Artificial Intelligence

9 Examples of AI in Cyber Security in 2021

In this article, I will cover the 9 examples of AI in Cyber Security in 2021. The world of cybersecurity has been experiencing a lot of changes recently, with the rise in use and necessity for Artificial Intelligence (AI).

Artificial intelligence offers a promising way for cybersecurity professionals to keep up with this ever-changing landscape. As an emerging technology, it’s still in its early stages but there are already plenty of examples where AI experts anticipate that AI will play a significant role in cybersecurity efforts by 2021.

Artificial Intelligence

How AI is used in cybersecurity?

Security is a never-ending game of cat and mouse, with hackers finding new ways to infiltrate networks faster than the security industry can respond.

AI is used to protect data by analyzing potential risks and vulnerabilities. AI systems monitor network traffic, identify attack vectors and alert the human security team before a breach can occur.

When it comes to protecting critical infrastructures like power grids or water supplies from cyberattacks, experts say that given time, AI could be able to predict when an intrusion will happen to cybersecurity, AI is used to detect and halt attacks.

With machine learning algorithms that can identify patterns in network traffic, these defenses have the potential to be more accurate than traditional tools like firewalls or intrusion prevention systems (IPS), as they are better able to learn which types of behavior are malicious and alert a human analyst about them before an attack is executed.

In the future, AI could be used to create simulated environments that mimic how an attack would unfold in a real-world system and identify potential vulnerabilities before they are exploited.

Let’s explore the 11 examples of AI in cybersecurity in 2021. The 11 examples listed below are just some of the ways that artificial intelligence can be applied to help safeguard your organization’s systems and networks in the near future.

1. AI will help detect and prevent cyber-attacks

AI can predict malware before it has been developed!

One way that artificial intelligence will help fight cybercrime is by predicting malware before it has even been developed.

AI is used in automated forensics tools to investigate malware or other attackers: AI is currently being used by some companies in the automated forensics tools that allow them to investigate malware and/or other attackers without user intervention.

AI can analyze code and point out flaws that could lead to a data breach: Artificial intelligence is being used by some cybersecurity firms which analyze code and points out any weaknesses or potential loopholes that might allow for breaches of sensitive information.

Artificial intelligence is reducing the time it takes to analyze huge amounts of data. AI can complete in hours what would take humans days or weeks, which means that fewer people will need to be on hand for tedious manual work and more staff members can do other tasks.

AI also is helping to reduce the false alarm rate for IT security incidents, which means that enterprises can respond immediately when a serious threat does happen.

Some organizations are using AI in an effort to identify and prevent malicious code from being downloaded into their systems. Some of these programs could be able to detect potential vulnerabilities before they become actual threats.

2. AI can identify potential cyber threats faster than humans

AI can identify potential cyber threats faster than humans. Machine learning algorithms are already being used to scan for malware and other types of bad content on the Web, as well as in email spam filtering or detection systems. AI is also capable of detecting cybersecurity attacks based on a plethora of different data points (such as location, time zone, language settings, etc.).

This is very powerful because it is not possible for anyone person to know all of the different attack vectors. AI can also detect if a user in an organization has had their credentials compromised by monitoring how they use the data and what types of transactions are being conducted on the company’s systems.

In the past, AI has been used to create “wardriving” applications that monitor public Wi-Fi networks and identify potential security vulnerabilities in those connections.

Ai is also being integrated into many different types of firewalls where it can detect suspicious activity when a new connection is attempted or an outgoing connection is made.

Google, for instance, has integrated AI into its Chrome browser that can detect malware and alert the user to a potential threat before anything bad happens.

AI may not be able to solve all of the cybersecurity problems by itself yet but it does have some powerful applications in these cases where humans are unable to do everything on their own.

3. AI can predict the risk of a cyber-attack before it happens

The way AI can predict cyber-attack before it happens is by finding patterns in the data.

The AI learns from previously collected information and watches for anomalies that are outside of those parameters, which will trigger a potential threat. For example, if there is an increase in attempted logins to your files after hours when no one should be on the system, then it can predict with high likelihood that someone has gained access to your system.

AI can also learn from an attacker’s behavior, and understand the way they act when they are on a system that has been compromised. This will allow AI to isolate patterns in order to predict what is happening before it occurs.

5. AI will reduce the need for human security analysts

AI will reduce the need for human security analysts by performing many of the same tasks that humans do, like detecting malware and hacking attempts. AI will also provide a more efficient means to detect vulnerabilities in security infrastructure as well as new patterns emerging across detected threats.

