DNIF is an open Analytics Platform that uses Deep-Tech to Auto-magically identify Outliers in users application and systems in general. DNIF connects the dots in High-velocity data lake to uncover scenarios that directly impact business thereby mitigating risks and increasing efficiency.
It combines the features of traditional software with advanced technologies such as security analytics, SOAR, UEBA and security data lake to bring power and efficiency to security operation centres of all sizes. It has one of the fastest response times in the industry and bridges the gap between searching, processing, analyzing and visualizing data.
DNIF offers solutions to the world’s most challenging cybersecurity problems.This next-generation analytics platform combines security and big data analytics to provide real-time threat detection and analytics to the most critical data assets on the Internet.
Shomiron Dasgupta is the CEO at DNIF. In an interaction with The Tech Pod, Shomiron speaks about the role of machine learning in cybersecurity companies. Read more!
Tell us something about yourself and what does your company do?
I am an intrusion analyst and extremely passionate about tech advancements which led me to build threat detection systems close to two decades. DNIF was founded in 2016 with a vision to create a company that delivers high-quality attack detection products and services to its customers. Today, DNIF has established partners in 14 countries across industries such as healthcare, insurance, transportation, banking and media.
Prior to founding DNIF, I was working with ICICI Infotech Ltd. as a senior consultant, where my core responsibility was to solve critical challenges faced by customers.
I am also a speaker at many industry events like TedX, DSCI (the Data Security Council of India) and SACON (the Security Architecture Conference). St. Xavier’s College is my almamater . Outside the tech world, I am a trained mountaineer, with expedition experience in the high Himalayas.
How does DNIF provide cybersecurity solutions to its clients by using analytical tools?
DNIF is a Big Data Analytics platform that helps customers identify potential threats by monitoring events across IT systems. We build various ML based analytics capabilities on the platform to detect threats.
How does the product extract information based on historical profiles and statistical analysis detect a threat?
The product collects data from various systems over time and can build historical profiles and analysis. This forms a key capability in threat detection. It allows DNIF to create a baseline of normal behaviour and based on this identify outliers or potentially malicious events.
How does DNIF bring out the unbounded potential to identify cases that have never been experienced before?
Building historical profiles provides DNIF the capability to understand events that can usually happen. Imagine a situation, when a visitor goes to a company’s office and plugs the network cable lying in the meeting room to his laptop to intrude the network. With DNIF, users are able to look at event logs from the network switch to create a list of people of people who usually visit the office (employees) and hence also identify devices which have never been plugged on the network. This in fact is one of the key differentiators of the platform where we are able to easily work with these scenarios and identify threats.
How does DNIF make use of machine data analytics?
The input data to DNIF is data generated by various IT Systems. The data generated can be from hardware devices like Firewalls, Proxy Servers, Network devices to softwares like Operating Systems, Antivirus, Databases or even applications like SAP, CRM etc. DNIF completely relies on machine-generated data and runs analytics on this to detect threats.