In our digitalized world, cyber incidents are growing at an alarming pace. A constant surge in cyberattacks and our changing security landscape are pushing individuals and organizations to re-assess their security strategies. As a result, a modern and context-aware security model called "adaptive security" is being explored and adopted.

What is adaptive security and does it actually mitigate these evolving threats? What are the best practices to implement it and how do machine learning and analytics help with adaptive security? Let us find out!

What Is Adaptive Security?

Adaptive security is also known as "Zero Trust" security where nothing is trusted by default. This ensures consistent monitoring of threats along with a flexible approach where outdated and legacy security infrastructures are constantly replaced with adaptive ones.

Related: What Is a Zero-Day Exploit and How Do Attacks Work?

The famous Gartner analyst Neil MacDonald described adaptive security as:

“the use of supplemental information to improve security decisions at the time they are made, resulting in more accurate security decisions capable of supporting dynamic business and IT environments.”

The main premise behind adaptive security is the automatic implementation of counter security measures in the wake of any detected threats.

Best Practices for Adaptive Security and the Four-Layer Model

In its true sense, adaptive security is the composition of the following four layers.

Preventative

Prevention is better than cure, and the top layer for adaptive security is designed just for that. This layer isolates any incidents before they arise and outlines the precautionary policies, procedures, and tools to pre-emptively defeat any potential threats.

Detective

detective layer

This layer identifies any threats that the preventative layer fails to detect. The main aim here is to reduce response times for potential threats by stopping them right in their tracks.

Retrospective

This layer excavates further for any missed threats by the previous layer. This is also where a detailed incident analysis is conducted with the help of advanced forensics and threat analytics.

Predictive

Last but not least, the predictive layer keeps an eye out for external events. It provides a thorough risk assessment and alerts the IT staff of any suspicious activity.

The information provided by this layer helps in identifying successful attacks and anticipating and preventing similar ones in the future.

The Role of Machine Learning in Adaptive Security

machine learning

With the rapid transition to cloud-based services, advanced analytics and machine learning play a huge role in protecting big data.

Here are some major benefits that AI and machine learning offer in terms of adaptive security.

Threat Identification

Advanced analytics and machine learning are great at pattern recognition, classification, identification of malicious emails, links, and attachments. This greatly aids in the identification of new and evolving threats.

Threat Tracking

The major advantage of incorporating analytics and machine learning into your security landscape is to be able to track down incidents, especially the ones that can kill applications in seconds and leave no traces behind for investigation.

Instant Analysis of Massive Data

AI provides a great opportunity to analyze massive quantities of data in the blink of an eye which is not possible with traditional security measures.

This not only ensures the real-time detection of threats but also helps in mitigating them by offering risk-based modeling.

The Ability to Use a Threat Stream

data analysis

Most organizations face data threats from multiple sources and find it difficult to keep track of everything. Thanks to AI and machine learning, centralized and intelligent platforms like Anamoly's ThreatStream offer data investigations from multiple sources.

An example of a threat stream would be an IP address that instantly starts scanning all your network endpoints. However, with the use of an intelligent tool, any time an IP behaves oddly, it will be logged into the threat stream for further investigation.

The Major Benefits of Implementing Adaptive Security

Due to its preventative nature, early detection of security incidents is made possible. The real-time evaluation of events, users, systems, and network traffic helps in the early detection of security threats, while the automated responses expedite the resolution timeframe for malicious attacks.

Here are some major benefits that can be achieved through adaptive security.

Early Risk Detection

Premature risk detection is a major benefit of adaptive security. The preventative nature of this security model makes it easy to detect risks before they turn into real threats.

Event Filtering and Prioritization

The use of advanced analytics and machine learning in adaptive security ensures the detection, filtration, and prioritization of security incidents that would otherwise go unnoticed by traditional monitoring systems.

Quicker Resolutions

The real-time assessment of all users, systems, and tools—and the combination of manual and automated processes—aids in early risk detection, while the automated responses greatly shrink the remediation timeframe.

Reduced Impact of the Attack

hacked script with a lock

Due to instant threat detection and quicker resolution windows, adaptive security can shrink the size of the attack surface and limit the damage from spreading further.

Evergreen Multi-Level Monitoring Approach

Adaptive security provides multi-tier monitoring support that is not isolated to just one tool or incidence. By examining the Indicators of Compromise, it evolves continuously to face upcoming threats head-on.

The more the threat vectors change, the more agile the adaptive security becomes.

Flexibility and Integration With Other Tools

By design, adaptive security is a flexible concept that can work across different types of tools and platforms. Instead of restructuring your entire infrastructure, adaptive security can integrate with any existing system.

Out With the Old and In With the New

Adaptive security can mold itself to mitigate any type of threat by adapting and responding to a constantly changing threat environment—something that stale security policies cannot achieve.

With an evolving security landscape rife with distributed workloads, cloud-based environments, and emerging threats, it is imperative for both individuals and businesses to learn about the common threat vectors, get rid of traditional security practices, and focus on emerging threats.

Fortunately, the adaptive security model is here to assist.