Not too long ago, the only technology available to security teams for attack prevention were host-based and network-based intrusion detection systems (HIDS and NIDS). Even today, intrusion detection systems are being leveraged by organizations and combined with antivirus and firewalls to combat threats.
But given today’s sophisticated threat landscape, these systems do not offer enough protection on their own.
Without the proper security tools at their disposal, organizations may find themselves in an unfavorable position of helplessness — unaware that they are under attack. The best answer to the question of “What is happening inside and outside our company’s IT infrastructure?” can only be found in log files.
Log management and monitoring are about much more than compliance or performance. In fact, log files are the key to gaining full coverage and seeing every possible exposure point for an organization.
This article will define and explain all the different log concepts and tools related to threat detection and security monitoring.
Security Information Event Management (SIEM) and log management may seem similar, but the two tools have developed distinct characteristics over time. One trait shared by both SIEM and log management is most obvious: logs. Whether it’s event logs, audit trails, or audit records, a log is a text-based record of everything occurring both in and out of an operating system (including a server, device, application, or endpoint).
While there are numerous differences between the two tools, the most prominent differentiator is that SIEM is tailored explicitly to cybersecurity while the purpose of log management is for non-security systems analysis and log collecting. If maintaining security is the priority, a SIEM is the right tool for the job.
Sure, a log management system could be somewhat helpful for security purposes, but the functionality is limited.
One other key distinction between the two systems is that the modern SIEM is automated and offers real-time threat analysis, while log management lacks those features.
The differences between log monitoring and security monitoring are similar to those mentioned above. But when it comes to monitoring, there are additional benefits to security monitoring.
With security monitoring, the software typically leverages security functionalities that include reporting, automated alerts, and visibility into critical activity. Security monitoring can also play an essential role in an organization’s incident response process.
Log monitoring also offers a single, centralized repository for all of an organization’s log data coming from many different systems to be managed and analyzed by an analyst. However, log monitoring lacks some of the more critical security features of security monitoring.
Log ingestion is a term that describes the process of uploading and formatting data from a wide variety of external sources — such as servers, cloud platforms and applications. Think of data ingestion like a stomach ingesting food.
For log ingestion, log data is either streamed in real-time or ingested in batches. With real-time data ingestion, every data item is imported from the source exactly as-is.
With batch ingestion, data items are split up to be imported in separate chunks. Then, they can be ingested at specific time periods.
Log ingestion represents one of the biggest challenges for organizations when it comes to log management due to data size and speed — not to mention the diverse format of data sources.
Did you know that a SIEM consists of three security tools in one single application? The functionalities of Security Event Management (SEM), Security Information Management (SIM) and Security Event Correlation (SEC) software are all found in today’s modern SIEM. While SIM, SEM, SIEM and SEC may be used interchangeably by some, they all carry out different functions.
Security Event Management (SEM) tools are most similar to log management systems. Like an LMS, SEMs aggregate log files from numerous hosts and systems. But instead of system admins, SEM tools are used primarily by security analysts.
Security Information Management (SIM) software tools collect, analyze, and monitor data from event logs. Typically, SIMs offer automation functions in the form of alerts that can be activated when specific events occur, indicating that a network or system is compromised. For security analysts, a SIM is a valuable tool for automating incident response, cutting down on false positives and gaining an accurate view of the company’s security posture.
Security Event Correlation (SEC) software serves one primary purpose: to inspect and analyze vast quantities of event logs. An SEC can recognize when a correlation or connection exists between events that might indicate a security issue or breach.
Modern SIEM tools combine the best of SEM, SIM and SEC — and leverage AI, machine learning and big data to streamline threat detection and incident response.
Yes, there is a significant difference between log analysis and log parsing.
The simplest way to describe the difference between log analysis and parsing is that analysis decodes hordes of data into something more understandable. In contrast, parsing splits data into more manageable chunks.
Here’s a more detailed explanation of both functionalities.
Log analysis is the process of translating computer-generated logs to provide a clear view of what is happening (or has happened) across an IT infrastructure. Log analysis allows organizations to reactively — and hopefully, proactively — gain visibility into risk mitigation, security and regulatory compliance, user behavior and threat prevention and detection.
Log analysis is typically a four-step process: collect, centralize and index, search and analyze, and monitor and alert.
Log analysis could be manual (i.e. a security practitioner reviewing log data) or automated (i.e. automated alerts looking for patterns).
Log parsing, as mentioned above, splits data into smaller chunks so that it can be manipulated and stored. Every log contains many fragments of text data, and parsing takes those chunks and groups them according to specific functions (such as grouping user ids).
Log parsing is typically a two-step process that involves allocation and population of data structure as well as execution.
It’s important to note that when we talk about SIEM in this context and comparison, we’re referring to traditional SIEM and not next-gen SIEM.
The key differentiator between a conventional SIEM and security analytics boils down to which approach a company takes for security: reactive or proactive. Traditional SIEM takes a more passive approach while security analytics champions a long-term, proactive approach to cyber security.
Security analytics offers more flexibility and can operate in conjunction with external threat intelligence tools and services. And unlike a traditional SIEM, security analytics leverages cloud-based infrastructure to take advantage of infinite data storage, scalability, and significantly reduced costs.
To get the benefits of all the serverless SIEM concepts mentioned above, Panther offers the proactive tools you need for threat prevention, detection, and response. With Panther, you can reduce SIEM costs dramatically while gaining lightning-fast query speeds with an efficient, highly scalable data lake architecture.
Detecting threats in real-time is a reality, as you can analyze logs as they are ingested, giving you the fastest possible time to detection. You’ll get answers quickly with the ability to run queries over terabytes of normalized log data in minutes — not hours or days.
Most importantly, with Panther, you can focus your efforts on security rather than infrastructure management with our zero ops, serverless architecture.
To learn more about how Panther can make security monitoring fast, flexible, and scalable for all security teams, book a demo with us.
