The Role of AI in Cybersecurity: The Continuing Need for Cyber Professionals

As the technology landscape continues to develop and progress, innovations like artificial intelligence (AI) are transforming the way the industry operates and impacting the full range of tech fields within it. Cybersecurity is one of the fields experiencing this revolution, with AI now enabling newer and faster methods for detecting and preventing digital threats. For example, organizations can automate and streamline processes to identify and contain cyber-attacks more quickly using AI-powered incident response tools.

While only an estimated 28% of companies have adopted AI extensively for cybersecurity operations, according to IBM's Cost of a Data Breach 2023 global survey, more companies are seeking to invest in the technology due to factors like potential cost and time savings.

AI may seem like it will replace humans in information security and IT, but in reality, the trend is shifting more toward professionals working with AI models, similar to how assistance tools like spell check or code completion aids like IntelliSense have been used in the past. Despite the integration of AI, the need for cybersecurity professionals continues to grow in all sectors.

Read on for reasons why trained cybersecurity professionals remain indispensable and explore some of the uses of AI in this field, its benefits, and challenges.

Rising Cybersecurity Threats

Cyberattacks are on the rise, putting personal data, financial information, and even national security at risk. The number of cyberattacks worldwide increased by 38 percent in 2022, according to a report by Check Point Research. In 2023, this trend is expected to continue and potentially lead to $10.5 trillion in projected costs by 2025, according to a report by Cybersecurity Ventures.

With an ongoing global cybersecurity skills shortage and the increasing complexities of digital threats, AI plays an increasingly vital role in both offensive and defensive cybersecurity strategies.

Types of AI Cybersecurity Threats

In the world of cybersecurity, AI has become a double-edged sword, being used by both malicious cybercriminals and vigilant professionals alike. The following are some examples of types of AI cyberthreats:

AI-powered phishing attacks: Using AI large language models, such as GPT-4, cybercriminals create tailored phishing emails that are more likely to fool targets. By utilizing AI, cyber criminals can generate emails in a style and consistency matching official communications from credible banks, credit card companies, or any number of other institutions in order to trick even cyber-savvy users into sharing their sensitive information.

AI-powered malware: The use of AI by cybercriminals is making malware more difficult to detect and remove. Sophisticated malware can intelligently adjust its own code to avoid signature-based detection and even make real-time adjustments to its own functionality.

AI-powered deepfakes: A deepfake is a video or audio recording manipulated to give the impression that someone is saying or doing something that they have never actually said or done. Many tools and systems used by cyber criminals to create deepfakes are not intended for that purpose. Today it is possible to generate audio in someone’s natural voice using only a few seconds of their speech. It is possible to spread incorrect information, damage reputations, or commit fraud with AI deepfakes.

For organizations and cybersecurity professionals, AI offers a range of indispensable capabilities and ever-evolving threats.

Uses of AI to Combat Online Threats

According to the same survey referenced above, data breaches were detected and contained, on average, 108 days faster within organizations that incorporated AI capabilities extensively into their security posture. The costs of data breaches were lower by $1.76 million USD compared to organizations without AI and other automation capabilities. It was also found that 51% of organizations plan to increase their security investments in incident response, employee training, and threat detection and response technologies.

Additionally, around 71% of IT and cybersecurity professionals surveyed earlier this year, reported that their organizations were affected by the cybersecurity skills shortage, according to Enterprise Strategy Group (ESG) and Information Systems Security Association.

In order to respond to digital attacks more effectively and reduce some of the ongoing impacts of the cybersecurity skills shortage, some organizations are utilizing AI tools to perform:

Threat detection: By analyzing network traffic, log files, and security events, AI is able to detect suspicious patterns and anomalies that could indicate a cyberattack.

Incident response: AI can automate many of the processes involved in responding to an attack, such as notifying the security team, identifying the affected systems, containing damage, and eradicating threats.

Risk assessment: AI helps to provide insight into how vulnerable an organization's systems and assets are to cyber threats. By leveraging this data, security investments can be prioritized, and risk mitigation strategies can be developed with a clear understanding of the risks associated with them.

Compliance: AI is used to help organizations comply with complex cybersecurity regulations. For example, AI can be used to identify and monitor sensitive data, and to detect and report on data breaches.

Through AI and automating some offensive and defensive tasks, cybersecurity professionals can focus on more strategic and complex tasks. AI may also improve the decision-making abilities of cyber professionals by streamlining the collection and sorting of digital information, as well as analyzing patterns in the data.

How Is AI Cybersecurity Different From Traditional Cybersecurity?

Cybersecurity protection boosted by artificial intelligence can never fully replace security professionals. Human capacity is always needed to solve creative problems and address the more complex challenges in the workplace. However, AI can (and does) help human security professionals by analyzing colossal amounts of data, spotting patterns, and developing insights based on this security data. In contrast, traditional security processes often take hours, sometimes days or weeks, to complete this task.

Before the advent of AI, security professionals relied on signature-based detection tools and systems to spot potential cyber threats. These tools typically compare incoming network traffic to databases that store known threats or malicious code signatures. When an issue is detected, the system triggers an alert and suggests that the security professional block or quarantine the threat.

Traditional cybersecurity often depends on manual analysis. This means security analysts must manually investigate security alerts and event logs, searching for identifiable patterns that may indicate a potential security breach. However, investigating logs and events is often time-consuming, typically relying on a single security analyst.

Why Is AI in Cybersecurity Important?

Cybercriminals have invested in AI, machine learning, and automation to launch large-scale, targeted cyberattacks against many organizations. The number and types of threats against networks continue to grow.

