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How Artificial Intelligence Is Transforming Cyber Security Operations? Raghib Khan Comments

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As scams and fraud cases are growing every year, cyber security is becoming an indispensable part of the internet. We are witnessing countless numbers of cybercrime everywhere. In The United States of America, 90,000 people fall victim to cyber crimes every month. This alarming situation indicates that the conventional ways of operating cyber security are outdated. Artificial intelligence now gives us more reliable ways of dealing with online disasters. 

In a recent conversation with Raghib Khan, a tech entrepreneur and founder of RNF Technologies. we discussed that AI-based technologies are considered more accurate and helpful than manual cyber security methods. Regarding real-time fraud detection, we must integrate AI with cybersecurity. One of the significant concerns regarding machine intelligence is that it may be possible for cybercriminals to use artificial intelligence as a weapon to empower them to progress their fraudulent activities. That’s why the cyber security industry is extra cautious and doing their bit to make the most out of artificial intelligence in their favor. 

Let’s see how artificial intelligence can transform the cyber security landscape:- 

User Behavioral And Pattern Analysis

We can detect behavioral patterns that don’t match everyday activities using machine learning and AI. After creating a benchmark for standard behavioral patterns, reading algorithms like location, availability, device models, user ID, and scrolling patterns, we can filter suspicious behaviors from the common ones, and it will be easier not only to catch the cyber criminal but to prevent any cyber attack before it happens. 

Real-Time Fraud Detection 

Traditional cyber security service operations sometimes result in delayed response and many false positives. AI and machine learning boost real-time fraud detection while drastically lowering the possibility of wrong identifications. AI-powered fraud detection may also do root-cause analysis and track the origin of fraudulent transactions back to their sources, such as credit cards, debit cards, or ATMs.

Malware Detection

Malware is malicious software such as viruses, trojans, ransomware, and spyware that is often transmitted by email or messages as a link or a file and is meant to inflict substantial harm to your organization’s data and systems, sometimes becomes irreversible. Worm can be the most tricky form of cyber attacks, and it’s better to avoid it as much as possible Machine learning algorithms, with their deep web neural networks, can identify and analyze complex malware programs and even block them from recurring. 

Identity And Password Management

There are thousands of cases where cybercriminals hack passwords and gain full access to the system. People set weak passwords or use the same password on every platform, which gives cybercriminals an advantage. Biometrics technology plays a crucial role here by alarming us whenever we are about to choose a weak password. 

Sometimes fraudsters can use tricky methods to bypass biometrics authentication. So AI tools and algorithms develop a representation of the user’s face and discover basic patterns and everyday actions to prohibit fraudulent access. This is a far more effective and safe way to protect your accounts since the algorithm will function even when users are in dimly lit regions or are using accessories like hats.

According to RNF Technologies’s Raghib Khan, this is just the beginning of the future of AI-based fraud detection. A much brighter future awaits us, and we can have online platforms without cyber attacks. As AI keeps evolving, we expect more advancement in the cyber security landscape.  

 

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