AI dark side: Blockchain security threats

As artificial intelligence (AI) continues and integrates into various industries, its potential effect on its safety is becoming increasingly alarming. While blockchain technology is based on the principles of variation, transparency and decentralization, the increase in AI-controlled applications is a significant risk in the integrity and safety of blockchain networks.

Increased AI-Controlled applications

Artificial intelligence transforms many aspects of our lives, from health and finance to transport and education. However, these steps have also led to the development of complex AI-controlled applications that are sensitive to computer threats. These applications often rely on machine learning algorithms to analyze huge amounts of data, identify patterns and prepare forecasts – all of which generate huge amounts of sensitive information.

threats of blockchain security

Blockchain technology is designed to resist counterfeiting and change. However, the introduction of AI-driven applications is a number of challenges that endanger its safety:

• Manipulation : AI algorithms can analyze large data sets, identify samples, and even be able to manipulate data to create false or misleading information. This can lead to many malicious activities, including phishing attacks, invoice receipt and insider threats.

• Network exploitation

  : As AI-controlled applications rely on complex network protocols, they may be sensitive to attackers exploiting sophisticated techniques to exploit the code or infrastructure vulnerability.

• token phishing : blockchain-token-based systems are increasingly used as a means of payment of various transactions. However, AI-driven phishing attacks can target these tokens, resulting in significant financial losses and reputation damage.

• Identity -Theft : The decentralized nature of blockchain technology makes it difficult to monitor and control the ownership of assets. AI-controlled applications can be used to create false identities or steal sensitive data, endangering individual security.

real examples

The dark side of AI has already been seen in various high levels:

• Wannacry ransomware : In 2017, the global ransomware attack known as Wannacry exploited vulnerabilities in Notpetya malicious programs to spread in several countries, including the United States and Japan.

• Equifax Violation : Violation of Equifax 2017 database has endangered sensitive information to more than 147 million individuals worldwide, highlighting the potential risks of AI-controlled applications in the processing of personal data.

• Cryptocurrency Heists : Hackers successfully stole the millions of dollars cryptocurrency through phishing attacks and other malicious activities.

Risks to alleviate

To alleviate the dark side of the AI ​​threats, the security of the blockchain:

• Implementation of robust security measures : advanced security protocols such as encryption, two factors authentication and secure encoding practice.

• Regularly update the software : Keep the software and applications with the latest security fixes to minimize vulnerabilities.

• Complete regular security checks : Regularly check systems for signs of suspicious activity and treat possible weaknesses.

• Development of AI-Controlled security tools : Make special AI-based security tools that can recognize and respond in real time to malicious activities.

Conclusion

The dark side of the AI ​​is a significant threat to the security of the blockchain, highlighting the need for proactive measures to alleviate these risks.

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