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Los Alamos Scientists Develop AI to Fight Cryptojacking
Their neural network works faster and more reliably than non-AI systems, researchers said.

Scientists at Los Alamos National Laboratory, the U.S. government-funded research outpost that once hosted the atomic bomb Manhattan Project, say they have designed an artificial intelligence for detecting would-be cryptojackers.
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- In a press release, the scientists said their new AI sniffs out malicious code injections that can turn vulnerable supercomputers into zombie cryptocurrency mining operations, a serious IT issue that strikes governments and corporations globally.
- Called SiCaGCN, the neural network works by checking if a given program has the right backend structure to run on the computer system. Those that do, pass through. Those that don't, get flagged for removal.
- “This type of software watchdog will soon be crucial to prevent cryptocurrency miners from hacking into high-performance computing facilities and stealing precious computing resources,” project researcher Gopinath Chennupati said in the statement.
- SiCaGCN detected cryptojacking code faster and more reliably than non-AI solutions, according to the statement. The scientists originally proposed SiCaGCN in the journal IEEE Access last month.
Danny Nelson
Danny is CoinDesk's managing editor for Data & Tokens. He formerly ran investigations for the Tufts Daily. At CoinDesk, his beats include (but are not limited to): federal policy, regulation, securities law, exchanges, the Solana ecosystem, smart money doing dumb things, dumb money doing smart things and tungsten cubes. He owns BTC, ETH and SOL tokens, as well as the LinksDAO NFT.
