Privacy - Preserving Technique in cybersecurity: Balancing Data Protection and User Rights

Increasing technological complexity of cyber threats creates a major challenge between securing data privacy and maintaining potent cybersecurity practices. The paper examines privacy-protecting security methods in cybersecurity by detailing organizational approaches to defend private information throughout the cyber threat detection and mitigation process. Organizations need to establish the appropriate levels of data security because implementations that limit privacy too much threaten their security capabilities but weak protection measures create vulnerabilities to data breaches. The research implements Cybersecurity: Suspicious Web Threat Interactions data to examine actual cyber threats which comprise phishing attacks and malware and unauthorized access attempts. The effectiveness of data protection approaches including encryption and differential privacy together with homomorphic encryption and federated learning and anonymization solutions gets tested for their ability to secure confidential information throughout cybersecurity operations. The research investigates threat detection accuracy together with computational efficiency and GDPR and CCPA compliance effects when using these techniques. Results demonstrate that security frameworks gain significant improvements from privacy-preserving systems because these systems decrease breach threats and meet all regulatory compliance requirements. The main limiting factors for these privacy-preserving methods consist of excessive computational requirements as well as adversarial threat vectors and the detection versus protection trade-offs that need improvement. This paper presents strategic guidance about privacy-aware cybersecurity models which optimize security capabilities together with data protected information. This research investigates cybersecurity and privacy-preserving methods to assist the development of ethical systems meeting regulatory standards which protect users from advancing cyber threats through privacy-protected mechanisms.