi-layered security systems that include AI to detect anomalous email activity. Approaches such as SPF, DMARC, and DKIM signature verification help prevent phishing emails from being delivered to recipients.
Deepfake technology allows you to create fake audio and video that looks and sounds like the real thing. This creates new opportunities for cybercriminals, especially in the field of financial fraud. Using deepfake, attackers can fake the voices of company executives to gain access to financial resources.
Example: In 2019, in Europe, criminals used deepfake technology to fake the voice of a company director, leading to the theft of more than $35 million.
Protection: To protect against deepfake attacks, it is important to implement additional layers of verification for financial transactions, such as multi-factor authentication and cross-channel confirmation of transactions.
Botnets are networks of compromised devices used for attacks such as DDoS. Artificial intelligence can increase their adaptability and make them more difficult to detect. AI-driven botnets are capable of changing their behavior depending on network conditions, making them effective and flexible tools in the hands of cybercriminals.
Example: In 2020, a botnet was discovered that used AI to avoid detection by security systems by changing its behavior in real time.
Protection: Using AI to monitor network traffic in real time can help identify unusual activity and isolate compromised devices. Key protection measures are regular updates of security systems and timely detection of anomalies.
AI is used to analyze large volumes of data to identify vulnerabilities in security systems or to guess passwords. Such algorithms can find weak points in the defense faster than a human, opening up new opportunities for attacks.