Vision and Innovation Drive Securonix’s Position On 2017 Gartner Magic Quadrant For SIEM

Ch 3 – Unsupervised Learning: Combining Security and Data Science

Authors: Securonix Labs Introduction Machine learning is a subfield of artificial intelligence within computer science which is concerned with the design and analysis of algorithms that allow a computer system to learn from data without being explicitly programmed. In other words, the objective of machine learning is to develop learning...

Cyber Incident Response: What Is It, And Why Do You Need It?

  With the data breaches that we have seen through the course of 2017 so far, one would imagine that incident response teams threw up their hands in defeat. The Equifax breach, with a compromise of over 140 million records of extremely sensitive private information on virtually every American that...

Ch 2 – Data Science: Statistics vs. Machine Learning

Authors: Securonix Labs Introduction Data science is a field that cuts across several technical disciplines including computer science, statistics, and applied mathematics. The goal of data science is to use scientific methods to extract valuable information from data. Advances in large-scale data storage and distributed computing have enabled us to...

What You Need To Know About Bad Rabbit Ransomware

Ransomware On The Rise With Bad Rabbit For about a week now, a new ransomware campaign has been sweeping across computers. This is the third major ransomware campaign after WannaCry and NotPetya this year. Securonix Threat Research Labs has been tracking this campaign since its inception (technical details here), and...

Securing Internet Connected Devices (IoT)

Our society is blazing towards automating what seems like every aspect of our lives –self-driving cars, home automation, wearable devices, entertainment, medicine, manufacturing, finance/payments, energy – no industry has managed to remain untouched by internet-connected sensors and actuators. However, this explosive adoption of online devices has far-reaching implications for the...

Ch 1 – SIEM 2.0: Why do you need security analytics?

Authors: Securonix Labs Current State of Data and Threats Today, we see organizations face extraordinary challenges related to the safety of their information. With a majority of it stored and transferred in digital form, there is an important need to secure this data. Different types of stored data include personal...

Data Science: A Comprehensive Look

There is a lot of hype, confusion and misinformation regarding the use of machine learning, data sciences and AI for advanced threat detection. While it is true that many security solution vendors across the various disciplines of security have incorporated elements of data sciences for security detection, complete explanation, and...

Securing Patient Data Privacy Using User & Entity Behavior Analytics

Healthcare organizations are aware of the extremely sensitive nature of, and consequently the importance of securing patient data. Hackers, on the other hand, are also well aware of the value of this PHI, including its monetary value. As such, they employ increasingly nefarious techniques in order to gain illegitimate access...