Artificial intelligence (AI) has been part of computing since the 1950s, when a robotic mouse learned how to make its way out of a maze. In the 1990s, intelligent software learned how to beat humans at backgammon.1 The early 2000s brought realistic photo generation, large-scale text translation, automatic subtitles and CAPTCHA codes that hoped to tell humans apart from machines. Now, AI can schedule flights, track biometrics, and soon, drive cars. Behind these exciting innovations are teams of software engineers, data scientists, computer programmers and machine learning specialists who help AI learn by providing massive amounts of data.
Cybersecurity specialists are responsible for safeguarding the data, information and networks used to power AI. They can even teach AI how to protect itself from potential threats and malicious activity. These advancements have many people wondering if cybersecurity jobs will eventually become obsolete. But rather than replacing trained personnel, companies and organizations are using AI to supplement and optimize their cybersecurity efforts.
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How is AI used in Cybersecurity?
Some of the simpler ways that AI is used in cybersecurity include password protection, phishing detection and automatic software updates. Over the past several years, the field has discovered other advanced applications. Automatic threat detection and generative security processes are two of the most important examples of how AI is used in cybersecurity today.
AI Threat Detection and Generative AI Security
One of AI’s biggest contributions to cybersecurity is threat detection, which is how AI can identify and report cyber threats. With the right training and data sets, AI can protect itself against unwanted user access, data breaches and malicious software. According to Fortinet, a cybersecurity solutions company, AI can add extra layers of security to sensitive data by continually monitoring access attempts, identifying new strands of malware and creating security alerts.2
Once AI has learned how to detect threats and generate appropriate responses, an organization can save valuable time and resources. AI makes faster decisions, analyzes multiple data sets at once and draws upon historical data on-demand. With reliable threat detection and reporting capabilities, cybersecurity professionals can act against threats almost immediately.
More Examples of AI and Cybersecurity
AI offers several other benefits to the field in addition to threat detection and generative security:
- Continuous Learning: AI never stops learning from the data it interacts with, so it stays on the leading edge of cybersecurity trends, techniques and vulnerabilities. AI can deliver these critical insights directly to employees, including raw data and detailed analysis. Once security teams decide which data is the most valuable, they can provide their feedback to AI, creating a continuous learning loop.
- Efficiency: Because AI can help perform routine business tasks, analysts and cybersecurity personnel can place more focus on higher-impact operations. Some of the daily tasks that AI can assist with include network status updates, periodic data collection and firewall monitoring. With tasks like these taken care of, cybersecurity professionals can devote more time to complex data analysis, system upgrades, and fraud investigations.
- Behavioral Authentication: AI can analyze subtle, contextual data from users, such as login times and locations, typing styles and voice inflections. Identifying these patterns helps it recognize when variations might indicate a security risk. If an employee who works from home logs into a company network on a different IP address, for example, AI could immediately flag the company’s security team. Then, someone might reach out to the employee and make sure their device isn’t stolen or compromised.
Real-World Example: Triaging Security Alerts3
Security analysts at a Top 10 U.S. bank were sifting through over 900 security alerts each month, which took about 127 analyst hours per week – more than three full-time employees. On average, only three out of 900 alerts per month were legitimate, which meant that analysts were wasting significant time investigating false positives. With AI-powered threat detection software, the bank drastically reduced the analysts’ workload. AI offered additional context surrounding each alert so that analysts could quickly determine whether the alert was legitimate. Not only was the process much faster, but the accuracy of triaging alerts improved by three percent.
AI Security Risks
AI and cybersecurity innovations have a downside—cyber attackers are using the same technology, and they have upgraded their techniques. Some emerging risks are:
- Phishing: ChatGPT and similar language tools help attackers write more realistic, convincing phishing scams than in the past. As they craft their scams, Forbes reveals that hackers might train AI to identify potential targets, drawing on company datasets and even information provided on social media.4 Targets could be more likely to act on personalized phishing attempts rather than generic.
- Adversarial Machine Learning: Malicious users work to find weaknesses in AI algorithms, and then disrupt the algorithm’s behavior for their benefit. As examples, the Cybersecurity & Infrastructure Security Agency (CISA) explains that hackers can manipulate training data, adjust predictive models, steal data and more.5
- Deepfakes: A combination of “deep learning” and “fake,” a deepfake describes extremely realistic media created entirely with AI. Deepfakes require massive amounts of data about the media they’re creating. If creating an individual’s likeness, for example, the dataset needs good-quality photos and videos of the person. If given examples of a person’s writing and speaking, AI can even mimic speech and language patterns.
