Hacking contests that focus on simulated intelligence in modern network protection typically fall under the category of Capture The Flag (CTF) competitions. These events are designed to challenge participants in areas of cybersecurity, where they use their skills in ethical hacking, programming, and AI to identify and exploit vulnerabilities in a controlled environment. Some of the types of hacking contests include:

1. Attack-Defense CTFs: Participants are divided into teams, each defending their own system while trying to attack the other teams. AI-based tactics are used to automate both offensive and defensive maneuvers.
2. Jeopardy-style CTFs: This type includes various challenges in categories like cryptography, reverse engineering, web security, binary exploitation, and forensics. Participants may use AI algorithms to solve problems faster, like automating code analysis or pattern recognition.
3. Machine Learning (ML) and AI-focused Contests: These contests specifically highlight the application of AI and ML in cybersecurity. Challenges might involve using AI to detect anomalies in network traffic, predict potential attacks, or create intelligent bots that can mimic human hackers.
4. Red Team vs. Blue Team Competitions: In these scenarios, the Red Team (attackers) and Blue Team (defenders) use AI-driven techniques to simulate real-world cyberattacks. The focus is on developing AI strategies that can detect and counteract advanced threats.
5. Bug Bounty Contests: Participants use AI-powered tools to find vulnerabilities in software or systems. AI can help automate the discovery of bugs, making the process faster and more efficient.
6. AI-Driven Autonomous Hacking Competitions: These are specialized contests where autonomous systems, often developed using AI, compete against each other without direct human control. An example is the DARPA Cyber Grand Challenge, where AI systems defend against and launch cyberattacks autonomously.

These hacking contests aim to leverage AI’s capabilities to detect, respond to, and predict cyber threats in modern networks, enhancing cybersecurity defenses in real-world scenarios. They foster innovation and help develop skills in both offensive and defensive cybersecurity strategies using AI and machine learning.