It is critical than ever to have your systems and processes in place to protect your data as more and more companies are embracing digital technologies and cloud solution. Here the question arises, how? Stephanie Donahole has some interesting ideas!
In present times, artificial intelligence has been buzzing around the globe across various industries and applications than ever before as computing power, storage capabilities, and data collection has increased rapidly.
Digitizations seems to drive tremendous advantages to various industries like banking, trade, and healthcare as these sectors have a high level of vulnerabilities towards cyber attacks. Due to this reason, data is becoming one of the top priorities for the companies in this digital era in order to become cyber-immune.
Over the years, we have seen a dramatic increase in online attacks all over the world; not only these threats are increasing in terms of number, but they are also becoming more sophisticated. It is critical than ever to have your systems and processes in place to protect your data as more and more companies are embracing digital technologies and cloud solution. Here the question arises, how? Well, machine learning and artificial intelligence are improving their strategies to make your data stronger to protect them against cyber threats.
How does artificial intelligence help to protect your data?
Nowadays, hackers are launching strikes with the aid of automated attacks because many organizations use the same manual techniques to detect attacks which can contextualize them with external threat data. It can be dangerous to use the traditional techniques because they are time-consuming when it comes to detecting intrusions, and by that time, hackers would have proceeded with vulnerabilities by comprising and accessing your delicate data.
Risk identification factor
To eliminate these challenges, organizations are digging deeper into the use of AI in their cybersecurity management operations. Artificial Intelligence is useful in predicting risks for taking both defensive and offensive security measures. Prior to this, all organizations just needed to cover the networks and conduct endpoint protection, which is not similar currently as the attack surface has increased.
AI can be widely applied to cloud networking with the presence of smart devices like mobile phones, tablets, and smart watches. Threat identification is applied to the deeper attack surface, which only adds problems of maintaining security due to the accelerated velocity of attacks. The bigger the number of tools, the more it leads to bigger challenges as it broadens the attack surface along with more data to analyze.
To supplement the few security expertise, it has become necessary to automate the traditional security measures with the help of advanced technology. The interactive human-machine learning engines are more useful to automate the collection of data as they are correlated with the business criticality in order to establish a real threat and the impact it has on your business. For instance, – innovative algorithms and human interactive machine language play a huge role in coming up with the appropriate responses to an individual risk.
Predictions for the future
Today, for many organizations, it is a hard operation to increase collaboration of the security team who is responsible for identifying security gaps and remediating them. By using a risk-based cybersecurity concept, your proactive security incident notification and human interactive loop intervention can be enabled to automate processes by using it as a blueprint.
However, machine learning is helping to reduce time-to-remediation, but it cannot protect your organization from cyber attacks autonomously and efficiently. Sometimes, the unsupervised machine learning may result in fatigue of the system, which can consequently result in less attention towards it.
No matter if we like to admit it or not, we have reached a point where the massive volume of data is available for security which cannot be effectively handled by mankind. This critical problem has brought us forth to the human interactive machine learning.
To get the most out of artificial intelligence for the security industry, organizations need to recognize what machines and people can do at their best. Advancements in artificial intelligence can provide new tools for hunting threats and helping businesses to protect new networks and decides before a threat is classified by any cyber criminal.
Unsupervised learning and continuous retraining are few of the machine learning techniques which can be utilized in your systems to keep us ahead of the cyber crimes. As the hackers are not resting on their laurels, let us have more time to think creatively about the next attack vector to enhance the abilities of the machine. Keep Learning!