Real-World Example: CFO Deepfake6
In February 2024, a finance employee in Hong Kong held an important video conference call with the firm’s Chief Financial Officer (CFO) and other members of the department. With the reassurance of his manager and colleagues, this employee signed off on a confidential transaction of $200 million Hong Kong dollars – about $25.6 million U.S. dollars. Several months later, the company’s head office confirmed that the video conference call was an elaborate AI deepfake. The Hong Kong CFO and finance department were never involved in the video call, but the deepfake was so convincing that it didn’t raise any red flags with the employee who was targeted.
Will AI Replace Cybersecurity Jobs?
AI will likely become an essential component of any organization’s cybersecurity operations. It can enhance existing security efforts and learn to adapt to rapidly changing cyber threats within seconds, but only if it knows what to look for. Qualified cybersecurity professionals will continue to be indispensable, although their day-to-day work might change. Employees will need specialized skills to guide AI’s learning paths, confirm data analysis and protect software, networks and data sets.
These skills are in high demand. In an official 2023 report on global cybersecurity jobs, Cybersecurity Ventures projects 3.5 million unfilled jobs in the industry through 2025.7 Employers are urgently seeking those who can help them protect assets and avoid financial losses from cybercrime. According to Cybersecurity Ventures, the cost of cybercrime is expected to reach $10.5 trillion USD by 2025.7 Cybercrimes affect nearly every industry, so computer and IT professionals who are AI-savvy can stand out for advancement no matter what career path interests them.
In the U.S., computer and IT occupations are growing faster than the average for all other occupations, with some roles experiencing even more rapid development. The U.S. Bureau of Labor Statistics projects average annual job openings for the following computer and IT occupations each year from 2022 to 2032:8-12
- Computer and information research scientists: 3,400
- Computer systems analysts: 37,600
- Database administrators and architects: 10,200
- Information research analysts: 16,800
- Network and computer systems administrators: 19,800
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- Data Security
- National Security
- Security Management
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Sources
- Roser, Max. “The brief history of artificial intelligence: the world has changed fast — what might be next?” Our World in Data. December 6, 2022. Retrieved July 22, 2024, from https://ourworldindata.org/brief-history-of-ai.
- Fortinet, Inc. “Role of Artificial Intelligence (AI) in Cybersecurity: Why Is Artificial Intelligence (AI) Important In Cybersecurity?” Retrieved July 22, 2024, from https://www.fortinet.com/resources/cyberglossary/artificial-intelligence-in-cybersecurity.
- Leichter, Willy. “Automating Threat Detection: Three Case Studies.” Security Boulevard, powered by Techstrong Group. May 20, 2022. Retrieved July 22, 2024, from https://securityboulevard.com/2022/05/automating-threat-detection-three-case-studies/.
- Benishti, Eyal. “Prepare For The AI Phishing Onslaught.” Forbes. March 3, 2023. Retrieved July 22, 2024, from https://www.forbes.com/sites/forbestechcouncil/2023/03/03/prepare-for-the-ai-phishing-onslaught/.
- Cybersecurity & Infrastructure Security Agency (CISA). “Roadmap for AI.” Retrieved July 23, 2024, from https://www.cisa.gov/resources-tools/resources/roadmap-ai.
- Chen, Heather, & Magramo, Kathleen. “Finance worker pays out $25 million after video call with deepfake ‘chief financial officer.’” Cable News Network (CNN). February 4, 2024. Retrieved July 23, 2024, from https://edition.cnn.com/2024/02/04/asia/deepfake-cfo-scam-hong-kong-intl-hnk/index.html.
- Cybersecurity Ventures. “2023 Official Cybersecurity Jobs Report.” eSentire. Retrieved July 23, 2024, from https://www.esentire.com/resources/library/2023-official-cybersecurity-jobs-report.
- U.S. Bureau of Labor Statistics. “Computer and Information Research Scientists.” Occupational Outlook Handbook. April 17, 2024. Retrieved July 23, 2024, from https://www.bls.gov/ooh/computer-and-information-technology/computer-and-information-research-scientists.htm.
- U.S. Bureau of Labor Statistics. “Computer Systems Analysts.” Occupational Outlook Handbook. April 17, 2024. Retrieved July 23, 2024, from https://www.bls.gov/ooh/computer-and-information-technology/computer-systems-analysts.htm.
- U.S. Bureau of Labor Statistics. “Database Administrators and Architects.” Occupational Outlook Handbook. April 17, 2024. Retrieved July 23, 2024, from https://www.bls.gov/ooh/computer-and-information-technology/database-administrators.htm.
- U.S. Bureau of Labor Statistics. “Information Research Analysts.” Occupational Outlook Handbook. April 17, 2024. Retrieved July 23, 2024, from https://www.bls.gov/ooh/computer-and-information-technology/information-security-analysts.htm.
- U.S. Bureau of Labor Statistics. “Network and Computer Systems Administrators.” April 17, 2024. Retrieved July 23, 2024, from https://www.bls.gov/ooh/computer-and-information-technology/network-and-computer-systems-administrators.htm.