Binance Research Reported an Upsurge in the Restaking Sector
Restaking has emerged as the new 2024 trend in the crypto industry, according to a new report from Binance Research.
Binance Research has identified significant growth in the restaking sector in 2024, noting that the volume of assets locked in restaking protocols has grown by 700%. This surge has drawn attention to this segment, which has now expanded its boundaries beyond the Ethereum ecosystem. Experts have emphasized the role of protocols in improving the security of other blockchains, as well as the ability to restake tokens beyond their original network.
EigenLayer’s TVL has risen by over 700% through 2024. In our new #Binance report, we explore the restaking market, EigenLayer, restaking on other chains, liquid restaking & LRTs, and more!
— Binance Research (@BinanceResearch) February 27, 2024
Some highlights (1/16) 🧵
Among the industry innovators, the EigenLayer project stands out, offering an Ethereum-based Security-as-a-Service that combines restakers, node operators and active validation services into a three-part marketplace. With a planned mainnet launch in the second half of 2024, EigenLayer has already attracted attention, locking in about $8.9 billion in assets.
The Babylon staking protocol, which is preparing for integration with the Bitcoin blockchain and supports more than 45 networks in the Cosmos ecosystem, and the Picasso Network project, which is developing a restaking layer for Solana, are also noteworthy. The Picasso Network solution is expected to launch in the second quarter of 2024.
Meanwhile, Binance's interest in restaking is supported by Binance Labs' recent investment in the Babylon protocol. This protocol allows Bitcoin holders to utilize their assets on PoS networks, providing economic security and increased liquidity for investors without the need for bridging.
Babylon, using the Cosmos SDK, provides a unique technology for temporarily controlling Bitcoin in PoS blockchains and facilitates cooperation between PoW and PoS consensus algorithms.
