Adlumin Announces New Sensor for the IBM i Platform

Adlumin has announced a new sensor for the IBM i platform, the latest addition to its core banking monitoring suite. This new addition will help to expand customers’ access to and understanding of their network within the platform.

Adlumin provides a security and compliance automation platform built for corporate organizations that demand innovative cybersecurity solutions and easy-to-use, comprehensive reporting tools.

The IBM i sensor collects all relevant logs from core banking platforms and alerts users in real-time to threats, malfunctions and IT operations failures on the most mission-critical assets.

Core banking systems are connected to various bank services and the complexity of the interfaces can present opportunities for malicious actors to inflict massive financial damages. These platforms represent a financial institution’s central nervous system and store high-value data that are at constant risk of attack or failure.

“The addition of the IBM i sensor offers our customers complete network monitoring coverage including endpoints, servers, network devices, third-party software integrations and core banking platforms,” explained Dan McQuade, director of application development at Adlumin. “Our goal is to provide customers with a complete view of what is happening inside their network.”

The company specially developed the software to have a minimal footprint, with low resource utilization and no impact on overall system performance. Working in conjunction with the Adlumin Collector virtual machine, the sensor can deploy onto systems without internet connectivity.

Alongside the new sensor, Adlumin built an IBM log model that identifies incoming logs based on two factors: how rare or anomalous a log is and whether the log is indicative of any threats, malfunctions, or IT operations failures.

“Building this IBM model within the platform was a critical part of our process. The model establishes the anomalous character of a log by comparing incoming logs to log templates that the model compiled during training,” said Mahkah Wu, lead data scientist at Adlumin.

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