Enhancing Visibility Through Advanced Security Data Analytics.

An average enterprise can generate 10,000 security events each day. That same enterprise can generate billions of log events a day. Security big data analytics coupled with data analysts allows a security operations team to detect a security event without becoming overwhelmed by the sheer volume of logs.

Security Analytics

Security Analytics (SA) utilizes the data and capabilities of Big Data Analytic platforms built specifically to capture security logs and events. These platforms—often known as Security Data Lakes (SDL)—centralize data otherwise siloed within separate security products. By using advanced statistical and data management techniques, Alȳn analysts and Data Scientists correlate events across the organization and identify existing vulnerabilities, undetected cyber threats and help predict future risks to the enterprise.

The Big Data Challenge

The tools and expertise required to return value from a big data platform are different than those used by typical security analysts or by cyber threat intelligence analysts. This skills gap can impede an organization’s ability to implement a Security Data Lake (SDL) and create value from the platform. And in some cases, this gap can lead to the abandonment of the SDL platform in favor of the less effective but familiar siloed security products, wasting the organization’s investment in the big data security solution.

What Sets Us Apart

Alȳn, Inc. bridges the skill gap by providing security analytic and data management expertise, enabling organizations to ramp up and drive value from a big data security platform. Using our experience with big data tools such as python and pyspark and our knowledge of security data assets, Alȳn Data Scientists develop analyses based on an organization’s top priorities. The analyses include:

  • Analyzing user patterns and network traffic to detect suspicious behavior
  • Identifying compromised accounts and improper account usage
  • Conducting root cause analyses of incidents using security data assets to understand why incidents occur
  • Investigating fraudulent behavior across the organization

In addition to developing analyses, Alȳn Data Scientists will mentor your organization’s analysts. By sharing coding tips and best practices in using big data tools, Alȳn empowers your organization’s employees to use the big data security platform effectively, equipping them to develop and create their own analyses. Alȳn’s engagement will jump start the customer’s analytic development by using their SDL and ensuring the customer benefits from the platform in the future.