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Jump to navigation. Cheaters use wallhacks to see opponents through walls. In a tactical shooter like VALORANT , this gives them huge advantages when it comes to individual combat encounters as well as strategic decisions for the round as a whole. We really wanted to prevent that sense of doubt which lingers with players, poisoning their experiences long after the match. Without Fog of War : Wallhacks give a player massive gameplay advantages. At the beginning of development, when we were talking about security goals for the project, the two things that came up over and over again were wallhacks and aimbots. If we could pull it off, this seemed like the ideal solution - but we had no idea whether this would be feasible in Unreal Engine. This was a daunting task for me. I was new to the project, which was my first unreleased game project, using an engine I was unfamiliar with and a technique inspired by a completely different type of game. A week of reading documentation and engine source code fueled by the soundtrack to the second best hacking movie of all time yielded a few promising leads. I found that Unreal Engine has a concept of network relevancy that can be used to limit network updates and even despawn non-relevant actors. I also found that the Unreal Engine replication system was eventually consistent, so once information became relevant, the state of enemy players would catch up. At this point, I was growing more confident that this was a feasible solution. Agents, weapons, and abilities are all examples of network actors. A week later I had cooked up a simple prototype. When the actor became relevant again, it would send a message to spawn them if necessary and then make them visible and enable collision. There were a ton of bugs but the fundamental idea was sound. However, there were issues with performance, and the line-of-sight checks had some severe limitations. But I knew it could be done. I had to tie in the audio system, add tools for designers, and handle system notifications for gameplay events. These were relatively straightforward fixes, and once they were done, I could focus on the more complex issues of server visibility issues and performance problems. This meant repeatedly returning to fix pieces of an airplane while it was already in the air. Early on in testing it became clear that there were problems with the visibility check. During playtests, actors would pop in or remain invisible indefinitely. I went through several iterations before finally landing on a solution that worked consistently. My second attempt involved expanding the bounding boxes in an attempt to capture future actions, but the line-of-sight checks were still fundamentally too pessimistic biasing towards negative results to avoid false positives. The problem I tackled first was the pessimistic line-of-sight checks. It would cause completely inaccurate results in situations where a door, ledge, or corner obscured the midpoint of the actor - and a massive pop in effect as an enemy peeked a corner. My second iteration was significantly more successful. This prevented pop-in effects by sending the information to a player just before the enemy came around the corner. The server effectively looked into the future to get the client the information it needed just in time. Extending bounding boxes to account for movement and latency really helps! At this point, the system was workable but still had bugs and performance issues. Occlusion culling is a technique that game engines use to remove unnecessary objects from a scene before sending it to the graphics card to render. Reducing the number of objects sent to the GPU makes rendering a scene much faster. Both need to be really fast to make it worth doing occlusion culling in the first place. I decided to take our client occlusion culling system and run it on the game server as an alternative to doing ten raycasts. A PVS system pre-computes which parts of a scene our map can see which other parts. We run a process ahead of time which divides the scene into cells - imagine voxels in Minecraft. It then calculates line-of-sight between each cell and every other cell in the scene, and then stores all that data in a lookup table, which is like a giant multiplication table. I took this lookup table and started including it with the server assets and the client package. This is much faster than raycasting, and is also optimistic. This helped us avoid pop-in bugs and resulted in a massive performance gain. This precomputed visibility table gives us fast and generous line-of-sight tests. Before implementing the occlusion culling solution, our server performance was awful, Frame times were doubled, which basically sent us from tick back to 64 tick. In a 10 player game, we were calculating relevancy more than times every frame, and each one of those included the relatively costly original 10 raycast line-of-sight checks. The new PVS-based checks dramatically improved performance and I gained even more through a few other optimizations. These changes decreased the amount of calculations the system performed significantly making it even faster. Overall the system even improves performance because of the reduction in network messages the server sends to players hidden by Fog of War. Solving server visibility and performance issues was a huge step in the right direction - but we still had bug smashing to do! These required small tweaks and fixes as we caught them. But other, larger bugs could severely impact the game - like an enemy not being shown in the correct animation pose which breaks hit-registration , or characters being invisible for a moment after walking around a corner. An example of this bug class was that when an enemy hidden by Fog of War started defusing the Spike, a player who then observed them would see them in the default character pose rather than Spike-defusing pose. Left: What the player saw. Right: What was actually happening. This category of bugs was common and happened when the game system handled its own network messaging and state management. Instead of individually fixing each and every instance of these bugs by adding post-Fog of War reconciliation logic, we decided to create a standard solution that any system could use. The game engineers responsible for Agents and game systems built a system called Effect Containers. This neatly encapsulated client gameplay effects and provided a standard mechanism for restarting and fast-forwarding effects after an actor emerges from Fog of War. This kind of systemic approach to fixing bugs was only possible for two reasons. First, because of how early in development the Fog of War system was created. One concern I had with Fog of War was how to track if it was working as intended. During the development of Fog of War, I built a couple of different wallhack tools to test against. They do a very good job of showing Fog of War in action, but this tool is better for spot checking rather than catching bugs so I built out tests and dashboards to make sure we were consistently capturing how things were working. To build more confidence in the system, I expanded on my wallhacks by creating some automated test cases that have bots enter and exit Fog of War. This helps us make sure that the Fog of War system is still functioning after every new build. To catch those subtle problems and to get snapshot views of overall system performance, I created dashboards to track the health and effectiveness in real matches. I built telemetry into the game server that measures the results of every Fog of War query. Then I used these results to build dashboards that show the amount of time enemies are relevant and what percentage of Fog of War queries have each result e. The dashboard then breaks that down further by map and by Agent so I can see if there are any problems for those particular content types. With this telemetry I have the ability to set alert thresholds to make sure I notice when a new piece of content or a system change impacts Fog of War. It showed up in this telemetry as a significantly higher relevancy time for Jett players. This type of dashboard compares Agent Fog of War relevancy stats to help us find bugs. The VALORANT team started working on security features extremely early in the production cycle, which enabled us to take security requirements into account when building key game systems. This created an atmosphere where all developers were invested and involved in the security of the game. I believe this has seriously improved the security of the game as a whole. All this work resulted in a system that drastically reduces the time enemy positions are available to players, and therefore reduces the effectiveness of wallhacks. We can expand the Fog of War system and tighten tolerances to improve security. After Fog of War : The impact of wallhacks is greatly reduced. Thanks for reading! If you have any questions or comments, feel free to post them in the comments section below. It was time to dive into the guts of Unreal Engine. It worked! Server Visibility Issues Early on in testing it became clear that there were problems with the visibility check. Line of Sight Calculations The problem I tackled first was the pessimistic line-of-sight checks. Attempt 2 My second iteration was significantly more successful. Server-Side Occlusion Culling Occlusion culling is a technique that game engines use to remove unnecessary objects from a scene before sending it to the graphics card to render. The problems I was having with Fog of War visibility were similar because: Both systems decide which objects are visible. Performance Before implementing the occlusion culling solution, our server performance was awful, Frame times were doubled, which basically sent us from tick back to 64 tick. Measuring Effectiveness One concern I had with Fog of War was how to track if it was working as intended. Automated Tests To build more confidence in the system, I expanded on my wallhacks by creating some automated test cases that have bots enter and exit Fog of War. Dashboards To catch those subtle problems and to get snapshot views of overall system performance, I created dashboards to track the health and effectiveness in real matches. Posted by Paul Chamberlain. 如何在線電腦免費使用GTA 5
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