It is humanly impossible to keep up with the ever-changing tech landscape of the world. What is released today could be outdated tomorrow. This is true even for cyber threats, with new and smarter ones being released almost every day. In the world of cybersecurity, threats can come from all angles – hackers, viruses, malware, and more. To keep our computer systems safe, we need to be proactive in detecting and preventing these threats. This is where AI, or artificial intelligence, comes in. If you are wondering: how can AI improve cyber security, you are in the right place. Find out what is AI in cybersecurity, benefits of AI in cyber security, AI in cybersecurity examples, and more in this guide.
Benefits of AI in Cyber Security: Use Cases and Examples
AI is making life easier for everyone. It is also making it more effortless for companies to improve their cyber security infrastructure. Learn how benefits of AI in cyber security are helping companies to stop possible cyber attacks from harming their virtual assets.
Must Read: What is Ethical Hacking?
What is AI in CyberSecurity?
AI is a powerful tool. With its capability to perceive, learn, and understand AI has become a necessity in many industries. So what is AI in cybersecurity? and how is it changing the cybersecurity landscape?
AI can offer advanced tools to help organizations combat threats and make networks and services more secure. AI can prevent known and unknown threats using its machine learning capabilities to learn and understand attack patterns and make the systems more robust against any possible attacks similar to what it may have experienced before. Over time, it will improve after facing more and more sophisticated attacks and learning to protect your organization’s digital assets from attackers.
It can also respond quicker than humans and surpass traditional systems, thus helping organizations to minimize damage from cyber threats.
How is AI Used in Cybersecurity?
AI can be the best tool for your organization’s cybersecurity team if you know how is AI used in cybersecurity.
- Improved threat detection: AI algorithms can be trained to detect patterns and anomalies in data, such as network traffic, to identify potential security threats. For example, AI can detect unusual patterns in user behavior, identify malicious software, and recognize known malware signatures.
- Advanced threat intelligence: AI is used to analyze large amounts of data from various sources, such as social media or the dark web, to identify potential threats before they become a problem. This can help organizations take a proactive approach to cybersecurity rather than simply reacting to threats as they occur.
- Automated incident response: AI can assist in the incident response process by automating certain tasks, such as identifying the source of a security breach and suggesting the best course of action to resolve the issue. This can help organizations respond more quickly and efficiently to security incidents.
- Improved fraud detection: AI helps to detect and prevent fraudulent activities, such as identity theft and payment fraud. AI algorithms can learn from patterns of fraudulent behavior and identify new types of fraud more quickly than traditional methods.
- Enhanced vulnerability management: AI can help organizations identify vulnerabilities in their systems and prioritize which ones to address first based on the level of risk they pose. This can help organizations better manage their resources and focus on the most critical vulnerabilities.
AI in Cybersecurity Examples
AI has already become a part of cybersecurity around the world. Here are some AI in cybersecurity examples that showcase how well AI has been integrated to protect the virtual assets of an organization.
1. Microsoft Defender for Endpoint
Microsoft Defender for Endpoint is a cloud-based endpoint protection platform that uses AI and machine learning to detect and respond to threats. The platform uses AI to analyze behavioral patterns and identify suspicious activity on endpoints.
Darktrace is an AI-powered cybersecurity platform that uses machine learning to detect and respond to threats in real-time. The platform uses AI algorithms to analyze network traffic and identify atypical behavior, even in encrypted traffic. Darktrace has more than 30 offices around the world and has helped its clients to protect their digital assets against cyber threats.
3. Palo Alto Networks Cortex XDR
Palo Alto Networks Cortex XDR is an AI-based platform that uses machine learning and inline deep learning to detect and respond to threats across multiple endpoints and clouds. The platform uses AI to analyze threat data and identify patterns that indicate potential security incidents. It also offers its users firewalls and cloud security services.
4. Symantec Endpoint Protection
Symantec Endpoint Protection is an AI-powered endpoint protection platform that uses machine learning to detect and respond to threats. The platform uses AI to analyze threat data and identify patterns that indicate potential security incidents.
5. IBM Watson for Cybersecurity
IBM Watson for Cybersecurity is an AI-based platform that uses machine learning to analyze security data and identify potential threats. The platform uses AI algorithms to identify patterns and anomalies in security data and provide insights to security teams. It helps your Cybersecurity team by automating repetitive Security Operations Center (SOC) tasks, conducting deeper investigations, and helping gain actionable insights into critical incidents.
Hence, these were AI in cybersecurity examples.
Disadvantages of AI in CyberSecurity
Artificial Intelligence is a game changer in any industry. But there are several disadvantages of AI in cybersecurity as well.
- Replacing Humans: AI can be a powerful tool for automating cyber security in an organization. But this makes the human cyber security personnel useless as their work is already being performed by a computer. Maybe this isn’t a reality right now but sooner or later AI will take over the jobs of cyber security personnel, rendering them pointless to the organization.
- False positives: AI algorithms can sometimes generate false positives, flagging legitimate activity as suspicious or malicious. This can lead to unnecessary investigations or security alerts, which can be time-consuming and costly for organizations.
- Complexity: AI systems can be complex and difficult to understand, which can make it challenging for security teams to effectively manage and monitor them.
- Dependence on data quality: AI algorithms rely on high-quality data to provide accurate results. If the data used to train an AI model is biased or incomplete, it can lead to inaccurate results and false positives or negatives.
- Cybercriminals can use AI too: Cybercriminals can also use AI and machine learning to develop more sophisticated and effective attacks. This can create a cybersecurity arms race, where organizations need to constantly adapt and improve their AI systems to stay ahead of cybercriminals.
- Potential for misuse: Like any technology, AI can be misused by individuals or organizations for malicious purposes, such as conducting cyberattacks or stealing sensitive information.
How Can AI Improve Cyber Security?
AI can improve cybersecurity by helping organizations detect and prevent potential threats more quickly and accurately, take a proactive approach to cybersecurity, automate certain tasks in incident response, and enhance fraud detection and vulnerability management. AI can improve itself over time, and with its machine learning abilities, it will only get stronger.
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We hope that this guide was helpful and you were able to understand the benefits of AI in cyber security. Let us know how you find this article and if you have any queries or, suggestions then feel free to drop them in the comments section below.