Remote attacks are one of the most serious threats to cybersecurity in the field of information technologies. These attacks are carried out without direct physical contact, via the Internet or other network channels. Remote attacks include a wide range of attack methods such as DDoS (Distributed Denial of Service), remote distribution of malware, phishing, SQL injection, remote code execution and man-in-the-middle (MITM). These attacks can lead to infrastructure paralysis, theft of confidential information and economic losses. Among the existing defense systems, firewalls, antivirus software, network traffic analysis systems (IDS/IPS), encryption protocols (TLS, VPN), multi-factor authentication and artificial intelligence-based threat detection systems play an important role. Against the backdrop of the increase in remote attacks, it has become necessary to continuously update cybersecurity strategies. Due to the flexibility and sophistication of attack vectors, traditional defense mechanisms alone are not enough. For this reason, proactive security approaches, i.e. methods for identifying and mitigating risks before an attack, are coming to the fore. Using scanners to automatically detect security vulnerabilities, regularly updating systems (patching) and conducting security tests are important technical measures. In addition, forming a security culture in enterprises and regularly involving staff in training also play a decisive role in reducing risks related to the human factor. Since phishing and social engineering attacks mainly exploit human weaknesses, awarenessraising measures in this area are as important as technical measures. Among the innovative approaches, artificial intelligence (AI) and machine learning (ML)-based systems stand out in particular. These technologies can analyze large volumes of network data and distinguish between normal and abnormal behavior, thus allowing for the detection of attacks at an early stage. For example, SIEM (Security Information and Event Management) and UEBA (User and Entity Behavior Analytics) systems, which identify unusual activity of user accounts based on behavioral analysis, have become an integral part of modern cybersecurity architecture. At the same time, the Zero Trust model is also widely used in modern security strategies. According to this model, no user or device is trusted in advance, and the principle of re-verification of any access is applied. Thus, attacks carried out from the internal network are prevented more effectively. Regulatory legal frameworks and standards adopted at the state and international levels also play an important role in the development of this area. For example, data protection legislation such as GDPR (General Data Protection Regulation of the European Union) obliges organizations to take more serious security measures. Such rules serve to ensure the security of the cyber environment by defining not only technical, but also ethical and legal frameworks.