Search Results for "genetic algorithms"
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Showing 7 open source projects for "genetic algorithms"
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Bright Data - All in One Platform for Proxies and Web ScrapingBright Data offers the highest quality proxies with automated session management, IP rotation, and advanced web unlocking technology. Enjoy reliable, fast performance with easy integration, a user-friendly dashboard, and enterprise-grade scaling. Powered by ethically-sourced residential IPs for seamless web scraping.
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Alkindus is an automated solver for short monoalphabetic substitution ciphers without word divisions.
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GeeVir - software product specifically designed to search for computer viruses using the GA (genetic algorithms)
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Raiden block cipher: An extremely lightweight and fast block cipher, developed using genetic programming, with the intention to be an alternative to TEA. This cipher is as fast as TEA, and without many of its known weaknesses.
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OW.NET -- 1-Wire API port from Java (and J#) to C#. Use the Dallas 1-Wire and iButton chips with standard C# using a serial adapter (also CF.net) or the TMEX drivers on the Windows platform. No J# distribution installation required.
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NeoLoad is a very comprehensive tool if you are looking for a performance test tool for web applications and other applicationsYour applications are all built differently, but they all need to perform. NeoLoad simplifies and scales performance testing for everything, from APIs and microservices, to end-to-end application testing through innovative protocol and browser-based capabilities.
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A GLib/GTK+ classical encryption analysis and reversal tool that brings together multiple techniques into a single program to aide in decryption.
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It moves by itself inside networks like virus infection & plagues, it is being written to solve computer virus problem drastically and responsibly. It is legal, free and open for public domain to improve W3 ICT Security.
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CSI PC2 is a project for verification and identification of biometrical information that scales up to tens of millions of entries. Several algorithms are implemented. It includes testbeds, benchmarks and genetic algorithms for optimization.
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