Implementation Issues with Hashgraphs

Hashgraph is a type of decentralised data structure similar to blockchain. Hashgraph, on the other hand, is thought to perform faster, more fairly, and more reliably than Blockchain, making it a viable and feasible alternative. Let's see if this assertion is reasonable and if there are any facts to back it up. We'll also assess potential Hashgraph issues and compare the technologies listed above.

Diving deep into Hashgraph's mathematical algorithms and functions can be difficult, especially for non-technical users, although the main working concepts are rather straightforward. Hashgraph helps network users to obtain permanent and invariable data consensus. As a result, procedures can be carried out in a safe manner.

Hashgraph provides a graph of connected hashes in which members share information on data transit over the network, as opposed to blockchain blocks of data. Each member calls another at random to synchronise data until all nodes in the system are aware of all relevant data created in the network. This data-sharing and dissemination procedure allows the system and its members to reach a consensus: members agree that events have occurred and when they occurred. In addition, the event graph creates an immutable record of node communication.

What Is the Process?

Let's look at some examples of Hashgraph technology to get a better understanding of it. The following graph illustrates how hashgraph technology works:

The members of the hashgraph technology graph are the computers, which are represented as full nodes. A, B, C, and D stand for Alice, Bob, Carol, and Dave, respectively. The graph's circles serve as containers for transactions and are referred to as events. Furthermore, events can comprise a number of smaller transactions.

According to the diagram, every node has caused an event, and this is the graph's very beginning. The flow of time is now heading uphill. Any node (A, B, C, or D) can choose and exchange information with another node at random using the gossip protocol, which spreads data fast throughout the network to guarantee that all members are aware of what is happening.

Hashgraph architecture event creationThe graph above depicts the structure of an information flow and depicts the history of an event. Every event in the image depicts Alice starting the "rumour" and informing Bob of the details. Each new event retains the preceding two's hashes and transactions, as well as the creator's signature and date. The graph will show and connect the entire information-sharing process between the nodes.

A specific method is employed in the voting idea to allow the network to run a voting algorithm without the need for direct messaging between participants. Hashgraph provides the above-mentioned data structure, which can be examined and followed, so that all members are aware of the event information. As a result, all users can analyse event order and receive all responses without having to communicate directly. Furthermore, the nodes are capable of establishing an agreement on the validity of an event and/or transaction. When two-thirds of the nodes witness transactions and vote that they are genuine, the transaction is declared valid. This voting mechanism is designed to ensure that nodes communicate in a transparent and trustworthy manner.

Hashgraph Benefits

Let's take a look at Hashgraph's best features before moving on to its faults and hazards. Hashgraph is an exceptional technology capable of competing with Blockchain because of its speed, fairness, and security.


When it comes to employing the gossip protocol, which circulates and shares messages among network users, hashgraph technology is quick. It also does selective message optimization in order to reduce communication expenses. Furthermore, the consensus protocol is generated by this "gossip about gossip." Hashgraph is also quick since it operates in a private, permissioned network environment.

Transactions will be processed in seconds because to the high speed and low latency. According to studies conducted by the business, 32 computers operating at 50,000 transactions per second can attain consensus finality in three seconds. The time it takes to establish consensus can be as little as 1.5 or even 0.75 seconds, depending on the number of machines and areas involved.


Consensus timestamping ensures fairness by ensuring that the transaction that reaches two-thirds of the network is the first. Because the majority of people are present during the transaction, the system is fairly fair, and unfair decisions are avoided. If harmful conduct is suspected, nodes are authorised to halt the transaction and report the illegal or malicious behaviour, preventing the transaction from reaching consensus.

Because no single individual is in charge of everything, or is responsible for assigning a transaction timestamp, everyone has equal rights and possibilities. As a result, users have equal access to information, timestamps, and transaction order.


Hashgraph users benefit from a number of features that increase their security and safety. Among them are the following:

  • Cryptography. Hashes encrypt communications and interactions and are also used to sign certain occurrences. Hashgraph technology's algorithms adhere to security standards to secure private and confidential information.

  • aBFT. Asynchronous Byzantine Fault Tolerance ensures that no one user or small group of users may stop other nodes from reaching a consensus. This is avoided by BFT, which ensures resistance to all types of attacks.

  • Compliance with the acid. All nodes must comply with atomicity, consistency, isolation, and durability in order for a transaction to be completed.

