The threat from AI-powered cyber attacks in blockchain networks
Since the world is increasingly dependent on blockchain technology, the potential for cyber attacks to impair these networks has never been more pronounced. Blockchain networks that use a decentralized and secure digital general book to record transactions have made enormous progress in recent years, but their security is no longer a subsequent thought.
Artificial intelligence (AI) and machine learning (ML) algorithms are increasingly used to supply AI-powered cyber attacks in blockchain networks. These attacks can be devastating, not only for individuals and companies that rely on these networks, but also for the broader economy as a whole. In this article we will examine the threat from AI-affiliated cyber attacks in blockchain networks and examine some of the most important weaknesses that make you so appealing for hackers.
What are AI-powered cyber attacks?
AI-powered cyber attacks include the use of algorithms for machine learning to identify and use weaknesses in blockchain networks. These attacks can accept many forms, including:
- Sub-channel attacks : Hackers use techniques such as timing or power consumption analysis to close confidential information about the internal work of a network.
- Data poisoning : attackers inject malicious data into the network to manipulate his behavior or create fake transactions.
- Cryptanalysis : Hackers use mathematical algorithms to break the encryption methods used by blockchain networks.
Why are AI-powered cyber attacks in blockchain networks so threatening?
Blockchain networks are theoretically very safe, but their real implementations have numerous weaknesses that can be used by hackers. Here are some reasons why cyber attacks in blockchain networks are so threatening:
- Lack of standardization : There is currently no standardization in the design and implementation of blockchain networks, which makes it difficult to identify and remedy weaknesses.
- Inadequate security measures : Many blockchain networks are based on basic encryption methods such as AES-256, which can be easily broken with highly developed algorithms.
- Bad network architecture
: Blockchain networks are usually designed as a decentralized system, but this also makes them susceptible to attacks if they are not properly secured.
Examples of AI-powered cyber attacks
Several top-class hacking incidents have shown that the threat from AI-operated cyber attacks is equipped in blockchain networks. Some examples are:
- Parity technology : In 2020 parity, a DAPP developer (decentralized application), was hacked using an AI attack by Side Channel. The hackers were able to receive assets of $ 150 million.
- CoinCheck : 2018 Coincheck, a Japanese cryptocurrency exchange, was hacked with a crypt analysis technique to break the encryption methods used by its blockchain network.
Mastive the threat
While the risk of cyber attacks in blockchain networks is undeniable, steps can be taken to alleviate this risk:
- implement robust security measures : Use extended encryption methods and implement secure authentication mechanisms.
- Use the multi-factor authentication : Make sure that users have to provide several types of review before accessing confidential information or transactions.
- Update regularly and patch software
: keep the software from Blockchain Networks up to date to ensure that weaknesses are quickly patched after detection.
- Run regular security audits : Scan regularly for weaknesses and weaknesses in the architecture of the network.
Diploma
The threat from AI-powered cyber attacks in blockchain networks is a serious problem that cannot be ignored.