212-82 Exam Dumps : Certified Cybersecurity Technician (CCT)

In the context of developing a cryptographic protocol resilient against quantum computing attacks, SHA-3 is the most appropriate choice. Here’s why:

Quantum Computing Threats: Quantum computers can potentially break current cryptographic methods like RSA and ECC due to Shor's algorithm. Traditional hash functions like SHA-256 might not offer sufficient security in a post-quantum world.

SHA-3 Overview: SHA-3, part of the Secure Hash Algorithm family, was designed with quantum resistance in mind. It was selected through an open competition by NIST, ensuring it incorporates advanced cryptographic techniques.

Resilience: SHA-3’s design is fundamentally different from SHA-2, providing enhanced security properties, including resistance to various attack vectors that might be feasible with quantum computing advancements.

References:

NIST SHA-3 Standard:NIST FIPS PUB 202

Research on quantum-resistant cryptography:IEEE Xplore

To effectively trace unauthorized activities within TechTonic's Windows-based server farm, the best strategy is:

Centralized Logging:

Aggregation: Collect all system logs in a centralized logging server. This ensures that all log data is stored in one place, making it easier to manage and analyze.

Correlation: Correlate logs from different sources to identify patterns and anomalies that might indicate unauthorized activities.

Pattern-Detection Algorithms:

Automated Analysis: Use algorithms to automatically detect patterns that are indicative of security breaches. This can include machine learning models trained to recognize signs of intrusion.

Real-Time Alerts: Set up real-time alerts for suspicious activities identified by the pattern-detection algorithms, enabling swift responses to potential threats.

References:

Best practices for Windows logging and monitoring:Microsoft Docs

Centralized logging solutions and their benefits: Splunk Documentation

Anomaly-Based Intrusion Detection Systems (IDS):

Anomaly-based IDS monitor network traffic and system activities for unusual patterns that may indicate malicious behavior. They are effective in identifying unknown threats by detecting deviations from the established baseline of normal activities.