Introduction
With the advancement in technology, cyber-crimes are also increasing and getting complex. Cyber-criminals are launching sophisticated attacks that are putting modern security systems at risk. So, the cybersecurity industry is also evolving to meet the increasing security demands of companies. But, these defensive strategies of security professionals may also fail at some point.
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To up their game and enhance their vulnerability detection mechanisms, companies are choosing Artificial Intelligence (AI). Artificial Intelligence in Cyber Security is aiding companies to safeguard their defense mechanisms. It is also assisting them in analyzing cyber crimes better.
What is the impact of Artificial Intelligence on Cyber Security?
Companies are focusing more on cybersecurity right now like never before. This is because advanced cybersecurity attacks have cost companies millions of dollars in data breaches. It starts with designing a multi-layered security system that will secure the network infrastructure. The first step is to install a firewall that will filter out the network traffic.
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Then, antivirus software is used for cleaning out the malicious files and viruses in the infrastructure. As a part of their disaster recovery plan, regular data backups are executed.
And, this is where artificial intelligence comes in.
AI has impacted security by helping professionals to identify irregularities in the network by analyzing user actions and studying the patterns. Security professionals can now study network data using AI and detect vulnerabilities to prevent harmful attacks. AI will help enhance the traditional security approach by the following ways –
- Advanced AI-powered security tools will be used to monitor and respond to security events
- Modern firewalls will have built-in machine learning technology that will easily detect a usual pattern in the network traffic and remove it if considered malicious
- Using the natural language processing feature in AI, security professionals can detect the origin of a cyber-attack. Natural language processing also helps in analyzing vulnerabilities
- Scanning internet data and using predictive analysis will identify malicious threats beforehand
- Higher security of conditional access and authentication
Another important revelation of Artificial Intelligence in Cyber Security is biometric login systems. These are extremely secure logins that use fingerprints, retina scans, and palm-prints. A password can be used along with this biometric information for securely logging in. This method is used in organizations for employees to log in and even in smartphones.
Read: Future Scope of AI in Various Industries
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Applications in Cybersecurity
Machine learning, a very important subset of artificial intelligence, is also being used these days by corporations to enhance their security systems. Besides helping security experts in detecting malicious attacks, it has the following applications –
Mobile endpoint security
Machine learning is used for mobile endpoint security as smartphones, tablets, and notebooks are all prone to cyber-attacks. A company called Wandera recently launched its machine learning-powered threat detection engine called MI: RIAM. This engine has successfully detected several traces of repackaged SLocker Ransomware that targets mobile endpoints.
No zero-day vulnerabilities
A zero-day vulnerability is a threat that is completely new to the security professional and he or she does not yet have a solution or patch to fix it. Zero-day means that professionals have zero days to fix the issue, and they may have already been exploited by an attacker. These threats are sometimes found in unsecured IoT devices.
Machine learning algorithms can detect zero-day threats by analyzing the anomalies in network traffic. Vulnerabilities are removed and patch exploits are prevented using machine learning.
Improving human analysis
Machine learning helps in enhancing human analysis in cybersecurity activities such as vulnerability assessment, threat detection, network analysis, and endpoint security. ML algorithms can filter out suspicious data in the network and pass it on to a human security analyst. As a result, the alert detection rates can increase significantly.
Automating security tasks
Repetitive and boring security tasks can be reduced by machine learning. This helps professionals to focus on important jobs. Tasks like checking network traffic, interrupting threats such as ransomware, removing viruses, and analyzing network logs can be automated by machine learning.
Human security resources can also be allocated efficiently with the help of machine learning.
Companies using Artificial Intelligence in Cyber Security
AI-powered systems are used by the following companies to strengthen their security infrastructure –
They are using the Deep Learning AI system on their Cloud Video Intelligence platform. Videos stored on their cloud server are analyzed by AI algorithms based on their content and context. If an anomaly is found that might be a threat, the AI algorithms send an alert.
Gmail uses machine learning to filter out spams from your mail to provide a hassle-free environment. More than 100 million spams are blocked every day.
IBM
IBM Watson uses machine learning in its cognitive training to detect threats and create cybersecurity solutions. AI also reduces time-consuming threat research tasks and assists in determining security risks.
Also read: AI Exciting Real World Applications
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Conclusion
The use of Artificial Intelligence in Cyber Security will soon be the standard practice for developing and handling security systems. As many harmful threats can be detected before any damage, security experts will have more response time to fight against these malicious attacks.
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