AI in cybersecurity has played controversial roles by assisting cyber attackers but it also has proved itself as an effective defense against cyberattacks. In this blog, we are exploring both roles of this rapidly evolving technology.
Cybersecurity has always been a concern of the digital world since the value of data was recognized. Whether to steal financial data or to lock the data for ransom, hackers have evolved and pushed cybersecurity standards to improve with time. As cyberattacks kept getting smarter, businesses dealing with data kept getting anxious and anxious and that is why tools like best ethical hacking tools, AI cybersecurity apps, and more became the new normal.
A Mimecast report says the AI cybersecurity market is expected to grow at a compound growth rate of 23.6% and reach $46.3 billion by 2027. These numbers indirectly project the anxiety that has possessed the cybersecurity industry. Thus, the dependency on technologies like AI is boosting rapidly to improve cybersecurity standards.
With time, not only AI, but plenty of other cybersecurity methods have come into existence as well. To name a few, two-factor authentication, biometrics, captcha login, PINs, Photo ID, proximity scans, and more. Tech giants like Apple, Google, and OnePlus have also increased their dependency on AI and ML technologies to make their smart devices safer and better prepared against possible cyberattacks.
AI hacking is as real as AI cybersecurity. Hackers are able to use the effects of AI in cybersecurity to test and predict the success percentage of their attacks. AI is capable of delivering accurate probability of the cyberattacks planned by hackers.
The tactics, techniques, and procedures (TTPs) are a set of activities used by cyber security machine learning experts or hackers to project how defenders in an AI in a cybersecurity system react. Accordingly, they can focus on looking for weaknesses to go around these defending methods used by AI in cybersecurity systems.
Another method that best artificial intelligence companies have noticed being used by AI hackers in the past is using AI to guess passwords. To crack website backends, stolen smartphones, social media platforms, etc, machine learning hacking tools that can guess passwords faster have been very helpful. Especially in cases where additional security layers like two-factor authentication are missing, these AI hacking tools turn out to be very useful.
Poisoning AI databases is helpful in manipulating AI data to either hide or corrupt cybersecurity systems. This strategy often includes injecting rogue data in AI databases which either manipulate the way AI functions or it gets tougher for AI systems to recognize patterns of cyberattacks in the process. To inject the rogue data, cyber security machine learning systems are fed with the wrongly labeled data which gets tougher for AI systems to recognize and filter.
While AI is something cyber attackers can use in rare cases, it is undoubtedly the best defense existing to protect digital data at the moment. That is why whether to protect games or financial data, machine learning hacking tools are being used by cybersecurity experts across the world. Now, to figure out- is artificial intelligence a threat or not, it is time to look into its benefits for the cybersecurity industry.
We mentioned above how hackers can use AI to simulate the way defenders would behave to counter hacking attempts to avoid them. But AI is also useful in simulating the opposite. In other words, cybersecurity experts also have the leverage to use AI to simulate the impacts of hacking attempts to prepare strategies with better defensive probabilities.
AI is used to filter spam and possible phishing attacks already. However, with time, as more attacks happen, these attacks provide cybersecurity experts with new data to use to improve standards of cybersecurity. Regularly updated AI cybersecurity systems to filter spam can avoid serious phishing attacks.
AI is a technology that can learn itself over time, and combined with human intelligence, AI and ML algorithms can be used to create an unbreakable shield to protect digital data. IBM’s Cognitive Security system called Cognitive computing with Watson for Cyber Security is also an advanced combination of AI, machine learning, and deep learning algorithms that keep improving with time.
Cyberattackers have been known for leveraging hardware failures to enter servers. Thus, AI is useful to keep an eye on all connected hardware to ensure their health and safety. AI is useful in automating the process to keep a continuous check on all connected hardware to ensure no device can be used as the gateway to launch cyber attacks into databases.
The future of cyber security will be more dependent on AI, especially when data is seeing an expansion across industries like automotive, metaverse, education, etc. AI is being used in traditional ways to improve the quality of cybersecurity but tools like top hacking apps are also using the technology to simulate and counter the way hacking attempts work.
In this blog, we gave you some AI in cybersecurity examples to explore its role from the perspective of both sides. We went through some examples of how AI is useful for hackers and we also talked about how AI is helping the cybersecurity industry. So, hopefully, we were helpful in providing you with an insight into the contribution of this technology to the cybersecurity industry.
Now, if you liked this blog, you should also check out our report on leading cybersecurity tips that can be helpful in protecting your privacy better.
Aparna is a growth specialist with handsful knowledge in business development. She values marketing as key a driver for sales, keeping up with the latest in the Mobile App industry. Her getting things done attitude makes her a magnet for the trickiest of tasks. In free times, which are few and far between, you can catch up with her at a game of Fussball.
Cut to the
chase content that’s credible, insightful & actionable.
Get the latest mashup of the App Industry Exclusively Inboxed