Internet users today are very much aware of the harm and risk they are exposed to due to internet use. The pain of being hacked and the theft of vital information like financial details isn’t an unusual story among online users today.
With that, many try to secure their data through approaches like strong password generation, data encryption, and data backup. There is also an increase in the development of sophisticated tools and software like password generators and two-factor authentication techniques to secure user data in the cloud.
However, although new technologies and data protection techniques are leveraged in the modern world, the threat of cyber-attacks and data breaches remains significant worldwide. Apart from putting individual data at risk, millions of organizations globally are major targets for hackers exposing large sums of data to risk.
The latest cyber threat statistics indicate that online users saw at least 52 million data breaches worldwide in the second quarter of 2022. Another study revealed that cybercriminals can penetrate up to 93% of company networks with financial organizations more susceptible. Worse still, while technology is extremely advanced today, the threat of losing data to cyber criminals increases every passing year. So what could be the way forward?
AI in the Cyber Security Landscape
The advent of AI in the cyber security sector offers incredible possibilities for tackling cyber threats. It can also help in attaining SMART Goals, and guiding organizations through the change management process as they go digital. Generally, AI or artificial intelligence just gets smarter every passing year and this offers more insights to data professionals about how to develop robust solutions. The advancement in technology is a major driver for sophisticated and more competent techniques of combating and responding to data breaches and cyber-attacks.
The fact that AI systems can learn over time offers a chance for top-notch and more sophisticated security techniques. More so, AI via machine learning can analyze huge sums of data and offer a real-time response.
In the field of cyber security, AI can help with developing secure applications and enhancing data security. It can also help in the protection, and early detection of threats and also take necessary action against cyber threats. By leveraging the right AI systems, cybersecurity professionals can test AI models for tackling possible threats. They can also train them to automatically respond to threats.
Such possibilities offer hope to online users and organizations whose data is the backbone of their operations, decision-making, and future existence. Besides that, there are many more ways in which AI is altering the cyber security landscape and these include
- AI Speed & Accuracy
We live in an era of digital transformation where more and more companies and organizations are establishing their online presence. However, as their operations grow, there comes a need to handle large sums of data and the need to secure it from cyber attackers. Here, countering cyber threats may become difficult as there is always an increase in vulnerabilities that cybercriminals seek to exploit.
Whereas that remains the fact, AI offers a fascinating reality of dealing with these threats. AI through its subset of machine learning can discover anomalies in behavior and detect a threat before it even happens. Many times, cybercriminals leverage advanced automation to accelerate attack time which overpowers an organization’s defense systems.
However, training AI systems in specific types of cyber attacks can offer them a swift response time that detects behavioral changes and prevent cyber attacks before they occur.
- Proactive Protection Mechanisms
More than any remedial approach, proactive cyber-attack techniques should be prioritized over reactive approaches. Thanks to artificial intelligence, AI systems can be designed to create an accurate and comprehensive roadmap of a network’s user behavior, connections, and possible configurations.
In this way, security solutions are better positioned for risk prediction, which makes them proactive. Generally, artificial intelligence systems can predict how and where data is more susceptible to cyber-attacks and breaches. By the way, their accuracy in the detection of cyber security threats simply gets better with time.
In this way, organizations can learn to patch security gaps to eliminate or counteract cyber threats before they even cause damage to a network.
- Secured Application Development
As technology advances become the norm of the modern era, cyber attackers too are always developing sophisticated techniques of breaching system security protocols. Many organizations deal with a lot of data and yet lack the right approaches and IT expertise to establish a robust security system for their data.
When we bring AI into the picture, the technology can help organizations develop more secure applications by default. Ensure that applications are robust, scalable, and more secure, and can excellently complement other security techniques like multiple-factor authentication. Before deploying a given AI solution, the AI model can also be trained and tested on the right data and how to combat or mitigate threats.
- Malware Detection
The traditional approaches of malware detection are no longer effective as newer forms of malware are ever being developed by cyber attackers. However, they can be used as a foundation for building stronger cybersecurity frameworks.
When configured with AI, the current machine learning (ML) approaches and other technologies like reinforcement learning, and deep learning, can effectively analyze any intrusive software and compare it with the default set to ascertain whether it’s harmful or not.
In addition, advanced deep learning algorithms and complex neural networks are being developed to tackle intricate malware threats. With the help of AI, security solutions can quickly analyze millions of data to recognize deviations and identify threats, for example, suspicious IP addresses, malware, and nefarious activities.
- Behavioural Analysis
AI technology and machine learning algorithms allow systems to study and keep track of an entire organization’s activities. In the case of anomalies or suspicious user activities, the AI system can detect these deviations and subject a user to multiple passwords if the risk is high.
Risk analysis with AI is quicker and doesn’t require manual interventions. Based on the usual activities and user patterns, the algorithms can detect deviations and behaviors that aren’t possible with a usual user. In this way, an organization’s data can be protected from breaches and related threats.
Conclusion
To encapsulate, artificial intelligence is a powerful technology that is currently making the impossible possible. Together with the help of machine learning and deep learning, the technologies offer a fresh breeze for counteracting cyberattacks and above all ensure the proactivity of IT infrastructure and data systems. The best thing is AI enhances its knowledge of identifying and detecting cybersecurity threats with every passing period. This can help organizations to formulate change management and deal with too much data to develop an all-round robust cybersecurity solution for its data in a hybrid cloud.
