When it comes to enterprise security, prevention is better than cure. A recent study conducted by the University of Maryland confirmed that threat actors attack every 39 seconds, averaging 2,244 times a day.

The insurgence of cybercrimes is forcing organizations to re-evaluate their security strategies. In the purely digitized world of today, a growing influx of multiple devices, cloud computing and rapidly changing IT strategies and platforms has led to the emergence of a dynamic threat prevention solution known as “Adaptive” or “Context-Aware” security. The next section will shed some light on adaptive and context-aware autonomous threat prevention and analytics.

What is Context-Aware Threat Prevention?

According to the well-known Gartner analyst Neil MacDonald, context-aware security is:

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.

In a nutshell, context-aware security is the practice of utilizing various types of context information to improve security practices by replacing static and legacy security infrastructures with adaptive ones. This concept was predicted by Gartner in 2012 as an upcoming solution for enterprises looking to incorporate adaptive practices in their security landscape. Sure enough, his predictions came true and more and more organizations are now transitioning towards adaptive threat prevention. Another aspect of context-aware threat detection is self-directed or automated detection that is a much-needed requirement now that organizations are moving to cloud platforms. By automating threat hunting in cloud-based applications, seamless risk identification can be easily achieved.

What is Adaptive Threat Analytics?

Adaptive threat analytics is an ever-evolving cybersecurity monitoring model that meets the needs of integrated and continuous IT deployments as well as hybrid environments like the cloud. Continuous and preventative threat hunting and management is the main premise behind adaptive threat analytics, where pre-emptive monitoring of potentially looming threats is done constantly.  To conduct adaptive analytics, data science, artificial intelligence, and machine learning are utilized to separate normal from abnormal communication patterns. This greatly helps in identifying malicious emails, phishing links, and attachments. An example would be intelligent threat analytics systems that offer threat streams. If an incoming IP instantly starts scanning the network endpoints, that is considered suspicious behavior. With the use of AI and machine learning, whenever an IP trips on behavior, the system will log it into the threat stream. Multiple vectors and patterns of malicious behavior are also observed when utilizing adaptive security.

Now that we know the gist of adaptive security and analytics, let us dig deeper into the best practices for adaptive threat protection.

Best practices for Adaptive Security

Responding to incidents after they have occurred results in loss of revenue and time. Take ransomware for example, which is a malicious attack that can leave a company’s data locked by anonymous cybercriminals, and the only way to retrieve it is by paying hefty amounts of bitcoins or ransomware in return. Due to the complex nature of cybercrimes, most companies only focus on a reactive approach and ignore the proactive threat management that can save them from a lot of headaches. Adaptive security brings a ray of hope for agile business environments by offering a proactive approach that traditional security services often lack.

An adaptive threat management system is composed of the following four layers:

Preventative: This is the top layer of an adaptive threat management infrastructure. Isolating security breaches right in their tracks is the main premise behind adaptive security techniques. By helping create preventative, counter-attacking techniques, and processes, adaptive security shields organizational data from being tampered with.

Detective: The job of the second or detective layer is to identify attacks that were not spotted by the preventative layer. Prompt and efficient response to possible threats is carried out to prevent them from turning into actual threats.

Retrospective: This layer goes a step above the detective layer by digging deeper into any potential attacks that might have been missed. This is carried out by using advanced threat analytics, threat logs, retrospective analysis, and observing all the forensic information to avoid future risks.

Predictive: Last but not the least, the predictive layer centers around monitoring external events, assessing risks, and anticipating attacks. Alerts are generated for any suspicious activity and are used to further supplement the detective and preventative layers.

Benefits of Adaptive Threat Protection

Cybercrimes are spiking at an all-time high and the security of any organization is always at stake both from internal and external factors. Adaptive threat intelligence provides real-time threat intelligence information regarding potentially malicious devices, emails, or any other form of communication. Here are some of the key benefits of adaptive threat protection:

Early Detection of security risks: Due to the preventative nature of adaptive security and analytics, 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.

Filtering and Prioritization of events: The implementation of adaptive security through advanced analytics and machine learning processes encourages the detection and filtration of ultra-complicated security breaches that would otherwise not be detected by a simple monitoring system alone.

Smaller Resolution Windows: The combination of manual and automated processes makes it easy to resolve issues seamlessly and in an expedited manner.

Multi-Level Monitoring System: Adaptive security is a multi-level monitoring approach and does not cater to any single or isolated entity. As such, this system evolves with threats. The more complex the threats get – the more sophisticated the adaptive security turns into.

Integration with other tools: A great benefit of adaptive security is the flexibility it offers in working with a myriad of security tools. It can also integrate with and adapt to any security system in place.

Conclusion

Adaptive and context-aware security takes threat management to the next level. By offering real-time network security monitoring and analytics, both perceived and real threats are kept at bay. The constant monitoring and instantaneous response times are guaranteed through automated processes and depending on the type of risks, automatic security measures are implemented and adapted. Robust security protection is a necessity due to the growing cyber threats and adaptive and context-aware threat management truly fits the bill. Fortunately, many organizations are setting the foundations for adaptive threat management. Exium’s Autonomous threat prevention approach is re-defining network and cloud security by helping enterprises tackle their security challenges head-on.