Various limitations in Bitcoin have also sparked some interest in altcoins, which were developed specifically to address limitations in Bitcoin.
The most prominent and widely discussed limitation is the lack of anonymity in Bitcoin.
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Privacy and Anonymity
As the blockchain is a public ledger of all transactions and is openly available, it becomes trivial to analyze it.
Combined with traffic analyses, transactions can be linked back to their source IP addresses, thus possibly revealing a transaction’s originator.
Even though in Bitcoin it is a recommended and common practice to generate a new address for every transaction, thus allowing some level of unlinkability, this is not enough.
Various techniques have been developed and successfully used to trace the flow of transactions throughout the network and link them back to their originator.
Various proposals have been made to address the privacy issue in Bitcoin.
These proposals fall into three categories: mixing protocols, third-party mixing networks, and inherent anonymity.
Mixing Protocols
In this model, a mixing service provider (an intermediary or a shared wallet) is used.
Users send coins to this shared wallet as a deposit, and then, the shared wallet can send some other coins (of the same value deposited by some other users) to the destination.
Users can also receive coins that were sent by others via this intermediary.
This way the link between outputs and inputs is no longer there and transaction graph analysis will not be able to reveal the actual relationship between senders and receivers.
CoinJoin is one example of mixing protocols, where two transactions are joined together to form a single transaction while keeping the inputs and outputs unchanged.
The core idea behind CoinJoin is to build a shared transaction that is signed by all participants. This technique improves privacy for all participants involved in the transactions.
Third-Party Mixing Networks
Various third-party mixing services are available, but if the service is centralized, then it poses the threat of tracing the mapping between senders and receivers because the mixing service knows about all inputs and outputs.
Various services, with varying degrees of complexity, such as CoinShuffle, Coinmux, and Darksend in Dash (coin) are available that are based on the idea of CoinJoin (mixing) transactions.
CoinShuffle is a decentralized alternative to traditional mixing services as it does not require a trusted third party.
CoinJoin-based schemes, however, have some weaknesses, most prominently the possibility of launching a denial of service attack by users who committed to signing the transactions initially but now are not providing their signature, thus delaying or stopping joint transactions altogether.
Inherent Anonymity
This category includes coins that support privacy inherently and is built into the design of the currency.
The most popular is Zcash, which uses Zero-Knowledge Proofs (ZKP) to achieve anonymity.
Other examples include Monero, which makes use of ring signatures to provide anonymous services.
Suryateja Pericherla, at present is a Research Scholar (full-time Ph.D.) in the Dept. of Computer Science & Systems Engineering at Andhra University, Visakhapatnam. Previously worked as an Associate Professor in the Dept. of CSE at Vishnu Institute of Technology, India.
He has 11+ years of teaching experience and is an individual researcher whose research interests are Cloud Computing, Internet of Things, Computer Security, Network Security and Blockchain.
He is a member of professional societies like IEEE, ACM, CSI and ISCA. He published several research papers which are indexed by SCIE, WoS, Scopus, Springer and others.
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