Cybersecurity and AI: Applications and Implications

Cybercrimes are increasingly sophisticated, are more prevalent and can be executed faster than ever.¹ To keep up with ever-evolving cyber attacks, cybersecurity professionals now regularly use AI technology to protect and fight back against cyber criminals. Artificial intelligence (AI) solutions enable cybersecurity teams to detect threats early, prioritize threats more effectively and reduce false positives in a fraction of the time, cost and manpower.²

However, for as beneficial as AI tools are, they're not foolproof. There are quite a few things to consider when implementing AI technology in your computer systems—most importantly, what is your main goal in using them, and who will monitor the AI to make sure it doesn't fail?

Here, we'll take a closer look at how artificial intelligence complements and challenges modern cybersecurity efforts.

Although it's a relatively new and still evolving technology, artificial intelligence has many applications in cybersecurity and enterprise information systems. And with its popularity, it's likely to become a mainstream security tool for most organizations in the coming years. Let’s explore how organizations can use it to protect themselves from specific cyber threats.

On average, it takes about 287 days for an organization to detect and contain a cyber attack.³ On all accounts, that’s far too long. By the time a company discovers a breach, the perpetrator will have already caused extensive damage to the organization’s network and/or will have stolen sensitive information.

To recover that time, AI-based cybersecurity systems help organizations quickly detect and mitigate cyber threats. AI tools can monitor systems, data centers and networks in real time to identify suspicious log-in attempts (brute-force attacks) and unauthorized data transfers (data exfiltration) nearly instantly.⁴ This is possible because AI algorithms automate threat detection by establishing baselines for normal behavior in a system or network. So, when any unusual activity starts to occur, the algorithms recognize that it may signify a breach to network security. This early detection is crucial for acting quickly and effectively.⁵

Additionally, an AI algorithm can classify and prioritize alerts by assessing potential threats and assigning them a level of urgency. Instead of rotating between several high-priority items, this helps security teams prioritize threats based on the scale and scope of the cybersecurity risks.⁴

Besides providing prioritized alerts, AI applications can also automate mitigation. For example, they can automatically shut down a network and isolate affected devices when a sequence of ransomware-related activity is detected.⁶

Instead of simply examining what happened during a breach, AI-based cybersecurity solutions reveal why the incident occurred, how it happened and the best way to avoid it again in the future. To achieve that, AI cybersecurity tools come with powerful analytics that reveal insights into breaches.⁴ The analytics include the following:

AI threat detection tools with descriptive analytics can analyze a company’s cybersecurity data and identify patterns. These insights can reveal exactly what happened during a breach. For example, descriptive analytics can show the specific type of attack and the affected systems.⁴

Cybersecurity artificial intelligence with diagnostic analytics can examine past events to identify the root cause of a cyber attack. Diagnostic analytics show how and why a cyber incident occurred by revealing specific changes and unusual activities that led to the breach.⁴

Prescriptive analytics provide insights into the best way to respond to a cyber attack and permanently eliminate the root causes. As a result, prescriptive analytics help organizations create more powerful cybersecurity policies and strategies to prevent breaches from recurring in the future.⁴

AI’s ability to automate threat detection and reveal hidden patterns in data sets makes it a powerful tool for defending against cyber attacks. The following are the three key benefits of utilizing AI in cybersecurity.

Nearly all successful cyber attacks have one thing in common: human error. Unfortunately, simple missteps in human behavior are the primary cause of 95% of cyber breaches.⁷ AI tools are automated, meaning organizations can avoid human mistakes, such as forgetting to install security updates in a timely manner.⁸

Whether a company uses artificial intelligence or human personnel to monitor threats, false positives will always be in the picture. Without AI, though, organizations may need to hire more security professionals to examine and fix these false positives.

Since AI and machine learning algorithms learn from the vast amounts of cybersecurity data they collect over time, they can better differentiate between normal network activity and unusual events. This makes AI reliable in preventing even the most sophisticated cyber breaches.⁸

Unlike a human, AI can protect an organization’s sensitive data around the clock without getting tired. Even better, AI is designed to identify threats as soon as they happen and mitigate them early, before they wreak havoc on the company.⁸

The benefits of artificial intelligence are undeniable, but just as any company can leverage AI to beef up its cybersecurity measures, cybercriminals can use the same technologies to launch more advanced cyber attacks.

For instance, adversarial machine learning is a sophisticated technique for exploiting vulnerabilities in AI technologies, which then can be used to manipulate AI-powered cybersecurity systems. Cybercriminals use adversarial machine learning techniques to launch different types of attacks, including the following:⁶

Starting at the source, hackers in a poisoning attack will inject corrupted data into the training data set of an AI model. The goal is to compromise the model’s learning process or degrade its performance, making its neural networks and cybersecurity solutions less effective.⁴

Evasion attacks fool AI systems into thinking that a cyber breach is a normal activity in a company’s IT network. Hackers make malicious data look normal to bypass systems without being detected.⁴

This type of attack reconstructs the training data of a targeted AI model to enable the cybercriminal to steal private data. The bad actor attempts to reverse-engineer, or “invert,” a machine learning model to gain insights into sensitive information, such as someone’s identity.^4,6

As the name suggests, model stealing is a malicious attack designed to steal details on an AI model. Perpetrators can use the stolen information to learn about the inner workings of an AI system, revealing vulnerabilities, weaknesses or design flaws they can exploit.⁶

AI solutions are not perfect, and neither are cybersecurity professionals. Instead of one replacing the other, the two can work together to bolster an organization’s cybersecurity defenses. For instance, organizations can use artificial intelligence to handle time-consuming cybersecurity tasks, such as analyzing logs and sending out threat alerts.

Meanwhile, cybersecurity personnel can focus on the tasks that require more human intervention, such as investigating sophisticated attacks, training new team members and creating security policies. Harmonious collaboration between the two can strengthen the organization’s security measures.⁸

If you want to develop your cybersecurity skills and stand out from other professionals, earning an online Master of Science in Cybersecurity from Yeshiva University is the right step to take. You’ll get hands-on experience and learn to apply your skills in any industry setting, helping companies implement artificial intelligence safely and effectively. With this skill set and knowledge, you'll be an invaluable asset wherever you choose to go next.

Contact an admissions outreach advisor to start preparing for a better future.