The Role of AI and ML in Ransomware Protection

Ransomware is a universal threat — every business of every size in every industry in every country is at risk. That’s the bad news. The worse news is that the threats are growing in complexity, sophistication and scale. Cybercriminals are continually developing new tactics and exploiting new technologies to improve attack effectiveness.

According to the Acronis Cyberthreats Report, in 2022, 30.6% of all received emails were spam and 1.6% contained malware or phishing links. Phishing was the vector used in 76% of successful attacks and roughly 8% of endpoints tried to access malicious URLs. And attacks are speeding up: the IBM Security X-Force Threat Intelligence Index 2023 revealed a 94% reduction in the average time for the deployment of ransomware attacks. What took attackers over two months in 2019 took them just under four days in 2021.

Threat actors are also getting smarter, honing their techniques and strategies, and employing artificial intelligence (AI) and machine learning (ML) to improve the effectiveness and impact of intrusions. Ransomware attacks are moving beyond encryption to include double and triple attacks, which can take the form of data exfiltration and subsequent extortion for the return of data as well as disclosure of data leaks to your customers and partners, thereby putting additional pressure on your business to pay the ransom.

From using generative AI tools like ChatGPT to creating phishing emails that fool even the most suspicious employee, to improving the effectiveness of attacks through MI, these new strategies are complicating both ransomware prevention and ransomware protection. Savvy businesses must turn to AI and ML to counter the expanding ransomware threat.

Unfortunately, traditional anti-ransomware and anti-malware solutions aren’t able to effectively counter modern cyberthreats. Because they rely on signature matching — which can’t identify previously unknown zero-day threats — they’re unable to detect known threats during an initial intrusion. Anti-malware solutions struggle to recognize threats that use exfiltration and encryption to capture critical information.

Any business that continues to rely solely on traditional anti-ransomware and anti-malware solutions is putting its customers, partners and itself at risk. Modern ransomware threats require a more comprehensive, layered approach. By adopting advanced technologies that leverage artificial intelligence, machine learning and behavioral analytics, you can be better protected against today’s sophisticated and evolving threat environment.

Machine learning and AI are crucial components of modern ransomware protection since they enable the detection of patterns of malicious behavior as opposed to merely matching the signature of a malware instance against a database of known threats. Without this behavioral approach, no anti-malware measure can successfully identify the thousands of zero-day malware instances that are being generated daily by threat actors.

Machine learning improves your ability to detect previously unrecorded exploit information by presenting a baseline for safe system behavior based on past and current system interaction data. As organizations gather more and more data, this approach can detect zero-day threats more reliably.

According to the IBM Security X-Force report, machine learning algorithms have an 85% accuracy rate in detecting ransomware attacks by analyzing network traffic patterns, which can significantly reduce the risk of data loss and downtime.

By deploying anti-ransomware solutions that incorporate AI and ML, businesses are taking advantage of the technology’s ability to actually “learn” and adapt. Over time, systems are able to develop a baseline of expected behavior and compare it to new and changing behavior and data. With enough context, AI and ML-powered ransomware protection can determine whether or not unexpected behavior is safe.

Attackers are exploiting generative AI tools like ChatGPT to improve their odds of launching successful attacks. Tactics include improving the apparent authenticity and trustworthiness of phishing emails, automatically scanning applications for vulnerabilities, and fine-tuning the orchestration of multistage attacks.

We wondered just how much damage ChatGPT could do, so we decided to ask it. Here’s what it had to say in response to the following question:

Generative AI, like ChatGPT, has the potential to be misused by cybercriminals to enhance the effectiveness of various attacks, including ransomware attacks. While I cannot endorse or support any illegal or malicious activities, I can provide you with an understanding of how generative AI could potentially be leveraged in such scenarios.

1. Social engineering: Cybercriminals can use generative AI to simulate realistic conversational agents, such as chatbots, to deceive and manipulate unsuspecting individuals. By mimicking human-like responses and behaviors, these AI agents can trick users into revealing sensitive information or clicking on malicious links, which can facilitate the delivery of ransomware.

