New and more complex cyber security threats continue to emerge, year after year.

In response, cyber security companies continue to improve the technologies required to detect and eliminate these threats.

While there are some threats that cyber security services battle continuously like phishing scams and ransomware, the emergence of newer, smarter threats keeps the need for developing better cyber security defense technologies such as those listed below at the forefront of the fight.

Cloud Encryption

As cloud use expands, so does the need for cloud cyber security using encryption.

Cloud encryption protects cloud servers by encrypting stored data, then requiring an encryption code from an authorized user to download and unencrypt the data.

Blockchain

Blockchain is a security method used by cyber security companies to store chunks of data in multiple databases across multiple servers.

Without the key to access and reassemble those packets of data, they are inaccessible and unusable.

Blockchain offers improved privacy and eliminates the effects of human error, while also eliminating the need for third-party verification.

Behavioral Analytics

Behavioral analytics is a technology used by cyber security services which analyzes the way websites, devices, and applications are used by an individual and/or organization in order to detect irregular patterns.

Used as a means of providing cybersecurity, behavioral analytics can detect potential security breaches, shut down current breaches, and prevent future ones based on what is considered normal and abnormal use.

Zero Trust Security

The next step in the “trust but verify” approach for cyber security, zero trust technology simply requires every person attempting to access data to verify themselves every time.

There is no trust given to any user, whether an insider or outsider, resulting in the higher overall protection of all data.

Defensive AI Security

To combat the usage of artificial intelligence in an offensive manner to gain access to networks, cyber security companies can also use it in a defensive manner to prevent those attacks.

Defensive AI can detect deep fakes and false personas, stop other AI from testing or learning network functions and strengthen algorithms so they are harder to hack.

Context-Aware Security

Similar to defensive AI, context-aware security determines authorization by analyzing more than just the standard yes/no questions that typical security features ask.

Instead, it assesses context such as user location, time, URL recognition and trustworthiness, and other ways to identify specific authorized users.

Extended Detection and Response

Developed as a more capable version of security endpoint detection, extended detection and response or XCR monitors multiple locations such as endpoints, cloud services, and networks to get a more thorough look at how data is being accessed and used.

Cyber security services can use XDR to detect and respond to targeted attacks, confirm alerts, and automate repetitive detection tasks to reduce current and future data breaches across an entire network.

Manufacturer Usage Description

Useful with IoT devices, manufacturer usage description or MUD is an embedded security feature that allows manufacturers to set specific access standards for each device, controlling access according to a context-aware access policy.

MUD security protects network devices against DDOS attacks and other security issues.

Helping Businesses Stay Ahead of Cyber Threats

The world of cyber security is constantly evolving in the ongoing fight to control cyber threats.

Though cyber security companies continue to rely on tried and true security basics, the need to adopt newer security technologies as they are developed is ever-present.

Businesses investing in cyber security services that continuously implement the most current technologies will have the upper hand in protecting their data from current and future threats.