Cybercrime is a growing threat, and businesses are scrambling to hire qualified security talent to keep up. There will be 3.5 million unfulfilled cybersecurity jobs by 2021.
So what happens when there aren’t enough humans to fight back against the cybercriminals? The security industry is seeking help from the machines.
Why Is the Cybersecurity Industry At Risk?
Cybersecurity Ventures predicts that cybercrime will cost the world $6 trillion annually by 2021.
Cyberattacks advance in sophistication every day, and businesses always seem to be one step behind the bad guys. Hackers are constantly finding new ways to outsmart seemingly secure systems.
The idea that businesses can combat the increasing number of security issues by putting more people on the job is unrealistic. Human error is one of the most common causes of security failures.
No matter how many security employees you hire, someone will always forget to deploy a new patch. Your employees will never stop opening suspicious attachments from unknown sources. And analysts are bound to overlook major vulnerabilities at some point.
To make matters worse, there is a massive shortage of cybersecurity experts in the market. One report predicts the global security workforce will be short 1.8 million cybersecurity professionals by 2022.
The state of the cybersecurity industry looks dismal – but there’s no need to give up just yet. Security experts predict that artificial intelligence-based technologies will play a major role in winning the war against cybercriminals and eliminating human error.
How Does AI Benefit the Cybersecurity Industry?
Artificial intelligence enables machines to learn, think and act intelligently like humans do. AI systems combine large amounts of data with intelligent algorithms to learn from patterns, generate insights, make informed decisions and adapt.
AI has many practical purposes in the world of cybersecurity. 12 percent of enterprises have already deployed extensive AI-based security analytics, and 27 percent have deployed them on a limited basis.
Organizations are using AI-based cybersecurity technology to:
- Accelerate incident detection: AI can sort through software vulnerabilities, threat intelligence and configuration errors to isolate high-risk situations that call for immediate attention.
- Automate incident response: AI has the ability to prioritize certain types of incidents and automate remediation tasks for simple threats and attacks, freeing up valuable time for IT employees.
- Categorize attacks based on threat level: Deep learning is a machine learning technique that allows algorithms to do more independent adjustments and self-regulation as they train and evolve. Deep machine learning principles can adapt over time, helping businesses identify threats faster and maintain a dynamic edge over cybercriminals.
- Better understand cybersecurity situational awareness: AI can provide IT experts with a unified view of the organization’s security posture, reducing the need for humans to make sense of massive amounts of data.
52 percent of security professionals say AI systems have trouble correctly prioritizing threat alert systems, proving there’s still much work to be done. But AI offers a hopeful solution to the onslaught of sophisticated cyberattacks.
How Can AI and Machine Learning Help Contain Cybersecurity Threats?
At its core, machine learning’s biggest security benefit is learning to understand what is “normal” for a system and flagging anything abnormal for humans to review. Machine learning acts as a piece of the overall security solution rather than a standalone cure-all.
AI is already commonly used in anti-malware software in the form of machine learning systems. The AI algorithms learn from millions of samples and behavioral patterns of malicious programs to define suspicious activity and how to react to diverse situations. The scanning tool learns to look for characteristics of malware rather than specific signatures, offering a more holistic view, which makes a hacker’s job more difficult.
AI Technologies to Keep on Your Radar
Some big technology players are already making waves in AI-based cybersecurity technologies.
Google has been using machine learning to fight back against spam and phishing for years. Earlier this year, Alphabet, Google’s parent company, announced the launch of a new cybersecurity intelligence platform called Chronicle. Chronicle hopes to tackle cybersecurity on a global scale by combining Google’s existing AI, machine learning, infrastructure and “near limitless compute” capabilities.
Another rising player is Magnifier from Palo Alto Networks. The behavioral analytics solution is already available for businesses to download. It uses structured and unstructured machine learning to analyze network, endpoint and cloud data to improve threat detection and response.
The Dangers of AI in Cybersecurity
Unfortunately, the cybersecurity industry isn’t the only group utilizing AI and machine learning. The bad guys are adapting just as fast.
Researchers warn about the ways attackers are adopting machine learning techniques themselves. Cybercriminals already have access to hacking tools that use machine vision to defeat Captchas.
Hackers will also look for ways to confuse AI models — a practice known as adversarial machine learning or adversarial AI. Hackers can study machine learning models and find ways to manipulate them, evade detection or poison the data to compromise the learning process.
Is Artificial Intelligence the Future of Cybersecurity?
Only 30 percent of cybersecurity professionals consider themselves very knowledgeable about AI and its application to cybersecurity. And experts have mixed opinions when it comes to the safety and reliability of AI.
Some critics say artificial intelligence relies too heavily on feedback to learn what’s good and what’s bad. Others say AI is too prone to reverse engineering.
Artificial intelligence still has a long way to go. But if businesses can figure out how to harness AI to support cybersecurity initiatives, they might uncover the key to surviving in the increasingly hostile security landscape.
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