Breaking Down of 51% Double Spend Attack (DSA) in Blockchain Technology
S. Brilly Sangeetha1, S. J. Jereesha Mary2, S. Sebastin Antony Joe3
1S. Brilly Sangeetha, Associate Professor, Department of Computer Science and Engineering, IES College of Engineering, Kerala, India.
2S. J. Jereesha Mary, Faculty in Department of IT, A Musanna College of Technology, Oman.
3S. Sebastin Antony Joe, Faculty in Department of Computing Sciences, Gulf College of Technology, Oman.
Manuscript received on 20 August 2019 | Revised Manuscript received on 27 August 2019 | Manuscript Published on 31 August 2019 | PP: 805-808 | Volume-8 Issue-9S2 August 2019 | Retrieval Number: I11660789S219/19©BEIESP DOI: 10.35940/ijitee.I1166.0789S219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Today the emerging trend and innovative technology is block chain technology. The actual question is how to manage this. The basic concept behind this is mining. Block chain is equal to governance. It is basic type of governance. It governs a book called ledger which contains information. Here we focus on double spend attack in block chain. The attackers has a space to block the new transactions from gaining access to acknowledgements. They make half payments between some or all users. It is even possible to reverse transactions when using the network or holding the complete control of the network thus spending the coins twice which means double spend coins. This attack always exist as a thread and users are panic about their transactions being used by a corrupted miner. The solution for this malicious mining is Proof of Work (PoW) which is proved to be not sufficiently decentralized or secure. So here we are focusing on Proof of Stake (PoS) concept which is a response to the treat of centralization.
Keywords: Blockchain Technology, Double spend, Governance, Mining, Transactions
Scope of the Article: Data Management, Exploration, and Mining