Importance of using artificial intelligence for advanced analysis, detection, and response to threats
Primarily to implement a cyber defense against a potential cyberattack, it is important to incorporate a solution that includes preventive monitoring, user education, and adequate patching and incident management. However, options that can go beyond this basic configuration have been developed. One of the best is implementing Artificial Intelligence (AI) in cybersecurity. Artificial intelligence and machine learning are constantly improving cybersecurity capabilities to the point where it could be argued that the next generation of cyber defense is heavily based on robotics. Some cybersecurity vendors offer this technology that allows machines to see, detect, and respond to cyber threats. You can ensure that users are protected by using the latest advances in artificial intelligence and machine learning.
Artificial Intelligence in cybersecurity
Artificial intelligence consists of a system that has been taught to perform specific tasks without being explicitly programmed, which allows cybersecurity solutions to analyze and learn data with greater efficiency and precision. Therefore, it makes it the new priority of cybersecurity in IT departments in companies. Artificial Intelligence is constantly evolving, and its algorithms allow automatic learning, known as machine learning, which helps the system learn patterns and adapt to simplify the response to incident risks. Cybersecurity professionals are generally extremely busy, handle excessive data, do not have enough time, and therefore have little availability of skills, so Artificial Intelligence can have a great impact on IT managers by allowing:
• Detect threats accurately
• Automate the response
• Streamline attack investigation
In this sense, Artificial Intelligence generates significant benefits since the human resource in cybersecurity cannot meet the high demand. In this way, the efforts of administrators can be optimized. Artificial Intelligence systems collaborate by categorizing attacks according to the level of cyber threat; Those in charge of cybersecurity, for their part, assign the priority with which each one must be addressed, starting with the most dangerous for the state of the company’s information. Malware-type cyberattacks and others that may arise are also evolving, making cyber threats faster and more sophisticated. This is why Machine Learning becomes essential to be at the same level regarding preparation.
Which focuses on applying algorithms in relation to data. In the relationship between Artificial Intelligence and cybersecurity, two predominant schemes are presented: those defined by analysts and those defined by machines. Cybersecurity analysts create protocols based on their experience. However, they can encounter problems when encountering a new or unknown threat. On the other hand, machines apply their security protocols according to the information acquired by Machine Learning and Deep Learning. Behavior patterns in networks directly influence the prediction of future movements and attacks and the operating systems used, servers, firewalls, user actions, and response tactics. Nonetheless, they can suffer from “false positives,” reinforcing the idea that both schemes should complement each other.
Powered by data to help businesses thrive, she is at the forefront of endpoint defense efforts. As cybersecurity becomes a mainstream global issue, look for new ways to identify, monitor, and contain attacks. The cybersecurity provided by Artificial Intelligence is characterized by its autonomy, thanks to the engine that automates its daily security management and operations from start to finish.
Data Loss Prevention uses artificial intelligence machine learning techniques to rapidly scan and qualify data in motion, such as emails, text messages, documents, and associated attachments. This allows you to configure strict controls and restrictions on data transfers to prevent the loss or hijacking of these.
Endpoint Protection turns the latest advances in Artificial Intelligence and Machine Learning into business benefits, delivering the most advanced machine learning available in the industry through advanced engineering and assembly. The security administrator achieves a more advanced level of prevention through policy recommendations and automation that combines administrator and user behavior intelligence, indicators of compromise, and historical anomalies to identify cyber threats. Plus, it continually learns about your management trends to match priorities, recommendations, and responses to your network needs and your organization’s risk tolerance.
Without a doubt, the performance of Artificial Intelligence relies on a robust data source. These models analyze one of the world’s largest collections of non-governmental, multifactorial telemetry to identify potential cyberthreats and unusual behavior patterns. Artificial Intelligence technology processes more than 2 petabytes of data every day, generated by billions of files and messages, and trillions of network connections. Endpoint Protection tracks cyberthreat and cyberattack data across 175 million endpoints and monitors 57 million cyberattack sensors in real-time, minute-by-minute. As a result, you can carry out daily security operations and automate decision-making and defense execution, eliminating time-consuming processes and expanding your to-do list. In this regard, your business network’s cybersecurity is fortified through a solution that employs the most relevant technology in the industry: Artificial Intelligence.
Artificial Intelligence as a branch of computer science
Artificial Intelligence is a branch of computer science that tries to create machines capable of performing tasks that usually require human intelligence. This field aims to develop systems that can reason, learn, make decisions, and even assimilate the world around them. Artificial Intelligence can be divided into two categories: restrictive and general AI.
The restrictive AI has been designed to perform specific speech recognition or image classification tasks. General Artificial Intelligence can perform the same intellectual functions as a human. Machine learning is a branch of Artificial Intelligence that allows computers to learn, from data, without explicit programming. This is achieved by using algorithms that can identify patterns in the data and make predictions based on those patterns. There are three types of machine learning: supervised, unsupervised, and reinforcement learning. In supervised learning, algorithms are trained using labeled data, and the goal is to make predictions about future data. In unsupervised learning, algorithms are trained using unlabeled data, and the goal is to identify patterns in the data. In reinforcement learning, algorithms are trained through trial and error to maximize the benefits.
As we previously implied, Deep Learning is a type of machine learning that uses neural networks with multiple hidden layers to simulate complex patterns and relationships between data. It is considered a subcategory of Artificial Intelligence and has been used to obtain auspicious results in fields such as speech recognition, computer vision, and natural language processing.
Artificial Intelligence can detect cyber threats by analyzing vast data and identifying potentially dangerous patterns. This allows companies to respond faster and more effectively to threats.
AI in cybersecurity leverages advanced technology to swiftly analyze relationships between threats like malicious files, suspicious IP addresses, or insider activities. By automating time-consuming tasks, AI assists information security teams in mitigating breach risks through real-time monitoring and rapid response.
AI can detect various types of cyberattacks, including phishing, malware, ransomware, and data theft.
AI learns and adapts to new threats faster than humans, allowing for a faster response to cyberattacks.
AI can defend against internal threats by monitoring user behavior and identifying unusual usage patterns, such as unauthorized file access.
Hackers can use AI to circumvent security systems by developing AI-driven malware that adapts to security defenses and evades detection.
Although AI currently necessitates human supervision and real-time decision-making for adequate cyber attack responses, future advancements may lead to more autonomous cybersecurity solutions.
César Daniel Barreto