The market for AI deception tools is anticipated to reach US$ 288.4 million in 2023. By 2033, the market is anticipated to reach $2,608.5 million USD. During the forecast period, growth is expected to occur at a CAGR of 24.6%.
The market for AI deception tools is anticipated to reach US$ 288.4 million in 2023. By 2033, the market is anticipated to reach US$ 2,608.5 million. During the forecast period, growth is expected to occur at a CAGR of 24.6%.
The demand for AI deception tools to enable proactive and sophisticated IT security is anticipated to increase with the growing usage of cybersecurity technology. Businesses' attack surfaces expand as they shift their programs and data to the cloud, increasing their vulnerability to cyberattacks.
Attackers can access cloud systems using a variety of methods, such as phishing, malware, and other strategies. As a result, cloud systems would increasingly require sophisticated security measures, like AI deception techniques.
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Attackers that use the internet to circumvent conventional security measures are continuously changing their strategies. They make use of zero-day exploits, social engineering, and spear phishing, among other methods. These could make it difficult for conventional security methods to identify and counteract them.
Artificial intelligence (AI) deception tools use machine learning and AI algorithms to adapt to these cutting-edge methods. By doing so, you can improve your ability to detect threats and stay one step ahead of attackers.
AI is used by deception tools to track network activity and spot suspicious activity or unusual patterns. They can trick attackers into disclosing their location and their goals by fabricating plausible-looking but phony assets like decoy servers, files, and credentials. Early detection enables firms to act quickly, reducing the potential harm brought on by cyber threats.
Traditional security systems frequently produce a large number of false positives, warning security teams about potential risks that turn out to be unimportant. Alertness weariness and ineffective resource use may result from this.
AI deception technologies analyze data and weed out false positives using sophisticated algorithms, giving security teams more precise and proactive alarms. Organizations may concentrate on real risks and respond more skillfully by minimizing false positives.
Security information and event management (SIEM) systems are one example of current security infrastructure that AI deception technologies are made to effortlessly interface with. Organizations may take advantage of their current security investments thanks to this integration. These assist in enhancing their functionality with deception-based technologies, which facilitates the adoption and use of these products.
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Key developments in the market for AI deception tools:
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AI Deception Tools Market review , outlook , forecast , demand , size , share , key trends , analysis , Research , overview
Jun 20, 2023
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