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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.

Updated Sep 14, 2021, 9:46 a.m. Published Aug 21, 2020, 2:28 p.m.
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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.

  • 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.

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Bitcoin hash rate is tumbling as Iran war lifts energy prices

Bitcoin Mining (Hashage)

A falling hash rate and the resultant pressure on miners could signal another potential capitulation phase, which could push prices down further

Yang perlu diketahui:

  • The Bitcoin network hash rate has declined roughly 8% in the past week to 920 EH/s, likely tied to energy market disruptions in the Middle East.
  • Bitcoin mining difficulty is set to fall as much as 10%, marking one of the largest downward adjustments over the past five years.
  • A sharp drop in hash rate often coincides with periods of miner stress and downside pressure on bitcoin prices.