LogicHub SIEM Introduction

Analyzes events and sends out alerts to notify security staff of immediate issues, 
either by email, other types of messaging, or via security dashboards.

Creates visualizations to allow staff to review event data,
see patterns and identify activity that does not conform to standard patterns.

Automates the gathering of compliance data, producing reports that adapt to security, 
sgovernance and auditing processes for standards like HIPAA, PCI/DSS, HITECH, SOX and GDPR.

Stores long-term historical data to enable analysis, tracking, and data for compliance requirements. 
Especially important in forensic investigations, which happen after the fact.

Allows security staff to run queries on SIEM data, filter and pivot the data, 
to proactively uncover threats or vulnerabilities.

Provides case management, collaboration and knowledge sharing around security incidents, 
allowing security teams to quickly synchronize on the essential data and respond to a threat.

Integrates with other security solutions using APIs, and lets security staff define automated 
playbooks and workflows that should be executed in response to specific incidents.

Most SIEM systems collect data by deploying collection agents on end-user devices, 
servers, network equipment, or other security systems like firewalls and antivirus, 
or via protocols syslog forwarding, SNMP or WMI. Advanced SIEMs can integrate with cloud 
services to obtain log data about cloud-deployed infrastructure or SaaS applications, 
and can easily ingest other non-standard data sources.

Pre-processing may happen at edge collectors, with only some of the events and 
event data passed to centralized storage.

Traditionally, SIEMs relied on storage deployed in the data center, which made it 
difficult to store and manage large data volumes.

As a result, only some log data was retained. Next-generation SIEMs are built on top of 
modern data lake technology such as Amazon S3 or Hadoop, allowing nearly unlimited 
scalability of storage at low cost. This makes it possible to retain and analyze 100% of
log data across even more platforms and systems.

The SIEM allows security staff to define profiles, specifying how enterprise systems 
behave under normal conditions.

They can then set rules and thresholds to define what type of anomaly is considered a 
security incident. Increasingly, SIEMs leverage machine learning and automated 
behavioral profiling to automatically detect anomalies, and dynamically define rules on 
the data, to discover security events that require investigation.

The central purpose of a SIEM is to pull together all the data and allow correlation of 
logs and events across all organizational systems.

An error message on a server can be correlated with a connection blocked on a firewall, 
and a wrong password attempted on an enterprise portal. Multiple data points are combined 
into meaningful security events, and delivered to analysts by notifications or dashboards. 
Next-gen SIEMs are getting better and better at learning what is a “real” security event 
that warrants attention.

SIEMs help with real-time monitoring of organizational systems for security incidents.

A SIEM provides a unique perspective on security incidents, because it has access to 
multiple data sources – for example, it can combine alerts from an IDS with information 
from an antivirus product. It helps security teams identify security incidents that no 
individual security tool can see, and helps them focus on alerts from security tools that 
have special significance.

SIEMs can help detect, mitigate and prevent advanced threats, including:

* Malicious insiders – A SIEM can use browser forensics, network data, authentication 
and other data to identify insiders planning or carrying out an attack.
* Data exfiltration (sensitive data illicitly transferred outside the organization) – A SIEM 
can pick up data transfers that are abnormal in their size, frequency or payload.
* Outside entities, including advanced persistent threats (APTs) – A SIEM 
can detect early warning signals indicating that an outside entity is carrying out 
a focused attack or long-term campaign against the organization.

SIEMs can help security analysts determine that a security incident is taking place, 
triage the event and define immediate steps for remediation.

Even if an incident is known to security staff, it takes time to collect data to fully 
understand the attack and stop it – the SIEM can automatically collect this data and 
significantly reduce response time. When security staff discover a historic breach or 
security incident that needs to be investigated, SIEMs provide rich forensic data to 
help uncover the kill chain, threat actors and mitigation.

SIEMs can help organizations prove to auditors and regulators that they have the 
proper safeguards in place and that security incidents are known and contained.

Many early adopters of SIEMs used it for this purpose – aggregating log data from 
across the organization and presenting it in audit-ready format. Modern SIEMs 
automatically provide the monitoring and reporting necessary to meet standards like 
HIPAA, PCI/DSS, SOX, FERPA and HITECH.