AI-powered attacks

What Are The Risks Involved In AI-Powered Attacks?

What is Artificial Intelligence?

Now that the concept of machine learning and AI is possible, there is always the fear of AI-powered cyber-attacks. The use of this technology in the modern is unignorable. AI is creating new ways of thinking creatively and opening numerous doors of imagination that were impossible a few years ago. In an age where artificially working prosthetics exist in the medical industry, a major technological miracle is expected every day.  

Machine learning is a technology that enables machines to self-learn by identifying computer-defined patterns and trends. Based on such trends and patterns, machines can think human-like. This technology assists the industry sector and keeps on improving industries with each passing day. 

Risks Involved In AI-Powered Attacks

While this technology is a blessing for industries like healthcare, where it has opened new ways of innovation, in the same manner, it can act as a curse as well. Every technology has two aspects and implications. Firstly, proper usage and implication can lead to significant advancements. But on the other hand, fraudsters can also use it for their benefit. This negative aspect can cause unimaginable damage to any organization.

Here are a few risks involved in AI-powered attacks:

1. AI Phishing Attacks

The usual phishing emails were easily identifiable back in the day. However, it’s not that easy to detect phishing emails easily. With recent machine learning techniques, hackers can easily make such mails look authentic. This deception of portraying spam-filled emails as emails that seem to have been sent from a reliable source is possible because of AI phishing attacks. This is one of the most AI-powered attacks.

2. Data Poisoning

Data poisoning is a malicious activity that tampers the machine learning data to evaluate undecisive results. Such an intrusion can harm an already trained machine and disturb the pattern description of AI technology. The algorithm learns from the machine learning data. If this data gets tampered with, it can create unfavorable outcomes resulting in an overall failure. This attack can harm organizations in the worst manner.

3. Corrupted Patterns

Organizations can face the threat of corrupted patterns for machine learning technology to read. Once such practices get corrupted, the overall system is bound to malfunction abruptly. Thus, the victims need to fight AI with AI. Such intelligence requires the same level of brilliance to break into pieces.

Statistics To Lookout For

  • First six months of the year 2020, 30% of sensitive data was under attack 
  • At least in one of the functions, AI was used according to 50% of respondents
  • An increase of 270% is experienced from 2015 onwards in the usage of AI technology

SOCVault provides immense performance in the next-gen managed response detection services. These services are creating new ways to face the challenges of cybersecurity. Through an amazingly designed feature of XDR, experience a human yet machine learning-based security service.  

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