Analyzing credit card transactions using machine learning techniques – 2

Principal Component Analysis - Introduction and Data Preperation Principal Component Analysis [PCA] is an unsupervised algorithm which reduces dimensionality and is widely used. A good visual explanation can be found here: http://setosa.io/ev/principal-component-analysis/ As mentioned in our previous article, Correspondence Analysis  works exclusively on categorical data. In contrast, PCA accepts only numerical data. This means our data … Continue reading Analyzing credit card transactions using machine learning techniques – 2

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Analyzing credit card transactions using machine learning techniques

Introduction In this 3-part series we'll explore how three machine learning algorithms can help a hypothetical financial analyst explore a real data set of credit card transactions to quickly and easily infer relationships, anomalies and extract useful data. Data Set The data set we'll use in this hypothetical scenario is a real data set released … Continue reading Analyzing credit card transactions using machine learning techniques

Nugget Post: Reactive Functions to parse nested objects

Note this article assumes familiarity with the Observer Pattern / Reactive Programming as described here: http://reactivex.io/ Some APIs return complex nested JSON objects. For example, take this cleaned up sample response from ElasticSearch (which incidentally is used to build the "Data Table" visualization): https://gist.github.com/dvas0004/8f3427955a5bb21213c864d30094d072 Note the structure of the object. Within the top level "aggregations" object … Continue reading Nugget Post: Reactive Functions to parse nested objects

Lessons Learned: Winlogbeat & Forwarded Events – no event description

Scenario: Shipping Azure Cloud Logs to an Elasticsearch Cluster The Azure Log Service [AZLog ] audits events across your Azure Cloud infrastructure, and sends these to a central log collector. It leverage the Windows Event Forwarding subsystem to do this, meaning that the collector server will be able to view the AZLog alerts via the … Continue reading Lessons Learned: Winlogbeat & Forwarded Events – no event description

How to create a “heatmap” graph network visualization

What we're after @CyberSiftIO we've been going through an exercise of adding "confidence levels" to our visualizations. In other words, how confident is the CyberSift engine that an alert really is an anomaly/outlier? The above screenshot shows one of the ways we visualize the output from this exercise. Each blue node is an internal PC/Server, while … Continue reading How to create a “heatmap” graph network visualization

How we built the CyberSift Attack Map

Recently we launched a small site called the "CyberSift Attack Map" hosted at http://attack-map.cybersift.io. Any one involved in the InfoSec industry will be instantly familiar with the site:   It's basically a map of attacks which either trip some rule in a signature based IPS such as SNORT, or land in a honeypot. In this article we'll list … Continue reading How we built the CyberSift Attack Map

Super Simple React Native Redux Example

Inspired by http://blog.tylerbuchea.com/super-simple-react-redux-application-example/ In this article we explore the barest of solutions to get started with React Native + Redux. The only pre-requisite to the below is to have "create-react-native-app" installed (https://facebook.github.io/react-native/docs/getting-started.html) Setup create-react-native-app superSimple cd superSimple npm install --save redux react-redux redux.js https://gist.github.com/dvas0004/43f876637561ffba08f18a57c66a2ab3   App.js https://gist.github.com/dvas0004/b1d9d236661d2b77ebdc59774064ea27 Notes In most create-react-native-app + redux tutorials that I researched, … Continue reading Super Simple React Native Redux Example