We currently live in a digital age that is witnessing more and more people using all sorts of technologies. From applications to software programs the prevalence of technology is evolving more dramatically than ever before. From being used in homes, organizations, and public services, human dependence on technology will never phase out.

Factors like technological innovations, the desire for better standards of living, and access to the internet are major drivers of technology adoption today. The latest statistics indicate that 40% of the world’s population access the internet today, and over 5 billion people globally use mobile devices. To substantiate, as per DataReportal, 4.70 billion people use social media worldwide, which is 59% of the world’s population.

Now you can imagine the amount of data entered via technological touchpoints on a daily basis worldwide! However, as much as technology has made life easy for humans both in homes and businesses, the drawback that comes with it is currently a major concern. The cybersecurity landscape has become one of the most susceptible fields today. Many people, businesses, and organizations experience data breaches which at times leads to the loss of millions annually.

The Cybercrime Magazine previously indicated that cybercrime activities will cost the world $10.5 trillion annually by 2025. Many technology companies and corporate business accounts are targeted every single day. Nevertheless, many initiatives are taken to lessen data breach incidents and Statista shows a drop in data breaches between 2020’s first quarter and 2022’s second quarter.

Commonly, data leaks, cyber frauds, and attacks are due to weak passwords, misconfigured software settings, and software vulnerabilities among others. These scenarios make people’s and organizational information more accessible to cybercriminals.
Over the years there are different developments in the cybersecurity field aimed at enhancing data and security. However, these approaches haven’t largely managed to counteract cyber attackers’ tactics. So, can AI offer advanced security to online users’ data, and what is its impact so far? 

Incredible Ways in Which AI is Transforming the Cybersecurity Field 

AI in the field of cybersecurity is promising and can highly help combat cyber attacks. AI (artificial intelligence) is capable of collecting, processing, and analyzing large amounts of data, allowing cybersecurity agencies to proactively tackle online threats. The innovations in AI and machine learning are allowing cyber security agencies to tether systems with capabilities that decipher cyber attackers’ tactics before they encroach on private data. More vividly, this is how AI is facilitating the cause;  

1. User Behavioural Analysis 

The advent of AI and machine learning is revolutionizing the field of data analytics. Artificial intelligence and machine learning using algorithms can master user patterns and activities which become the benchmark for diverging activities on a network. Normally, business or organizational networks are wired to perform in a specific way. Also, regularly used IDs, geographical locations, and activities are mastered by computers. 

Artificial intelligence can help IT departments detect user behavioral patterns that are diverging from the usual or expected ones. AI is able to help cybersecurity teams understand the average and far-unlike user behaviors. This can help cybersecurity agencies via computer systems take appropriate action to prevent cyber attacks and threats hence succeeding in their SMART Goals.      

2. Proactive Cyber Threat Detection 

AI through machine learning can analyze potential threats such as suspicious IP addresses and files. Additionally, AI technologies like machine learning become smarter over time which helps them recognize patterns on a network. Unlike humans who can miss out on certain cyberattacks, AI can detect anomalies before they damage a network.

It also facilitates real-time monitoring of data as it comes, signaling potential threats before they cause data leakage. AI-powered cybersecurity tools generally provide a safe network ecosystem or neutralize malicious activities before they can cause damage or data breach. 

3. Vulnerability Management 

Organizations manage large amounts of data and a minor mistake can increase the vulnerability of the entire company’s data. It can lead to leakage of financial information that can cause significant losses to a company. Modern cybersecurity agencies and teams leverage a vulnerability management program or software to secure a company’s network. 

These programs detect and address vulnerabilities as soon as possible and also patch up weak points in computer systems that can expose company data to unauthorized parties. AI can help assess computer systems faster and more efficiently than cybersecurity teams. Needless to say, for businesses relying on data, vulnerability management is a key aspect of business objectives.      

4. Fraud Detection

Individuals and organizations take different measures to prevent data breaches. These commonly include utilizing stronger passwords, password generators, and two-factor authentication. However, these approaches may not proactively detect anomalies.   

Modern AI capabilities can detect deviations from usual human behaviors or online activities that usual human beings can’t do.  They can also scan huge data or transactions in context with user patterns to identify fraudulent possibilities. This is more common in eCommerce where online platforms accept visa cards or allow the use of other payment gateways. 

Today eCommerce companies are using AI to prevent fraudulent transactions that bring about poor customer experiences.  

5. Malware Detection

There are different types of malware such as viruses, spyware, and trojan among others. These are designed to damage or destroy computer systems. For generations, malware tools have been used to detect and remove malware. The ever-evolving online hackers’ tactics are no longer compatible with traditional malware detection approaches. 

AI-powered malware techniques can act against intrusive malware by comparing several aspects of data to identify abnormalities. They are designed to model and master good behavior patterns and identify diverging ones.

Bottom Line

Technological innovations are impacting every sphere of life and human dependence on technology is expected to increase in the future. When it comes to the cybersecurity field, AI, machine learning, and deep learning are real game changers. These technologies allow computer systems to analyze large sums of data and draw patterns that help IT teams prevent, tackle, and act proactively against cyber criminals.

These developments help confine malware and spyware into IT sections without crossing over to the entire organizational systems or causing massive damage to computer systems. By leveraging AI-powered cybersecurity tools, online users, businesses, and companies can better protect their data from leakage and unauthorized access. They are also futuristic cybersecurity approaches that help stay ahead of the hackers’ game.

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