Ai will help with solving cybersecurity problems that are not easily solved by a human. For example, AI can use machine learning to generate new signatures for detecting malware and hacking attempts when no signature exists yet or is appropriate in the given context. An analyst would have to manually create these signatures which could take days or weeks of intensive manual work. With ai, this can be accomplished in just seconds.

AI will also help provide an understanding of the potential severity or risks associated with cyber threats by identifying various factors such as where there is overlap between malicious actors and tactics over time. AI’s capability for detection and remediation is expected to reduce cybersecurity costs including external audits not be detected by human eyes or security systems.

6. AI will be able to monitor social media conversations in real-time

Monitoring social media conversations is an essential part of cybersecurity. It reveals who has an influence on the internet and what they are talking about, which can reveal vulnerabilities or other threats to a company’s network.

AI will be able to monitor these messages in real-time by scanning posts for keywords that could indicate malicious intent, such as phishing scams, malware, or other malicious content.

AI will also be able to analyze posts for sentiment and the popularity of a topic among users on social media networks. This technology is being developed by research institutes in China, Japan, Korea, Singapore, and the United States with high expectations that it will become a key tool in fighting cyber threats.

7. AI can identify abnormal behavior on a network or device that may indicate an intrusion attempt

AI can identify abnormal behavior on a network or device that may indicate an intrusion attempt. In this method, the AI software monitors and analyzes system logs in order to detect anomalous patterns of activity such as more than one user session running from the same IP address at the same time, which would be flagged by anti-virus software for investigation.

AI can also identify unusual network traffic that may indicate data exfiltration, and help mitigate the effects of ransomware by detecting changes in file permissions to sensitive files.

In this method, the AI software monitors and analyzes system logs in order to detect anomalous patterns of activity such as more than one user session running from the same IP address at the same time, which would be flagged by anti-virus software for investigation.

AI can also identify unusual network traffic that may indicate data exfiltration, and help mitigate the effects of ransomware by detecting changes in file permissions to sensitive files.

AI can correlate data from multiple sources to detect intrusions or malware

AI can be used to identify patterns in malware or intrusions that might not otherwise be identified.

AI can be used to identify system anomalies that might suggest an intrusion, such as a process on the system not responding.

The machine learning algorithm may detect deviations from expected behavior in networks or security devices (such as IPS) and trigger alerts for human review

The AI-based solution learns over time and eventually will be able to predict intrusions beforehand. For example, an AI system analyzed nearly 60 million log files from the Apache webserver and found over 65,000 previously unknown vulnerabilities of this type.

8. AI will provide a more centralized view of the security posture

The reality is that AI will provide a more centralized view of the security posture. Security operations centers (SOCs) are typically spread across several facilities, and they may not be situated close to each other geographically or in terms of similar functions. By contrast, an artificial intelligence-based system would theoretically bring together all data points from different stakeholders in a single view.

The AI-based system would be able to analyze the full range of data and understand which are most important. It could synthesize key events, learn patterns, identify anomalies and threats early on, generate recommendations for corrective actions, provide visibility across all devices within an organization running security software (even if not using it ), and present a single view of all data across the entire infrastructure.

The beauty of this approach is that it can make sense out of what otherwise would be miscellaneous, disconnected sets of information gathered from different sources. It provides one-stop intelligence for security operations teams to more quickly understand how everything fits together in their environment as well as how to respond.

9. AI can identify abnormal behavior on a network or device that may indicate an intrusion attempt

AI identifies abnormal behavior on a network or device that may indicate an intrusion attempt, by analyzing the device or network’s normal behavior.

It can do this because it is able to look at the big picture of a system and identify changes in behavior.

This process, known as anomaly detection or outlier analysis, can be used for both prevention and response purposes. For example, it can monitor for abnormal activity on a network that may indicate an intrusion attempt like unauthorized access to sensitive data; then take action to stop the intrusion or respond to it.

Artificial Intelligence

Conclusion

Artificial intelligence is the future of our world, and it will impact us more each day. Some say that AI has a negative effect on society because they believe people are getting dumber in an era where technology dominates their lives – but others see its benefits as well.

For cybersecurity purposes, one major benefit for utilizing artificial intelligence would be faster analysis and mitigation of threats; however, concerns lie with whether or not hackers can deploy even smarter cyberattacks using this new form of technology to oppose security teams worldwide