  • DoS resiliency that is distributed. Hashgraph avoids putting one person or group in charge of everything, ensuring a fair method for reaching an agreement. This reduces the likelihood of nodes flooding the network or causing it to fail.

Hedera Hashgraph also offers improved performance, cost, and state efficiency to its consumers.

The benefits of Hedera Hashgraph also include governance, stability, and regulatory compliance.

Model of Governance

The governance model consists of a collection of regulations that must be followed in order to comply with the technological software policy, coin distribution, and incentive model. During transaction processing, open consensus establishes confidence between nodes. Additionally, inside the governance model, all members can be chosen and elected, with the ability to vote and decide on policy rules and codebase changes.


Another benefit of Hedera is its stability. Technical and legal safeguards have been devised to ensure that the system operates in a stable manner that is not jeopardised by the prospect of forking. Signed state proofs, ledger ID, and fork handling are all provided via technical controls.

Legal Restraints

The codebase is subject to legal regulations to guarantee that it is:

  • open

  • transparent

  • accessible

This allows everyone to see the code and its sources, which may be verified further.

Regulatory Adherence

Know-your-customer (KYC) and anti-money-laundering (AML) measures are prioritised in regulatory compliance. An opt-in escrowed identity method, on the other hand, allows individuals to link their verified identity to additional private accounts. This gives the government the oversight it needs to ensure regulatory compliance.

Blockchain vs. Hashgraph

Let's compare Hashgraph's basic features to blockchain's to identify potential implementation issues.

Data Retention

The essential principles of data storage on Hashgraph and Blockchain are comparable. Blockchain stores data in blocks, which contain transaction records such as the timestamp, current hash, and transaction from the previous block.

Hashgraph stores data in the same way, but in the form of a "event." Each event includes timestamps and regular hash transactions, the history of which may be examined in the graph.

Structure of Data

The following is the data structure:

The blockchain protocol chooses a node that is authorised to add a transaction block to the overall chain of blocks. All computers (nodes) communicate with each other in Hashgraph, delivering the most up-to-date information they have via gossip, whose relationships are documented in the graph. As a result, the blockchain structure resembles a tree with unbroken chronological branches, whereas the Hashgraph structure resembles a tree with branches wreathed inside.


Proof of Work (PoW) and Proof of Stake (PoS) consensus techniques are used in blockchain.

Proof of Work

There is a requirement to specify an expensive calculation, which is termed mining, according to PoW, which is employed by main blockchains. Each miner that solves a block problem is rewarded. This creates rivalry among miners, as those who solve issues faster are rewarded more. Block validation, on the other hand, costs a lot of energy and takes a long time. Safety algorithms are also executed on nodes to check transactions and prevent malicious behaviour. If a block with fraudulent transactions (such as double spending) is attempted to be included, the subsequent blocks must reject and delete it. Attacks are more likely to occur if a chain of blocks contains numerous dishonest nodes. It should be noted, however, that unanimity can only be achieved through PoW. As a result, transaction recipients must wait for other nodes to validate the transaction.

Proof of Stake

In the case of PoS, a new block builder is selected based on his or her wealth (stake). Miners charge fees on transactions since PoS does not have a reward mechanism. Furthermore, the cost efficiency of PoS currency is thought to be 1,000 times better.

However, it is important to note that the PoS protocol is subject to hacking attacks. The bigger the stakes, the greater the chance of a system attack.

Byzantine Fault Tolerance in an Asynchronous Environment

The aBFT protocol (Asynchronous Byzantine Fault Tolerance) underpins hashgraph technology, which ensures strong security and resistance to fraud. The protocol does not require extra node effort because it is based on links between nodes. The steps are as follows:

Step 1: Each round is generated when one event can connect more than 2/3 of the current round's starting events through more pathways than 2/3 of the node population.

Step 2: When a new round is generated, the first new nodes in the new round will vote to see if they agree with the data in the previous round's first row of events. They only need to make sure they're connected to these nodes to do so.

Step 3: Collect the node answers from the third round. The 4th round nodes are necessary for this. They must be able to clearly view the third round node. The consensus is reached if one of the 4th round nodes collects a super majority (more than 2/3 of the population) of favourable votes on the data in the 2nd round.

aBFT protects the entire community of users from the effect of a single user or a small group of users. To develop a shared understanding, all members must agree on the details, authenticity, and timeliness of the occurrence.

Let's compare the above-mentioned protocols using a Mesh-network as an example.

