Technology’s evolution and rise have brought many benefits to individuals and businesses. It has, however, had one major drawback: the increase in cybercrime and cyber attacks, as well as malware infection, facilitated by an ever-growing attack surface.
This increased network perimeter is a problem for business operations at high levels. They require constant monitoring of thousands upon thousands of security events and codes to avoid breaches. This task is too difficult for humans and needs a better solution.
Predictive AI (or AI) has also been created thanks to technological advances. This AI is making huge strides toward eliminating cybersecurity issues.
This article will give you a quick overview of predictive AI and how it can be used to secure your data.
What’s Artificial Intelligence?
Artificial intelligence is a broad term that refers to technologies that simulate human intelligence through computer systems and acquired data.
AI has advanced human intelligence and can create new knowledge using mechanisms that enable it to acquire, store, process, and apply existing knowledge.
The following section provides more context on the most important information about AI models. AI models can include neural networks, expert systems, and deep learning.
- Neural networks allow AI software to learn from data gathered and observed.
- Machine Learning Models use statistical processes to enable the software to learn instead of being programmed for a task.
- Expert systems provide software problem-solving capabilities in certain areas.
- Deep Learning models enable software to learn from data and not preprogrammed algorithms.
Three explicitly designed evolutions of artificial intelligence are called waves for cybersecurity.
The first wave was considered the most primitive. This was because it was when programmers wrote the code for the still-supervised AI codes to follow.
This wave’s AI collected data and created historical baselines to detect anomalies in different data. It is significantly slower than its current counterparts, as it takes months for baselines to be created.
It also had many errors because it only measured against one failsafe, the baselines that it created.
Predictions were possible with the second wave in the AI evolution. This wave comprises both unsupervised and supervised machines capable of creating their own rules using statistical methods. This allows them to make predictions.
The second-wave AI can detect anomalies even if accessing the network or making network changes is impossible.
The third wave of AI evolution, Predictive AI Intelligence, generates the most advanced cybersecurity solutions.
These AI self-supervised systems can use their analysis in a variety of situations. They can learn from new observations and create new conclusions through their self-learning abilities.
Predictive AI in Cybersecurity
Let’s now learn more about predictive artificial intelligence and its use in cybersecurity.
Automating Threat Monitoring
You will need to analyze many unstructured and structured data to monitor network threats effectively.
It will take you a while to do this on your own. Even if you hire many people to verify, you won’t know if you’ve overlooked essential pieces of information. You can automate the threat monitoring process with predictive AI.
This eliminates human error and makes it more cost-effective than hiring employees to check your data manually.
Predictive AI also allows you to analyze your credit risk and model your company to minimize the possibility of cyber-attacks or ransomware attacks.
Improved Risk Management & Incident Response Decision Making
Predictive AI intelligence scans large amounts of data and makes rational decisions when faced with an imminent threat.
This enhanced predictive analysis tool allows you to make more data-anchored decisions and gain valuable cybersecurity insights.
These advanced cybersecurity policies can be integrated into third-party services to prevent data breaches.
You can also use AI to manage contracts for consistent and current techniques that use better tools and more secure methods.
Predicting and Sensing Cyber Risks
Predictive AI is an excellent choice for cybersecurity because it can detect and predict risks faster than humans and uses less restrictive rules-based algorithms.
This highly efficient process, based on predictive AI’s self-learning capabilities, allows companies to identify new anomalies and assess their risks. It also creates future risk predictions.
Your predictive AI’s risk-sensing capabilities can detect problems with customer service management systems that have been integrated into your social media accounts.
It can also provide predictions such as how frequently anomalies like these will occur if there is no solution.
Preventing Cyber Crimes
According to IBM’s 2021 report, an average data breach could cost a company $4.24 million. These breaches can be caused by compromised credentials, email compromise (BEC), social engineering, and malicious insiders.
Predictive AI can provide 24/7 protection without the need for human intervention.
Third-wave AI’s predictive capabilities can alert you to zero-day vulnerabilities in your company’s software before a breach. Zero-day vulnerabilities are software flaws that manufacturers don’t know about.
Hackers can use these weaknesses to launch zero-day attacks. They can use zero-day exploits to gain access to your system to compromise it.
Cyber Security Operations Boosted with Predictive AI
Technology advancements have created unprecedented security problems and provided the tools to address them.
Strong, predictive AI can be used to protect your company’s critical infrastructure from cyber-attacks.
An AI technology can offer you peace of mind that no manual security process cannot, considering the rapidly-changing cybersecurity needs of modern businesses.
Predictive artificial intelligence can help you identify problems before they cause damage to your reputation and operations.
It can help you to plan better and create a more robust ransomware response policy or incident resolution plan for dealing with anomalies.
It would be best if you still considered a multilayered security strategy that does not discount human capabilities. When defeating advanced criminals, the best way forward is to bring together cyber experts and combine their abilities with intelligent machines.
Human supervision and intervention are essential for businesses. Predictive analysis and AI can help boost what humans can accomplish and create a more robust cyber infrastructure worldwide.
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