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Machine learning for cybersecurity: only as effective as your implementation

We recently launched Elastic Security, combining the threat hunting and analytics tools from Elastic SIEM with the prevention and response features of Elastic Endpoint Security. This combined solution focuses on detecting and flexibly responding to security threats, with machine learning providing core capabilities for real-time protections, detections, and interactive hunting. But why are machine learning tools so important in information security? How is machine learning being applied?

Dear Search Guard users #2, including Amazon Elasticsearch Service and Open Distro, and others

Back on September 4th, we filed a lawsuit against floragunn GmbH, the makers of Search Guard, a security plugin for Elasticsearch and Kibana, for a multi-year pattern of copying our proprietary code. After filing the claim, we have continued to investigate floragunn’s actions. Today, we have updated our lawsuit in two important ways. First, we have identified additional copying by floragunn with respect to the separate, proprietary code base for our Kibana product.

Preventing and mitigating data loss with Graylog

If you’re handling sensitive information, dealing with data loss can be more than just a headache. Log management tools such as Graylog can enhance your incident response and management strategies, and help you mitigate the damage when a breach occurs in your database. Minimizing data loss with a fast and scalable logging solution is key if you want to bring your cybersecurity to the next level.

What Is MTTF? Mean Time to Failure Explained in Detail

“What is MTTF?” That’s the question we’ll answer with today’s post. Yep, the article’s title makes it evident that the acronym stands for “mean time to failure.” But that, on its own, doesn’t say anything. What does “mean time to failure” actually mean? Why should you care? That’s what today’s post covers in detail.

Announcing the General Availability of LogDNA Screens

LogDNA is known and loved by developers for our lightning fast live tail and search. With some users ingesting over a petabyte of data per day, our users want to be able to visualize their data and put it to use. You told us what analytics you value most and we’ve taken the first step to providing them within the LogDNA product. The first is having highly interactive graphs. Graphs allow you to analyze patterns and trends by navigating through your data over a period of time.

Shipping Office 365 audit logs to Graylog with O365beat

O365beat is an exceptionally useful open-source log shipping tool created by counteractive. With a few simple tweaks, it can be used to fetch Office 365 audit logs from the Office 365 Management Activity API and forward them to Graylog. The best part of this tool is that it leverages all the flexibility and power of the beats platforms such as libbeat.

Super-Size Your Log Searches

At SolarWinds® Papertrail™, we know that when you’re combing through lines and lines of long event messages, every pixel matters. That’s why in the new Papertrail event viewer, we introduced the ability to hide the application chrome. Hiding the application chrome, or ‘presentation mode,’ removes the header and navigation menus and maximizes your screen real estate. So far the feedback on this new option has been great.

IBM Expands IBM Cloud Paks Offering with LogDNA

IBM recently announced an expanded Cloud Paks offering with LogDNA. With this offering, developers and engineering teams can easily aggregate and search huge volumes of data from any source to gain real-time insights on their applications. LogDNA is now offered by IBM and deployable on-premise or multi-cloud with all IBM Cloud Paks including Cloud Pak for Applications, Cloud Pak for Data, Cloud Pak for Integration, Cloud Pak for Multi-cloud Management, and Cloud Pak for Automation.

A Breakdown of Language Analyzers for Elasticsearch

Any search engine needs to be be able to parse language. As the field of natural language processing (NLP) has grown, specific text analysis has been applied to stop words and tokenizing (or marking) them by part of speech. In Elasticsearch (and elsewhere), the most attention has been paid to English, although the ELK stack has built-in support for 34 languages as of this writing.