AI and machine learning are the great equalizers for security analysts. They can process massive amounts of data, providing rapid, analysis-based insights and slicing through the fog of daily security alerts and false positives. This approach drastically improves a cybersecurity team's efficiency and productivity, giving them an advantage over potential cyber criminals.

Is it Safe to Automate Cybersecurity?

Automating cybersecurity is safe, provided it enhances human oversight and expertise. However, it should never substitute for cybersecurity professionals, as it brings certain challenges, as mentioned below.

The Applications of AI in Cybersecurity

Here are some ways that AI can be applied to cybersecurity.

• SOC operations. Managed detection and response (MDR) providers recognize the great potential in leveraging AI to improve and optimize their security operations center’s (SOC) overall performance and operational efficiency. AI can aid in identifying and addressing operational bottlenecks, security gaps, or shortcomings.

• Threat hunting and threat intelligence. Deep neural networks can train machines to detect and identify threats like malware. AI collects, processes, and enriches threat data from diverse sources across the organization, correlating and contextualizing that data to develop threat profiles, measure against indicators, and discover new emerging threats. AI also facilitates proactive threat hunting, where cybersecurity professionals use advanced analytics and automation to find hidden or unknown threats.

• Cybersecurity training and development. AI can assess and enhance SOC analysts' relevant competencies, skills, and knowledge. Since AI has the power to learn and continuously improve, MDR vendors can develop highly personalized learning paths. Additionally, organizations can develop realistic and interesting security simulations, training scenarios, and exercises.

• Security innovation. Today's SOC must quickly adapt and evolve its capabilities, responding to constantly changing customer needs and threat landscape. MDR providers use AI and ML to keep their SOCs ahead of the curve, thereby reducing risk.

The Benefits of AI in Cybersecurity

Here’s a list of some of the significant benefits of AI in cybersecurity.

• It offers transparent solutions. AI ensures its recommendations and analyses are understandable and transparent, fostering collaboration and support from stakeholders at all organizational levels, including management, end users, security operations, and auditors.

• It exposes threats: AI can remain informed and current about global and industry-specific threats, which can help organizations prioritize security measures based on incident likelihood and potential impact.

• It maintains an inventory of IT assets: AI can achieve a comprehensive, accurate inventory of all users, devices, and applications with access to information systems while it categorizes and assesses business criticality.

• It controls effectiveness. AI can strengthen an organization’s security posture by assessing the impact and efficacy of existing security tools and processes.

• It can predict breach risks: AI can predict vulnerability and potential breaches by considering IT asset inventory, threat exposure, and control effectiveness, allowing proactive resource allocation for mitigation.

• It makes incident response more efficient. AI provides contextual insights that can prioritize and respond quickly to security alerts, spot root causes, and improve the entire incident management process.

The Challenges and Risks of AI in Cybersecurity

Remember: AI as a technology is still in its infancy, and it still relies on humans to train its engines and intervene if an engine commits an error. AI-driven security systems depend on machine learning algorithms that use historical data to learn from. This can result in false positives if the system encounters new or unknown threats that don’t conform with existing patterns. An additional troubling issue is the question of how hackers could potentially leverage AI for malicious purposes, such as composing more convincing phishing e-mails or churning out better malware.

Here’s a short list of some of the significant risks facing AI in cybersecurity:

• Organizations might become complacent and overconfident that automated systems can catch every threat.

• Automation workflows could be vulnerable to instances of unauthorized data access.

• Automation might introduce vulnerabilities, resulting in more security incidents.

• Automated tools might find it challenging to adapt to new threats, resulting in false positives and negatives.

Why AI Can't Fully Replace Cybersecurity Professionals

Although AI offers a number of benefits, such as automation and predictive analysis, it is equally important to acknowledge its significant limitations. A key factor in maximizing the potential of AI for an organization is possessing cybersecurity professionals to work alongside it and question information and outcomes. Here are just some of the many ways in which cybersecurity professionals address the limitations of AI and continue to add value to organizations.

Critical Thinking and Innovation: Patterns and historical data form the basis of AI. Cybersecurity professionals, on the other hand, possess innovative problem-solving skills to handle new and unfamiliar challenges. While AI excels at detecting known threats, human expertise remains essential for addressing unforeseen threats.

Bias and False Positives: Although AI systems are capable, biases can cause false alarms and missed threats, putting organizations at risk. Security professionals are critical in deciphering and analyzing the broader context to identify and reduce inaccuracies to enhance security posture by leveraging their judgment and experience.

Vulnerability to Exploitation: AI systems themselves can become targets for exploitation by cybercriminals. If attackers compromise AI-driven security measures, the consequences can be disastrous. Cybersecurity professionals are essential in securing and maintaining these systems.

Comprehensive Security Strategy: Beyond identifying risks, cybersecurity professionals help organizations develop comprehensive security plans and strategies. The strategies include not only technological solutions, but also policies, procedures, and training for employees.

Due to these limitations, cybersecurity professionals are highly in demand. More than 600,000 cybersecurity positions are available across the nation, reported Cyberseek.org. Roles like information security analyst are projected to grow 33% from 2020-2030, according to U.S. the Bureau of Labor Statistics.

By learning cybersecurity, you can make a meaningful impact and benefit from the growing demand for professionals. Consider enrolling in a Fullstack Academy Cybersecurity Analytics Bootcamp to gain the skills and knowledge necessary to meet the needs of this dynamic and ever-evolving field. Learn live online, part-time, or full-time from field-knowledgeable professionals and an immersive, hands-on curriculum that prepares you for industry-recognized certification exams.