liu, tempo Date: 2021-09-08 10:40:17 From:cengn
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Despite the many benefits AI brings to cybersecurity systems, it doesn’t come without challenges and limitations. The drawbacks of implementing artificial intelligence into cybersecurity present themselves in two primary forms: usage by cybercriminals and the high adoption barriers.



AI is a dual-use technology, being used both for offence and defence. On the offensive, AI supports malicious attacks and can make them even more effective, increasing their precision and identifying more attack points on a network.


Although we learned AI is a powerful tool for defensive purposes, it has a major disadvantage. Cybersecurity is restricted by regulations that hackers are not. High-risk applications, understood as systems that use AI for critical infrastructure, safety, and deal with confidential information, are usually strictly Government-regulated. Unfortunately, this may limit how an organization can use artificial intelligence defensively.


On the other hand, as the cost of developing applications diminishes and the attack surface increases for cyber threats, it becomes easier for criminals to leverage the technology for harmful purposes.Neural Fuzzing Artificial Intelligence


AI technology allows for faster, more precise, and destructive hacking, introducing a new wave of malicious attacks.


Hackers commonly use one popular program analysis technique, known as fuzzing, to find vulnerabilities in complex software. This technique presents a target program with malicious input designed to cause buffer overflows, crashes, memory errors, and exceptions and expose system weaknesses.


Combined with AI, it becomes a severe cyber threat as hackers increase the precision and efficiency of their attacks, obtaining critical information on a system’s weaknesses more easily by combing through large data sets quickly.


Another example comes in the form of more effective phishing attacks. AI-powered phishing can quickly navigate sensitive data, and extract only the necessary information, to reduce traffic and make the malware harder to detect.


 cybersecurity systems



Companies need to invest considerable time and money in computing power, memory, and data centres to build and maintain artificial intelligence systems. Over time these costs have decreased with the advancement of technology, making quality servers more affordable.


Security automation effectiveness also continues to grow, becoming a prerequisite for any organization running on the cloud. Globally, businesses with no deployed security automation saw an average total data breach cost of $6 million. In comparison, those with fully deployed security automation had an average total cost of a data breach at $2.45 million.


Cybersecurity automation powered by AI is becoming indispensable for organizations. The most significant roadblocks for its adoption and deployment are talent acquisition, data complexity, and the employment of proper AI tools.


Adoption Barriers for Artificial Intelligence (AI) in Cybersecurity


The skills gap is an important barrier for AI deployment in businesses today, with 37% of organizations expressing difficulty finding talent with the appropriate level of AI expertise and knowledge. The need for AI skills is critical mainly to companies still exploring AI adoption. Those focused on AI deployment see data complexity and having the right toolset as crucial issues.


Data complexity stems from keeping up with the large flow of data through the network and sourcing the correct data set of malicious codes and malware to use in AI model training. Organizations need to properly manage the enormous amount of different data types and data silos. Not only does this require skilled workers, but also the right toolset.


Tools refer to cyber solutions an organization integrates into its network. Many factors are essential to consider when choosing the right toolset, like whether an organization is locked in with a vendor or uses AI solutions from their cloud provider. The important thing is to get it right the first time, as it’s costly and challenging to switch tools.



Network activity continues to grow, and just about all critical information is stored on the cloud. This reality means cyber threats are becoming more frequent, and organizations must prepare for faster and more compromising attacks on their system’s integrity. Artificial Intelligence is the answer, with adoption rates swiftly rising over the years and a proven track record of improving security and providing cost savings in the long run.


Nevertheless, it is essential to consider that cybercriminals also use AI to penetrate systems. So, organizations must not fall behind in this arms race and consider employing AI in their cybersecurity efforts to protect their network from malicious threats.

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