2. Phishing attacks: AI-powered chatbots could generate highly convincing and personalized phishing messages, making them more effective at tricking users into divulging sensitive information or downloading malicious attachments. Ransomware attacks are often initiated through phishing campaigns, and AI-generated content could make these attacks even more sophisticated.

3. Evading detection: Generative AI can be used to generate polymorphic or dynamically changing ransomware strains, making them more difficult for traditional security solutions to detect and block. By leveraging AI algorithms to continually modify the underlying code of ransomware, cybercriminals can create variants that can bypass conventional signature-based defenses.

4. Targeted Attacks: AI can be employed to gather and analyze vast amounts of data about potential victims, allowing cybercriminals to craft more personalized and targeted ransomware attacks. By utilizing machine learning techniques, attackers can exploit weaknesses and vulnerabilities specific to a target's environment, making the attacks more successful.

It's crucial to note that the use of generative AI in cybercrime is an ongoing concern, and the security community is actively working on developing countermeasures. The responsible use and development of AI technologies are necessary to mitigate the risks associated with potential misuse by cyber criminals.

Machine learning algorithms can be used in various ways to optimize different aspects of the attack process. While I cannot endorse or support any illegal activities, here are a few ways in which machine learning could potentially be misused in ransomware attacks:

1. Targeted attacks: Machine learning algorithms can analyze large datasets to identify potential targets and gather information about their vulnerabilities, systems or networks. By understanding the target's environment, cybercriminals can tailor their ransomware attacks to exploit specific weaknesses, increasing the chances of successful infection and encryption.

2. Attack delivery: Machine learning can be utilized to optimize the delivery mechanisms of ransomware, such as email phishing campaigns or malicious websites. By training models on vast amounts of data, attackers can improve the accuracy of targeting potential victims and increase the chances of users interacting with malicious content, leading to the deployment of ransomware.

3. Evasion techniques: Machine learning algorithms can help cybercriminals develop evasion techniques to bypass security defenses. By analyzing security solutions and their detection mechanisms, attackers can train models to generate ransomware variants that are less likely to be detected by traditional antivirus or intrusion detection systems, making it harder for victims to protect themselves.

4. Encryption optimization: Machine learning can be used to enhance the encryption algorithms employed by ransomware, making them more sophisticated and secure. By training models on encryption patterns and techniques, cybercriminals can develop stronger encryption methods that are harder to break, increasing the likelihood that victims will be forced to pay the ransom to recover their data.

Clearly, technologies like AI and ML pose a real threat in the ransomware ecosystem. By increasing the sophistication and effectiveness of ransomware attacks, these tools are complicating response and protection. With a robust cybersecurity infrastructure in place that includes a comprehensive incident response plan, you can go on offense and defense against ransomware threat actors.

Ransomware is the #1 threat that businesses face, regardless of size. Cybercriminals are constantly evolving their tactics to find new ways to infiltrate systems and networks. Any business seeking to reduce its risk must get aggressive on defense but also plan for the possibility that an attack may succeed.

Businesses need to embrace AI and ML tools for detecting, preventing and responding to ransomware attacks. The future of ransomware demands the ability to analyze traffic patterns, identify anomalies and detect potential attacks. By staying ahead of ransomware threats with AI and ML, you’ll be better positioned to protect critical information and processes.

Acronis Cyber Protect is an integrated cyber protection solution that helps defend businesses against all types of ransomware. It uses a combination of machine learning and artificial intelligence to detect and block ransomware attacks while providing recovery options in the event of an attack.

Acronis Cyber Protect detects and blocks ransomware attacks using a multilayered approach. Heuristics and signature-based detection identify known ransomware threats, while behavioral analysis and machine learning technologies can detect even never-before-seen threats. The solution uses artificial intelligence to monitor behavior changes that could indicate an impending attack.

In the event of an attack, Acronis Cyber Protect provides several options for recovery. For example, it can restore individual files or folders that have been encrypted and entire systems. It also offers the ability to roll back changes made by the ransomware so that you can return to a previous version of your data before the attack occurred.

Ready to improve your security against modern cyberthreats while streamlining efficiency of management? Book your free spot in our next engineer-led demo of Acronis Cyber Protect.