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Boosting cybersecurity with continuous authentication

Boosting cybersecurity with continuous authentication
 

By Gaurav Sharma, Director of Operations at Chetu

Enhanced biometrics continues its tradition as a cutting-edge and versatile resource to optimize security and streamline processes. Fortune Business Insights has globally valued the burgeoning biometrics market at $30 billion.

Cybersecurity is critical to protecting digital assets, valuable data, and the functionality of all industries. IBM reported that the global average data breach cost is $4.45 million. This chilling statistic prompted cybersecurity experts to optimize biometric security processes with continuous authentication. Further, the process utilizes modern machine learning resources to strengthen cybersecurity with a validation process that monitors the end-user throughout an access session, not just initially confirming the user’s identity.

Machine learning propels continuous authentication

Machine learning (ML) enables unprecedented insight into patterns and end-user behavior. With the ability to automate processes, ML becomes a powerful and versatile resource designed to modernize operations. Its application within authentication and biometrics enables a “smarter” strategy for strengthening cybersecurity because by studying end-user behavior patterns, such as how a resource is being used, duration of operation, schedules, and functions performed, machine learning quickly establishes a user profile. It monitors data to confirm identity, making cybersecurity and authentication more comprehensive because several data points and parameters are studied instead of traditional authentication methods that rely on data inputs from verified and connected devices, such as cell phones.

The versatility of ML makes it an ideal resource to modernize industries further and optimize authentication processes. Its ability to rapidly and accurately process large volumes of data proves invaluable when used to study how end-users utilize hardware and software, expediting the process of accurately identifying anomalies that could pose cybersecurity threats. ML enables heightened intelligence by providing personnel with greater real-time data insights, mitigating laborious manual assessments of system performance and security.

Machine learning has earned its place as an unprecedented new benchmark for technology. ML can deploy automation to eliminate repetitive tasks and provide 24/7 cybersecurity and continuous authentication to companies requiring stricter security protocols.

Modernizing authentication: enhancements bring unprecedented security

Technology’s transformative impact on business always goes heralded, but we often overlook its critical role in security. Authentication has steadily evolved to counter the rise of cyberattacks that have the power to not only disrupt business operations but also stymie progress and cause irreparable financial consequences.

The journey of authentication began when end-users were required to design and enter unique passwords meeting the criteria to gain access, initially lauded as a new process to protect hardware from misuse while limiting access to data. In retrospect, this process appears more than dated, but it did pave the way for today’s enhancements, which we may take for granted.

The following outlines the evolution of authentication processes:

Salted Hash

Experts created this in response to password storing in plaintext files that were easily hacked. Hashing takes plaintext data and converts them into ciphertext outputs used for data verification. Salting adds random characters to data to confuse hackers.

Asymmetric Cryptology

End users enter passwords that are automatically encrypted by the server, enabling quick access but thwarting unauthorized use by deeply disguising passwords.

One-Time Passwords

Generating new, unique passwords for every use.

Public Key Infrastructure

The deployment of built-in system certificates managing passwords and data that end-users must read and then enter passwords that track access and how systems are used.

Multi-Factor Authentication and Single-Sign-On

Connected devices to servers and hardware are messaged with singular, unique codes that end-users must manually input to confirm identity and gain access to systems.

Biometrics became the modern standard for cybersecurity and authentication because of its unprecedented use of unique, physical-based traits of end-users that were required to gain access. Fingerprint capture and iris scanning offered unparalleled performance and accuracy to ensure all assets were protected and the correct end-user was seeking access.

Continuous authentication: forefront of security

Continuous authentication builds upon the evolution of biometrics, but incorporating powerful algorithms driven by machine learning puts it at the forefront of modernized authentication security.

Continuous authentication distinguishes itself as a modern solution for cybersecurity because it does not rely on an initial security hurdle to clear. The powerful algorithms monitor and report how an end-user interacts with hardware, identifying user behavior and patterns nuances, recording what sites are used and how data is accessed, quickly creating a user profile, and alerting officials to deviations or unusual patterns.

Enhanced authentication provides an elevated protocol performance and another layer of protection and safeguarding of digital assets. Cybersecurity and IT officials are augmented with continuous authentication and can deploy this cutting-edge resource remotely and in real time. As cybercriminal activity has dramatically risen, industries can successfully counter these efforts with continuous authentication driven by machine learning.

About the author

Gaurav Sharma is a Director of Operations at Chetu, a software solutions and support services provider, overseeing Chetu’s Biometrics, Artificial Intelligence, and Cybersecurity portfolios. With a proven track record of leading successful teams and projects, Gaurav has driven innovation in many industries for more than a decade. He has established himself as a prominent technology industry leader and an AI development and implementation expert.

DISCLAIMER: Biometric Update’s Industry Insights are submitted content. The views expressed in this post are that of the author, and don’t necessarily reflect the views of Biometric Update.

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