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Artificial Intelligence for Smarter Cybersecurity

Artificial Intelligence (AI) has numerous real-life applications in multiple industries, and cybersecurity can benefit from the technology the most.

One of the more compelling uses of AI is in cybersecurity because systems can learn and adapt to emerging threats faster than machines that are “programmed” to identify these threats. A typical security solution will only detect and thwart threats it already knows about, which leaves the window open for zero-day exploits and other nasty forms of malware. A system augmented with AI will recognize the new threat and adjust its defenses to neutralize or quarantine the danger until it can be effectively neutralized.

AI Applications in Cybersecurity

Much like proactive monitoring technology that sweeps the web to protect your identity from criminals engaged in identity theft and fraud, Artificial Intelligence’s applications on a broader cybersecurity net can solve even the most challenging aspects in the industry. AI can handle even the most complex problems, and today’s ever-evolving cyberattacks inevitably fall under that premise. Cybersecurity teams can use AI, machine learning, and deep learning to automate threat detection and keep up with the threat actors. With AI, the response is immediate and more effective than traditional approaches centered on software that behaves linearly.

Cybersecurity as a Non-Linear Approach because of the New Threats and Challenges 

Consider the large attack surface that needs protection – large organizations have thousands of devices, large chunks of moving data, and hundreds of attack vectors – it’s like an all-you-can-eat buffet. The problems are exacerbated by a shortage in the number of skilled security specialists with the commensurate experience to deal with current cybersecurity issues. Experts estimate that there will be a shortfall of 3.5 million cybersecurity professionals worldwide by 2021, while the number of hackers continues to grow. Hackers also target small and medium enterprises. There are some tips that small and medium enterprises should follow to be protected.

Practical Cybersecurity Uses for Artificial Intelligence:

  •       AI techniques can be used to remove unwanted data or noise to enable higher detection rates of abnormal and malicious activities.
  •       AI can automate the methods used to generate the proper response to a specific threat detected by the system.
  •       AI can analyze significant amounts of data that can augment existing systems and improve or develop new ways to defeat cyber attacks.
  •       AI can help protect organizations from existing threats and identify zero-day malware.
  •       AI-based cybersecurity systems can help develop practical security standards for better protection and enhanced recovery strategies.

The use of AI in cybersecurity can also help create a real-time, dynamic, and global authentication framework that can switch locations or change network access privileges on the fly.

The AI/Cybersecurity Conundrum

IT security professionals use Artificial Intelligence and Machine Learning (ML) to enforce “smarter cybersecurity” practices to effectively shrink the attack surface of the organizations they’re trying to protect, as opposed to reacting and chasing after malicious activity. However, large cybercriminal gangs, ideological hackers, and state-sponsored hacking groups can also use AI to augment their strategies to avoid detection and defeat defenses. According to a study conducted by Webroot, 90% of Japanese and American cybersecurity professionals expect hackers to use AI for their attacks.

As AI adoption in the cybersecurity space increases, organizations need to be proactive in securing against the possible downsides of this new technology. These are:

  •       Hackers can defeat security algorithms by targeting training data and warning flags AI systems learn from and corrupt or change them.
  •       AI systems need massive volumes of events and data to train on, or they run the risk of delivering false positives and inaccurate results.
  •       Cybercriminals can use AI to smash through protections by developing mutating malware that can adapt to avoid detection.
  •       Organizations that fail to detect manipulated data will struggle to regain the correct information that supports AI learning.

The bright side is that AI in cybersecurity will be able to instantly spot malicious code in a system, detect intrusions on the network, and provide a measured response to these threats. AI can create powerful human to machine connections that work in unison to recognize and adapt to emerging problems.


Cybercriminals have leveraged the power of emerging technology over the years to launch their attacks on vulnerable systems yet to be patched. After all, technology is an equal opportunity enabler – both the cybersecurity world and the criminal underworld uses the latest tech to test their wits against the other. The use of AI in cybersecurity levels the playing field a little, because cybersecurity teams will have extra processing power to anticipate and detect cyber threats as they come.

This scenario is somewhat like a double-edged sword – cybercriminals will get their grubby hands on the newest tech eventually. Cybersec teams need to be proactive and vigilant in identifying the risks of AI falling into the wrong hands by developing better machine learning and deep learning techniques to combat hackers armed with the same tools.

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