When it comes to the finest matching protocols, it's worth noting that blockchain proof of stake isn't the ideal option because the larger the stake, the higher the risk of failure. As a result, proof of stake should be changed, with constraints, to work well within the Mesh network. The amount of shared data with the network, for example, must be appropriate and equitable across the nodes. The risk of assault can be eliminated with this type of restriction.

Mesh networks have a star-and-tree architecture, with network nodes connected to smaller groups of switches/bridges and infrastructure linkages organised hierarchically. The Hashgraph aBFT protocol's ability to contribute to fault tolerance demonstrates that it is well-suited to the functional mesh-network principle. Learn more about the decentralised Mesh network's blockchain technologies.

Cryptoauxiliary can assist you in setting up an ICO cabinet that meets your needs and interests if you're unsure about the protocols to utilise for your project.

Problems and Pitfalls with Hashgraphs

After going over the key features of Hashgraph technology, it's evident that there are various advantages, including speed, fairness, state efficiency, and superior performance. The platform, on the other hand, is yet to be launched, which is a Hashgraph disadvantage. Many experts have raised concerns about certain features, and they have already identified hidden hazards and Hashgraph flaws that have yet to be addressed. Let's take a closer look at a few of them.

Corruption Possibilities

Hashgraph's downside is that it does not provide something similar to blockchain nodes in the form of incentives in the form of rewards, which prevents the potential of cheating. As a result, the platform becomes an intriguing case study for potentially malevolent and fraudulent behaviour.

To reach consensus, Byzantine tolerance necessitates the agreement of a majority of nodes. The majority of voting decisions are made by the council. But what if the council is tainted and wants to declare a system attack? There isn't anything that can be done to stop it. When users interact with a corrupt message, another issue can arise. The message/rumor is spread wrongly, causing the entire data structure to be ruined.

Consider the following scenario. Consider a doctor who has been invited to three scientific conferences and has been nominated for an award. Obviously, the doctor will not be able to visit all three, so he will attend the first. Because cellular connection is not available in this case, the doctor sends someone (a runner) to the other conference to see whether he has gotten an award and pays him $20. When a cheater, who is interested in the doctor's failure, pays the "runner" $30 to pass the false information, the problem arises. This causes erroneous information to circulate, further influencing the situation; as a result, even if the doctor is picked, he may not receive an award.

Hashgraph events and false gossip can be used in the same way. As a result, corruption looks to be a problem that has to be addressed. The implementation of non-aBFT consensus on top of Hashgraph raises this issue in Hedera Hashgraph.

“Decentralized” Centralization

Although Hashgraph is marketed to the public as a decentralised distributed platform, because its algorithm is technically decentralised, external state control remains. Leemon Baird owns the intellectual property for Swirlds' technology and algorithm, and he has the authority to regulate and govern the network's development. No one knows how this will affect the amount of control or whether there will be good or bad actors as a result.

Security and Scalability Issue with Hashgraph PoS Outside aBFT

Implementing Byzantine Fault Tolerance require nodes, which are required for the development of virtual machines in order to execute smart contracts. Hedera By implementing proof-of-work consensus, Hashgraph adds an additional layer of these criteria to increase processing power for virtual machines. This raises security concerns, as aBFT is thought to be fast and secure, whereas PoS consensus is more vulnerable to potential assaults. Another security concern is the uncertainty about bandwidth protection against possible assaults. This issue could slow down smart-contact execution even further, and it's unclear whether it will be faster than Ethereum SC execution.

aBFT Turing-Complete Smart Contracts Cannot Be Supported

To execute programme instructions, Hashgraph does not require nodes to have a sufficient level of computational power and hardware resources. As a result, Hashgraph is not a Turing-complete environment in and of itself. Hedera's method is based on the idea of gaining such processing capacity by adding an additional layer of nodes connected by PoS consensus. However, instead of aBFT, transactions must not be hashed (mutable) and processed on a PoS blockchain. Only after the smart contract has been processed will it be hashed and submitted as gossip to Hashgraph for verification, posing a serious threat to Hashgraph's security and anonymity.

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Though Hashgraph is comparable to blockchain in that it can work faster and more fairly, and it is more protected in terms of security, there are still some unanswered problems. As a result, there is a risk of probable corruption. Apart from aBFT, other difficulties include centralization, reliance on a single authority, security and scalability issues, and the inability to execute Turing-complete smart contracts. Let's see what the future holds and how Hashgraph hopes to address the challenges raised above.

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