Not many are aware that predictive analysis combined with AI and ML have a key role in cyber security to identify potential cyberthreats in organizations. Read on to know how predictive analytics helps in boosting cyber security…
Unlike humans, Artificial Intelligence (AI) and Machine Learning (ML) can perform mundane and repetitive activities with a consistent efficiency and can assemble and process large scattered data-sets and extract intelligent insights out of them. Moreover, learning algorithms can update the models according to the changing trends in real-time. Recent years have witnessed these algorithms contributing to analytical systems to mine and process big data intelligently.
Predictive analysis is the ability to anticipate the next move of a threat and the advantage of that insight is the ability to align your security resources for maximum advantage. Predictive analysis has been used earlier in the Intelligence community and then later in the military environment in cyber security space. Now, it’s becoming more of a calling need across cyber security Industry.
Enterprises constantly accumulate large amounts of data through threat intelligence reports provided by security vendors and information gathered from their own networks. On an organization’s network, threat actors typically move around for weeks or months, leaving signs that they were there.
Artificial Intelligence & Machine Learning
Globally, various companies are spending billions of dollars each year on their security infrastructure. However, the security breaches are occurring despite all the traditional attempts. This is posing a potential threat to the organizations and impacting their abilities to grow and succeed. Predictive analytics as a service is proving to be a potent solution to security and fraud. Computer systems are far more efficacious in identifying the subtle patterns of abnormality when compared to humans, especially with increasing information-sets. Based on predetermined guidelines, machine learning models can detect relationships, similarities and polarities between various parameters such as organizations, people, transactions etc. immediately with an accuracy existed never before. Now it is possible to ascertain which traffic is not normal for the network. Artificial Intelligence and Machine learning combined with predictive analytics has enabled the IT departments of the organizations to detect breaches and attacks in early stages thus giving them sufficient time to take appropriate cyber security measures.
Application in Cyber Security
It is obvious fact that if you know the danger in advance, you are better prepared for it. Hence, predictive analytics has been increasingly used in cyber security all over the business world. Over the years, it has been offering significant dependency to the organizations across the departments especially in risk and security predominantly. Besides bringing efficiencies to the operations, it can also play a major role in gauging customer behavior patterns and identifying anomalies to fortify the security infrastructure. In fact, it has had a major application in cyber security which has been one of the top items in the list of strategic priorities of the businesses across the globe.
It analyzes huge volumes of past data to understand the cause-effect patterns and provides deep insights into the sources of threats, their probability, levels of severity and safeguard options to address them. Predictive analytics helps the CIOs and security executives be prepared for probable occurrences of future.
Rewriting Security Landscape
The introduction of machine learning in predictive modeling given it a revolutionary shift. Predictive analytics, in its independent form, can only provide insights into the probable threats to make appropriate preparations. However, this approach has certain limitations and may not always be able to defend against the attacks in real-time. That is where machine learning arrives to enhance the predictive models. When coupled with predictive modeling, it is able to revamp the overall security infrastructure making it stronger than ever before.
Enterprises have started to explore a new entity as machine learning coupled with predictive analytics has a distinct potential to introduce unprecedented security measures in their systems and applications. However, what you need to remember that ubiquitous intervention of AI and ML will not be sufficient independently. For predictive models enabled by ML to be successful, it’s crucial to understand the know-how of the application. It requires a mix of experience and a meticulous planning. Security practitioners have started to capitalize the knowledge of the experts to use various algorithms and extract valuable insights from the raw data.
The Road Ahead
CIO’s and CISO’s always need foresight and a sharp vision to identify and know everything about the probable threats by their occurrence and intensity. Smart insights and real-time mechanism can provide them with an accurate assessment of the threats quite well in advance. This insight into the future can not only help them in gauging the nature of the threat but also preventing the unfavorable incidents and responding to them in an optimum manner.
It should be fair to say that the Artificial Intelligence and Machine Learning combined with predictive analytics will have a critical role to play as they are slated to redefine enterprise security.
The journey has only started and what follows will be quite interesting and worth watching!