By: Katie Johns
Traditional methods to detect malware and cyber security threats are failing. Cyber criminals are constantly coming up with new ways to bypass firewalls and become a threat to an organization’s security. The only way to fight it out is to be more prepared and smarter than the hackers.
As per 2017 Cybersecurity Trends Report, cyber security budgets are set to increase as security professionals anticipate more attacks in the next 12 months. It is indicated that organizations will increase their security spend on cloud infrastructure (33%), training / education (23%) and mobile devices (23%).
Cyber-attacks are getting more complex and smarter
If you think 2016 was bad for cyber-attacks, 2017 proved to be worse. The malware, DDoS, and other types of cyber threats are becoming more serious. Imagine in 2016 alone, 357 million malware were detected and a number of them had left businesses crippled, scouting for better data security. The use of IoT has increased the threat of cyber-attacks. The security infrastructure on these devices will determine how secure the devices are and if there are any weak links in the system, the threat of malware attack will loom till then.
Image Source: http://cdn.nanalyze.com/uploads/2017/04/AI-CyberSecurity-Teaser.jpg
The threat to a business increases if it has data flowing from different sources. The data is constantly exposed to more malware, bots and DDoS attacks. Network systems security is also a matter of concern for businesses. There are threats to networks that have become more common, hacks have become more complex, and they are no longer just a concern for large organizations. The traffic on the network needs to consistently monitored, inspected and co-related.
How is Artificial Intelligence being used?
In order to detect unusual behavior on a network, there are newer security technologies that are using Artificial Intelligence programs. AI uses machine learning to detect similarities and differences within a data set and report any anomalies. Machine learning is a part of AI that can help to recognize patterns in data and predict effects based on past experience and data. AI systems, in most of the cases, use machine learning technology to generate results that replicate human functioning. As per an article published in Forbes titled Separating Fact From Fiction: The Role Of Artificial Intelligence In Cybersecurity, ML, coupled with application isolation, prevents the downside of malware execution — isolation eliminates the breach, ensures no data is compromised and that malware does not move laterally onto the network.
Another way that cyber-attacks are changing are in terms of speed. Humans are not able to detect the abnormalities at the speed that the attacks happen. AI, however, can assess a huge amount of data generated on a network to identify what doesn’t belong there.
AI solutions can work effectively if there are powerful input data, so organizations can start to capture their log data and consolidate into a common data repository so that the broad set of AI-enabled tools and analytics can become effective. There should also be a complete visibility to all aspects of the network, which includes internal network communication, server logs, etc.
Security experts are hoping to use predictive analytics to frame new ways to deal with cyber threats. These are insight driven solution enabled with the help of AI. Machine learning can help in anti-malware, performing dynamic risk analysis and detecting anomaly. AI techniques can be made to learn to remove the noise or unwanted data, and facilitate security experts to understand cyber environment for detection of any anomalous activity. AI can also benefit cyber security with automated techniques to generate cyber courses of action (COAs) whenever cyber threats are detected.
It is believed that now is the time to seriously contemplate artificial intelligence for cyber-security for any business. If you wish to protect you business data against cyber-attacks, speak to one of our cyber security experts today.
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