Employing Effective Cybersecurity Solutions for Data Protection Against AI-Assisted Attacks

Cyber risk provider IT Governance says over 6 billion records were compromised through November 2023. IBM’s 2023 Data Breach Investigations Report found that 83 percent of breaches involved external actors. The immediate future doesn’t look bright either because those statistics mostly predate the arrival of new artificial intelligence (AI) applications like ChatGPT. 

Hackers are now using AI to increase the frequency and severity of their attacks. Empowered by easy-to-use AI tools, even many newbies are even jumping in to try their hand at cybercrime. Black hat wannabes with zero coding experience can now grab off-the-shelf AI tools and create and deploy malicious software relatively easily. 

All it takes is one individual with bad intentions to quickly develop and unleash malware that can wreak havoc on your company. These readily available AI tools empower even unsophisticated actors to execute denial-of-service attacks, create phishing emails, and launch ransomware. These attacks can be run simultaneously from systems spread worldwide, making it nearly impossible for human operators to manually detect all the attacking systems accessing their websites and portals.

Fight Back With AI-Driven Cybersecurity Solutions

There is good news. AI and deep-learning technologies give you potent weapons in the fight against cybercrime. AI-driven security solutions with self-learning capabilities can proactively respond to emerging threats and protect against a wide range of threats like ransomware and malware, effectively empowering you to fight back.

These solutions, such as Sophos Intercept X Advanced, can detect anomalies and patterns indicative of malicious behavior and stop attacks before they can cause harm. This intelligent approach to data protection reduces your reliance on reactive measures and allows you to stay a step ahead of cybercriminals.

AI and deep-learning systems can adapt and evolve to counter emerging threats, learn from previous incidents, and continuously improve defense mechanisms. By leveraging techniques like transfer learning, these systems can update their knowledge bases with the latest threat intelligence and ensure greater data resiliency against future attacks.

These systems can also take proactive, automated actions based on predefined rules or learned behavior. For example, when a security breach or anomaly is detected, the system can automatically trigger measures like isolating affected systems or blocking suspicious traffic.

This automated response cuts the time between detection and remediation, minimizing the potential impacts of a cyberattack.

AI In the Real World

One example of AI in action is the well-known threat in the cybersecurity world called remote access Trojan (RAT). A RAT can be embedded into a simple email attachment, such as a JPEG image, allowing cyber attackers to gain unauthorized access to your systems. Since the IBM report also found that 74 percent of breaches involved the human element, this is a common scenario.

Antivirus engines typically detect RATs based on their signatures and then distribute an alert to all endpoints to identify and remove the RATs. However, attackers can easily modify RATs—even slightly—to generate a different signature and evade traditional signature-based detection.

AI and deep learning technologies are crucial to fighting back. Instead of relying solely on static signature matching, modern cybersecurity tools powered by AI can analyze the behaviors of files and processes. They can observe whether a file is executing specific actions or installing software. They can flag suspicious behavior and prevent potentially malicious actions by learning and recognizing patterns in these activities. 

Ensuring your data protection solutions employ this approach gives you more effective defenses against emerging threats. Attackers are constantly developing new methods to evade conventional cybersecurity measures, so you must keep pace with these changes by taking a proactive approach.

AI’s Evolution Continues

When you implement AI and deep learning tools, it’s essential to consider the challenges they may bring. While the benefits of AI are clear, mistakes can still occur because it is quickly evolving. Sometimes, AI may misinterpret what is happening, disrupting data or system availability. 

These disruptions could occur if AI detects what it thinks are illegal activities. For example, AI tools often work with a reliability score, triggering a response from your organization if the score falls below a preset threshold. If that happens in error, the result is costly unplanned downtime. As an evolving technology, AI can’t guarantee perfection, and the threat of errors will always exist. Regardless, AI will continue to improve its ability to distinguish real threats from other events. 

Getting Started With AI

While many companies are excited by AI’s potential, most don’t know where to start. The easiest way to leverage the benefits of AI is by working with a reliable security solution provider well-versed in deep learning and AI. Your vendor of choice should already incorporate AI into its products, as is the case with Arcserve Unified Data Protection (UDP) software. That way, you can realize the benefits of AI immediately. 

As the technology evolves, watch for more advances in data protection solutions that leverage AI and deep learning. In the meantime, strengthen your defenses by working with a solution provider with readily available AI-powered tools you can use to neutralize cyberattacks and protect against data loss.

Thanks for reading. 

For expert guidance in implementing AI-driven data protections, choose an Arcserve technology partner. 

Request a demo to learn more about the AI and deep-learning data protections included with Arcserve UDP.