Over the past year, one of the most widely held beliefs that we held about blockchain has been turned on its head. Since blockchain was first released with bitcoin back in 2008, it was widely assumed that the network was unassailable. This claim went unchallenged and untested for over a decade. However, we have since discovered that blockchain can be hacked like any other network. Machine learning is going to be essential to help ethical hackers improve the security of this technology.
Cracks in the Security of Blockchain Are Unveiled
MIT Technology Review author Mike Orcutt published an article about the shortcomings of blockchain security earlier this year. In his article titled Once hailed as unhackable, blockchains are now getting hacked , Orcutt pointed out that a growing number of security flaws were being discovered. Two major cryptocurrency exchanges have been hacked over the past year, as cybercriminals found vulnerabilities in the blockchain.
Cryptocurrency hacking attempts are not new. However, in the past these security breaches were exclusively reported by individual users and third-party organizations that have their personal machines hacked. The idea that blockchain itself could be breached was unfathomable. A guide about blockchain cryptojacking shows this isn’t the case.
Ethical hackers are still trying to figure out how their black hat counterparts have managed to penetrate the defenses of what was once believed to be the most secure network in the world. They are going to need to use sophisticated machine learning technology to answer this question and develop better defenses.
How Ethical Hackers Can Employ Machine Learning to Safeguard Blockchain in the Months to Come
Black hat hackers have only recently started developing successful attacks against the blockchain network. Anybody that thinks these attacks will cease in the near future is being unrealistically optimistic. Blockchain attacks are likely to get even worse in the months to come.
The good news is that there are a number of ways that ethical hackers can use machine learning to support their more malicious rivals. Here are some of the defenses that machine learning can bring to the table.
Reverse engineering generative adversarial network attacks
Sadly, the good guys aren’t the only ones using machine learning. Malicious hackers are also taking advantage of its capabilities to increase the veracity of their attacks.
One of the ways that they do this is with generative network attacks. They create scripts that use machine learning algorithms to better understand the digital security defenses of various networks, firewalls and malware protection software. This enables them to create more evasive malware to infect these networks. It is highly likely that they are using this technology to penetrate the defenses of blockchain.
Ethical hackers can use machine learning to beat them at their own game. They can improve the security of blockchain by getting a better handle on these new attacks. They can reverse engineer the cyberattacks that are initiated through GANs with their own machine learning scripts.
Machine learning can identify patterns in smart botnets that try to assail blockchain
Botnets have been used in cyberattacks for years. Although it is not clear whether hackers have used them to target blockchain networks, the probability is very high.
Black hat hackers are using machine learning to develop more sophisticated botnet attacks these days. Machine learning enables different nodes in botnets and even entirely separate botnet networks to communicate with each other and make more vicious attacks. It is highly likely that smart botnets will be used against blockchain, assuming that hackers have not already started to do so. The article Tearing Up Smart Contract Botnets discusses these presumed risks.
The network activity of smart botnets will be more difficult for human security experts and traditional cyber security technology to identify. However, machine learning will make it easier to notice these types of patterns and prevent access to the network.
The network activity of smart botnets will be more difficult for human security experts and traditional cyber security technology to identify. However, machine learning will make it easier to notice these types of patterns and prevent access to the network.
Machine Learning is Going to be Essential to Maintain Blockchain Security
Blockchain technology is known to be incredibly secure. However, it is not bulletproof. Ethical hackers will need to use machine learning technology to improve the security of blockchain in the years to come.
