What are the uses of AI cybersecurity?


Using AI for cybersecurity is not a brand-new idea. Security analysts have been using bots to detect and respond to threats faster and to automate repetitive tasks for decades. Over the years, these AI-based cybersecurity solutions have increased their bandwidth and accuracy.

Estimated reading time: 5 minutes

Today, they provide teams with relevant data and help them continually manage and improve security faster. What are some critical areas in which AI already benefits cybersecurity professionals?

Automation of Monotonous Tasks

Security teams are overwhelmed with tasks — many of which have to be repeated every day. Some of these repetitive duties involve data gathering and analysis, assessment of weaknesses, and organizing insights into comprehensive security reports.

When performed manually, said tasks require a lot of time and mental energy. Moreover, not every member of the team can perform them since certain jobs require more skill and expertise.

AI automates monotonous tasks such as data gathering, classification of security alerts, and even automates compliance. All of them have to be set on repeat because attack surfaces of companies change in minutes.

As a result of delegating these tasks to AI, security analysts get more time to allocate to critical or advanced issues that require more brain power.

Moreover, less skilled team members can rely on insights from automatically generated reports to patch up new vulnerabilities.

With an increasing number of hacking cases and security data that have to be continually managed, keeping up with it all is not even sustainable without the help of AI.

Teams have limited resources and have to use them wisely. AI makes every minute of their time count.

Assessment of Vulnerabilities

Regardless of how well the systems are protected and how many tools cover the software within the infrastructure, vulnerabilities can appear at any time. This is why it’s integral to continually seek for weakness in the ever-shifting attack surface.

AI-powered security tools scan the complete infrastructure of an organization. They gather their findings into reports, classify the threats based on the severity of risk, and alert the teams.

Typically, it would take months for employees to detect weaknesses within the systems. AI cuts that time down to just minutes.

This process enables security teams to fix flaws before hackers get a chance to exploit them. Essentially, it’s the process of discovering flaws before hackers do. Plus, it’s automated and repeated 24/7, leaving no digital stone unturned.

The best AI tools can detect vulnerabilities within the unique context of a company. Combined with machine learning, they can spot anomalies within a specific organization in real-time.

The secret to a well-protected attack is continual management. Severe flaws within the system that are not discovered early can be costly for the company if they turn to major incidents such as data breaches.

Streamlining Threat Detection and Response

cybersecurity man looking at computers ai

Some cyber threats slip through the cracks. The AI-based solution Threat Detection and Response (TDR) tool is designed to catch and identify cyberattacks that other tools didn’t prevent.

The longer an attack remains undiscovered, the more it burdens the company financially. This means that the business has to pay more to mitigate the threat, remedy the issue, and dedicate additional time to further secure the systems.

TDR identifies hacking activity early and responds to the threat — reducing the financial harm to the company.

To do so, the tool combines features such as:

  • Advanced threat intelligence
  • Automated threat remediation
  • Sophisticated data analysis

It also increases the visibility of the complete infrastructure of the business and gathers and analyzes the data that is relevant for the complete attack surface.

To do so, it covers all vectors that a company has — including email, IoT devices, mobile applications, and the cloud.

For teams, the results of the scan provide them with relevant data they can apply to protect the company against sophisticated threats.

Instead of getting many uncorrelated alerts they ignore, experts receive relevant data about critical threats they can apply to manually investigate and mitigate potential cyber-attacks.

Identification of Phishing Activity and Training

UC San Diego Health Phishing

The fight against social engineering is usually hyper-focused on phishing awareness training for the general workforce. While this is effective and can reduce the number of successful scams, it’s not an all-encompassing solution.

Because even companies that invest in phishing awareness training are not immune to successful scams. Therefore, they also need security tools that are better at detecting compromising emails.

But AI can take that detection a couple of steps further.

AI can detect phishing emails that contain compromised attachments and infected links, or analyze emails and websites to identify content that indicates phishing activity.

It also takes into consideration the unique context of a company when detecting possible phishing exploits — making it more accurate and nuanced compared to regular email filters that separate genuine emails from spam.

AI-Based Phishing Training and Testing

Besides the detection of phishing attempts, AI is useful for phishing training. It can be used to create more personalized and engaging phishing awareness training materials.

In addition to that, AI can be used to test employees with automated phishing attacks and determine if they would recognize the signs of a scam email.

AI for Cybersecurity Is the Key to Fighting AI Threats

The problem with AI is that cybercriminals have access to this technology, too.

They already use it to create malware that can bypass protective security solutions.

Thanks to AI, bad actors also spam companies with numerous attacks.

Skilled hackers can also use it to uncover vulnerabilities that allow them to exploit networks.

Besides highly technical hacking attacks, they leverage AI to conduct advanced phishing scams. For example, there have been reports of phishing scams that rely on impersonating the voice of a loved one over the phone.

Businesses, on the other hand, can rely on AI for cybersecurity to automate processes such as vulnerability assessment or threat detection and response to react to scaling threats as early as possible.

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