Notes

In the last few year the threat of malware to network users has increased. The internet has become a crucial part of people’s personal and professional activities worldwide. Attackers use various strategies to target individuals and organizations, aiming to steal sensitive data and harm computer systems. Security measures today focus on scanning systems. There are different techniques like dynamic, static, statistical, and content analysis used in these scanning methods. Unfortunately – hackers know about these protections, so they create new malware that antivirus can not easily detect. Malware is basically software that spies on what a computer is doing, gets access to it, or collects important information. It is different from regular software because it is made with the intention of causing harm, not by accident. Security measures today focus on scanning systems. Nowadays, malware is big threat to the internet users. As the internet gets more advanced and popular, dealing with malware is getting trickier. People classify malware into different types to understand and fight against it.
Chapter 5 and 6 talks about the ways how to keep information safe. There are different ways which helps how to maintain and keep information private, intact, and available. I chosed this article, because it is relevant to the chapter 6. According to article there are explained different malwares and best ways how to detect it. One of them is (ML) Machine learning methods. Machine learning methods can quickly solve complex problems. ML plays a crucial role in cybersecurity. Offers solutions for such as phishing detection, network intrusion detection, malware detection, anomaly detection. While ML contributes to protecting various systems, ML classifiers can still be vulnerable to malicious attacks. There have been efforts to enhance the accuracy of ML predictions and defend against a variety of attacks.