Recently, most of the organizations experienced severe downfall due to an undetected malware, Deeplocker, which secretly evaded even the stringent cyber security mechanisms. Deeplocker leverages the AI model to attack the target host by using indicators such as facial recognition, geolocation and voice recognition. This incidence speaks volumes about the big role AI plays in the cybersecurity domain. In fact, some may even go on to say that AI for cybersecurity is no longer a nice to have tech rather a necessity. Large and small organizations and even startups are hugely investing in building AI systems to analyze the huge data trove and in turn, help their cybersecurity professionals to identify possible threats and take precautions or immediate actions to solve it.
AI is being employed by attackers, such as within Deeplocker malware, which avoided a tight cyber security mechanism by utilising AI models to attack target hosgts using face recognition, geolocation and speech recognition. This attack speaks volumes about the huge role of AI in cyber security domains. To counter attack and defend, AI for cybersecurity has become necessary. Large and small organizations and even startups invest heavily in building AI systems to analyze large data and in turn, help their cybersecurity professionals to identify possible threats and take precautions or immediate actions to resolve them. Phishing, one of the simplest and most common social engineering cyber attacks is now easy to master by attackers.
Organizations continue to embrace the Internet of Things (IoT), the cloud, and mobile technology. This has influenced considerable changes in the threat landscape and created more vulnerability points. Cybercriminals are leveraging these new vulnerability points to develop and launch sophisticated, high-volume, multi-dimensional attacks. Such attacks mean that data is at risk, and organizations must analyze potentially malicious files. Using artificial intelligence software, organizations can process large volumes of threat data and adequately prevent and respond to breaches and hacks.
By the year 2021, cybercrime losses will cost upwards of $6 trillion annually. It's no surprise, then, that the cybersecurity industry is exploding as it grows to protect the networks and systems on which companies and organizations operate and store data. Because effective information security requires smarter detection, many cybersecurity companies are upping their game by using artificial intelligence to achieve that goal. A new wave of AI-powered solutions and products keep bad actors on their toes while giving IT teams much needed relief. Here are 30 companies merging artificial intelligence and cybersecurity to make the virtual world safer.
In the present scenario, techniques like AI and machine learning are involved in almost all sectors. These techniques help organisations by various means, starting from getting insights from raw data to predicting future outcomes, and more. Focussing all the benefits of AI and ML, the utilisation of machine learning techniques in cybersecurity has been started only a few years ago and still at a niche stage. AI in cybersecurity can help in various ways, such as identifying malicious codes, self-training and other such. Here is a list of top eight machine learning tools, in alphabetical order for cybersecurity.