Have you ever wondered about the security risks that come with using blockchain technology? While it has revolutionized how we initiate transactions, there is always a potential for attacks. Along with crypto phishing attacks, flash loan attacks, dusting attacks, and more, one of the most notorious threats is the Sybil attack, where a single computer can control multiple fake identities and wreak havoc on the network.
In this blog, we’ll take a deep dive into ‘what is a Sybil attack?’, various types of Sybil attacks, and the problems they can cause on online networks. More importantly, we’ll show you how to prevent them, giving you the confidence and trust to use blockchain technology with ease.
Table of Contents
A Sybil attack, also known as an identity or reputation attack, is a type of online security threat in which an individual or group creates several nodes, accounts, or devices with the intention of taking control of a network. It could be as risky and complicated as hacking into a high-security network, or it could be as easy as utilizing many accounts on a social media platform.
In blockchains, a Sybil attack refers to engaging in activity prohibited by operating numerous nodes.
Usually, hackers will utilize one of these two types of Sybil attacks:
Direct Sybil attacks include rogue nodes communicating with real accounts. When a sufficient number of honest nodes on the network authenticate these phony accounts, it becomes simple for a threat actor to subvert or exercise control within a system.
In contrast to direct attacks, indirect Sybil attacks rely on accounts that act as intermediaries in order to disseminate false information. When these communication connections get tainted, legitimate nodes become more susceptible to the exploits implemented by the attacker. It is typically more difficult to determine who is responsible for this assault when the approach does not involve direct connection with any other nodes in the network.
While there are many ways blockchains can be attacked, there are precautionary measures that can be implemented for each as well. For example, here’s how blockchains can prevent Sybil attacks:
The real identities of network participants can always be authenticated through identity validation, effectively preventing Sybil attacks. The validation process depends on a centralized authority that checks the identities of the entities in the network and can conduct reverse lookups. Validation of identities can take place either directly or indirectly, as follows:
It’s important to keep in mind that while identity-based validation offers accountability, it comes at the expense of anonymity, which is essential for most peer-to-peer network configurations. Even though it is still possible to maintain anonymity by eliminating reverse lookups, the validating authority is vulnerable to the possibility of being targeted in an attack.
Analyzing the connectivity data contained within social graphs are used to thwart Sybil attacks. This allows the user to keep their anonymity while reducing the damage that a specific Sybil attacker may cause.
Some of these methods already exist: SybilGuard, SybilLimit, and the Advogato Trust Metric. Computing a sparsity-based measure to identify possible Sybil clusters in distributed systems is another method social graphs can use to thwart intrusions.
Sybil attacks can be made more expensive by using economic fees, which act as artificial barriers to entry. Investments of stake or storage space in preexisting cryptocurrencies and proof-of-work protocols are two examples.
Proof-of-work (PoW) requires every user to demonstrate that they spent computational effort solving a cryptographic puzzle. Competing miners add new blocks to the blockchain in permissionless cryptos like Bitcoin. Those that provide computational power to the network receive compensation roughly in line with the time and energy they have put in.
There have been several attempts to create a distributed protocol immune to Sybil attacks. Some examples are:
Any new nodes or identities added to the blockchain might be Sybil nodes. As a result of this, they need to be regarded with suspicion for some time before their overall genuineness can be validated.
Develop a structure in which the cadets hold the nodes’ integrity with high esteem. A hierarchical structure, for this reason, is an extremely effective defense against Sybil Attacks.
The people who have been part of the network for longer ought to have greater powers than the newcomers. This way, even if the new Sybil nodes wanted to launch a large attack, they would be unable to.
One of the first known Sybil attacks against a P2P network was launched against Tor in 2014. Tor is a decentralized system that enables anonymous communication.
In that year, it was attacked by people trying to learn the whereabouts and identities of Tor users. The Tor team discovered some evidence in the unofficial post-mortem report suggesting the attack was a Sybil attack, combined with a traffic confirmation attack.
From a single IP address, the attacker managed around 115 relays. This indicates that there was just one person responsible for the many relays. The attacker gained excessive sway over the network and obtained access to data.
In 2020, another Sybil attack, likely more lethal, occurred on the Tor network again. The 2020 attack’s hackers particularly targeted Tor users who held Bitcoin.
Bitcoin owners’ online transactions could be intercepted and stolen by an attacker in control of a large number of bogus Tor relays.
The consequences of a Sybil attack on a blockchain’s security can be severe. These are the threats they pose:
Security and anonymity are prioritized in blockchain systems. However, a Sybil attack challenges this fundamental principle. A bad actor can operate a node in order to snoop on the information passed between the honest ones.
A blockchain may be vulnerable to a Sybil attack depending on the information the attacker is trying to obtain. One of the specifics may be the unethical acquisition of IP addresses hiding behind trustworthy nodes.
The 51% assault is an example of a weakness that a Sybil attack can introduce into a blockchain system. When one individual or organization controls more than half of a blockchain, this is called a 51% attack.
When more malicious or phony nodes exist than legitimate ones, this control grants the attacker privileged decision-making abilities within the protocol. Therefore, the former can gain control of such a blockchain by casting more votes than the latter. Sybil attacks are an inevitable catastrophic breach of security.
The occurrence of a Sybil attack can also lead to a Block Withholding attack. This is an attack in which a sizable portion of validators is working against the interests of the network by refusing to add new blocks.
This can cause the blockchain to become unusable over time and require human intervention to fix.
Sybil attack is one of many ways hackers can get into a blockchain system and mess up how it works. Cybercriminals make fake identities called Sybils, which they use to get into a network and take control of it. As someone involved in blockchain development, you must set aside a significant budget for strong data security measures to protect against data theft such as the kind caused by sybil attacks, 51% attacks, and more!
Now that we have explored ‘what a Sybil attack?’ and the problems it causes, we hope you can better protect your data!
Mechanisms for spotting Sybil attacks try to tell the difference between Sybil users and normal users by looking at how users interact with each other and behave. Sybil attacks can be found and stopped when the validation system points them out in time.
Sybil attacks can be stopped in several ways. Some of these are SumUp and DSybil, which are algorithms for recommending online content and voting that Sybil can’t fool. Whnau is another solution: it is an algorithm for a distributed hash table with built-in Sybil protection.
A Sybil attack is a dangerous threat to wireless sensor networks in which a bad actor creates an unlimited number of fake identities without permission. In wireless sensor networks, Sybil attacks can be stopped in a number of ways, such as through message authentication and passing methods.
Sybil attacks could work on any blockchain. The size of the network often makes a difference, however. The more miners are needed to verify transactions, the more secure a network is, since it’s hard for one person or group to control 51% of the miners. Most blockchains have structures that make it nearly impossible for Sybil attacks to happen.
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