Cyber security attacks can affect entire networks and domains, including endpoints, email, applications, and identities. This makes it important for your Security Operations Centre analysts to monitor and secure all your devices and entry points from being exploited. Endpoint threat detection and protection solutions in 2021 will normally come with a range of advanced capabilities, including behaviour-based detection, automation, machine learning (ML), and artificial intelligence (AI).

Real-time endpoint threat detection and diffusion

The right endpoint security system can detect threats before they actualise, providing comprehensive protection from the destruction caused by sophisticated malware and other evolving dangers. For example, a breach attack may start with something as small as downloading the wrong email attachment. Or it could begin with an attacker stealing user credentials to access and exploit your resources and data.

Real-time endpoint protection and detection can help you find and remediate such incidents before they inflict damage. A well-tuned endpoint detection and response (EDR) system continuously monitors and collects endpoint data backed up by rules-based automated response capabilities.

An endpoint protection system detects and investigates suspicious activities on hosts and endpoints, automating security services to detect and react to threats in real-time. This AI-powered function can also collect activity data from endpoints, analyse it to find possible threat patterns, and remove them immediately.

Continuous data analysis substantiates the incidence, providing useful information so analysts can implement a timely solution.

Behaviour-based endpoint threat detection

This proactive and multi-layered approach to security and protection monitors endpoint activity to identify anomalies in users’ behaviour.

A behaviour-based approach makes it easier to detect advanced threats such as ransomware, zero-day malware, and file-less malware. These issues are quite prevalent in and around endpoints where users access and store data, making them vulnerable to cyber-attacks. 

As distributed devices become the norm, you should consider implementing stringent security policies and taking a prevention-first approach to coordinate data flow between your network and endpoints. From an endpoint protection perspective, this denotes frequently validating the device’s owners, their location, what applications run on it, and the content it generates.

However, authentication is not always enough. We recommend safeguarding and protecting your endpoints from phishing attacks to reduce the chances of compromised endpoint security. Your endpoint protection strategy should include:

Monitoring endpoints to detect behavioural inconsistencies: Your endpoint protection strategy needs threat detection capabilities that track activities using analytics to uncover any unusual activity. It is also a good idea to deploy ML tools to augment detection accuracy.

Remember to include the remote VPN users and those on your physical network when endpoint monitoring. This should help you stay on top of your security specs even when you have remote workers regularly accessing your networks.

Next-generation prevention: It is paramount to protect your endpoints from unknown and known exploits, file-less, and malware attacks, blocking malicious actors before they attempt to infiltrate the network. Endpoint threat detection solutions can intuitively create additional barriers between cyber threats and your organisation’s sensitive data.

With the appropriate endpoint protection measures, you can understand changed access behaviours, inspect files and eradicate malware. You can also detect phishing activities to block script-based attacks and threats with a behaviour-based approach.

Automatic prevention and remediation of endpoint breaches

Cyber-attackers and other malicious actors have access to sophisticated methods to access unauthorised systems. Even security executives with extensive expertise find it challenging to recognise and proactively react to such attacks without robust automated tools.

Irrespective of how comprehensive your endpoint protection and detection is, the risk of breaches and cyber-attacks is inevitable. That is why we recommend having strong post-infection recovery and remediation capabilities for your company.

When you need to gauge such capabilities in an endpoint breach protection solution, consider automation. Automatic prevention helps you with rapid containment and remediation, effectively containing the after-effects of the attack while also giving you the ability to restore your data in seconds.

From an endpoint breaches perspective, automated identification and response capabilities can significantly minimise the consequences of an attack on endpoint devices in your organisation.

You have around 228 days to detect a data breach, while the containment time is eighty days on average, making up 308 days of a complete attack lifecycle. When the lifecycle extends more than 200 days, the average breach cost is $4.33M. Automation can significantly reduce the lifecycle and the total cost of data breaches.

With endpoint protection and detection, you can automatically and entirely remediate the cyber kill chain. Once your system detects an attack, you can isolate the infected device automatically to avoid adjacent infection movement and restore it to a safe state.

Machine learning for endpoint protection

As remote work becomes the new normal for many organisations, employees are the first line of defence for your business network. But it can be challenging to make them understand their role. Fresh cybersecurity challenges presented by the transition to hybrid and remote work arrangements exacerbate this problem.

How can a business with inadequate IT security resources cope with these developments?

First, you might secure your employee’s devices and consider the right tools for your technology stack to prevent endpoint threats. Some of the most stringent protective measures consist of cybersecurity defences collectively known as next-generation endpoint protection tools.

These endpoint protection technologies are advanced detection cybersecurity techniques that progressively leverage ML and AI to enhance safety.

Endpoint safety tools also leverage reliable signature-based detection along with new approaches, such as behavioural analysis, endpoint detection and response, predictive analysis, threat intelligence, and sandboxing.

This has the power to take your cybersecurity efforts to the next level; we recommend considering platforms that leverage ML and AI. The security tools help you prevent next-generation endpoint attacks, making it easier for IT security professionals to view the correct uses of applications or system capabilities.

As these AI-powered platforms ingest data following user behaviour anomalies, network traffic, and applications enable you to detect malicious activities.

ML tools for endpoint protection greatly help determine the extent of threats for small businesses with limited IT resources, saving you time and valuable resources.

All in all, when you leverage AI and ML to protect your endpoints, you can better monitor situations that demand your instant attention, so you can take action to address security vulnerabilities before an attacker exploits them. 

Endpoint threat detection and protection with CT

We offer a robust endpoint threat detection and protection solution that provides protection, scalability and flexibility. Our solution, CT EDR, delivers real-time endpoint protection for devices in a single platform with flexible deployment options and predictable costs.

Visit our Cyber Security page to learn more.