In this section of the course,
we are going to discuss Secure Architecture Design.
The Secure Architecture Design section of the course
focuses on Domain 2: Security Architecture,
specifically objective 2.3,
which states that given a scenario,
you must be able to integrate controls
in the design of secure architecture.
Designing a secure architecture
includes safeguarding sensitive data
throughout its lifecycle
and ensuring that security controls
are tailored to the needs
of both internal and external environments.
Additionally, effective architectures
account for the complexities of diverse infrastructures
while continuously assessing and mitigating potential risks
to reduce exposure to threats.
As we go through this section,
we will cover many topics
related to Secure Architecture Design,
including Data States,
Data Classification, Data Labeling and Tagging,
Data Loss Prevention, Hybrid Infrastructures,
Third-party Integrations, Attack Surface Management,
and Control Effectiveness.
First, we will look at Data States.
Data states are the different conditions
in which data exists.
Specifically, data can be at rest,
in transit, or in use.
Each data state requires distinct methods of protection.
For example, Data at rest,
that is, data being stored on a hard drive or in a database,
is protected through encryption and access control.
Whereas Data in transit,
that is, data which is actively moving between systems
through a network,
is protected with encryption protocols,
such as Transport Layer Security or TLS.
Finally, Data in use,
which is data that is actively being processed
by an application or system,
is protected with secure processing environments.
Next, we will explore Data Classification.
Data classification is the process
of organizing data into categories
based on its sensitivity, value,
or in response to regulatory requirements.
A data's classification
determines the level of security controls
and handling procedures that will be applied to it.
Data classification models
are frameworks or methodologies used to categorize data
into levels or types based on sensitivity.
Classification models use categories such as public,
internal, confidential, and restricted.
Each level dictates the security measures required
to protect the data.
For example, a healthcare organization's patient records
might be classified as "Restricted."
The "Restricted" classification makes it clear
that the data requires encryption
and strict access controls
to comply with the Health Insurance Portability
and Accountability Act or HIPAA.
Conversely, the healthcare organization's
internal training documents
may only be classified as "Internal Use Only."
This classification indicates
the level of protection is lower,
and more people within the organization
can have access to it.
After that, we'll look at Data Labeling and Tagging.
Data labeling and tagging involves assigning markers
to the data to indicate its classification, sensitivity,
or handling requirements.
Labeling and tagging
ensures proper data management and protection.
Data labels include classifications,
such as "confidential," or "public,"
which direct how the data should be handled and protected.
Data tagging adds metadata,
such as project names
and department associations to the data,
which enables automated processes like data loss prevention.
For example, a company might label a document
as "Confidential," and tag it with "Finance"
and "Sarbanes-Oxley (or SOX) Compliance."
This ensures that only authorized
finance department employees can access it,
and it identifies the data as governed
by the Sarbanes-Oxley Act (or SOX) regulatory requirements.
Next, we will explore Data Loss Prevention.
Data loss prevention is used to detect, prevent,
and respond to unauthorized access, transmission,
or use of sensitive data.
Data loss prevention concepts include data discovery,
managing data at rest, and in transit,
and policy enforcement.
Let's take a moment
to describe each of these in more detail.
Data discovery is the process of identifying
and locating sensitive data
within an organization's infrastructure.
Whether the data is at rest and stored in databases
and file systems,
or the data is in transit
and actively moving across the network,
it is important to know where the data is at any given time.
Once identified, data loss prevention policies
can be enforced.
Data loss prevention policies
include actions such as alerting administrators,
blocking unauthorized transfer,
and quarantining sensitive files
that have attempted to be moved.
It also includes applying tombstone markers
to announce policy violations to the user.
In all cases, the process of data loss prevention
begins with data classification,
data labeling, and data tagging.
Following that, we will look at Hybrid Infrastructures.
Hybrid infrastructures refer to environments
that combine on-premises systems with cloud-based resources.
This type of infrastructure
requires integrated security measures
across both on-premises systems and cloud-based resources.
This means extending traditional security controls
like firewalls, encryption,
and access management
from the local data center to the cloud.
In hybrid infrastructures,
security challenges may arise
from differences in infrastructure management and control.
It may require policies and tools
that can enforce security consistently
across multiple environments.
For example, a company might store sensitive data
on-premises for regulatory purposes
while using cloud-based applications
for data and client processing.
This infrastructure
would require secure communication channels
and coordinated security policies
to ensure data remains protected,
regardless of where it is stored or processed.
Then, we will explore Third-party Integration.
Third-party integrations
involve securely connecting external services
or applications to an organization's internal systems,
often by using Application Programming Interfaces or APIs.
Application Programming Interface Communication
involves data encryption to protect sensitive information
during transmission and storage.
Additionally, data protection measures
and monitoring must be extended
to include third-party services.
This ensures that security controls,
such as access management and encryption,
are effectively applied.
Finally, monitoring and logging
are used to track interactions with third-party systems,
detect anomalies,
and ensure compliance with security policies.
For example, an organization
might integrate a third-party payment processor
via an application programming interface,
which will require encrypted data transmission,
strict access controls,
and real-time monitoring
to ensure that financial transactions are secure
and comply with regulations.
After that, we will look at Attack Surface Management.
Attack surface management involves identifying, reducing,
and continuously monitoring
all potential paths of attack into a system's architecture.
This minimizes exposure to security threats.
Let's quickly discuss a few concepts
that relate directly to attack surface management.
First, we have hardening.
Hardening is the process of securing systems
by reducing their attack surface,
in part, by disabling unnecessary services
and applying up-to-date security patches.
Next, defense-in-depth implements multiple security controls
such as firewalls, intrusion detection systems,
and access controls,
to provide redundant protections against attack.
Then, vulnerability management can be used
to regularly scan and address network
and asset security weaknesses,
including those in legacy components
that may no longer receive updates,
but are still a critical part
of the enterprise infrastructure.
Finally, we will explore Control Effectiveness.
Control effectiveness refers to the degree
to which security controls mitigate risks
and protect assets.
Control effectiveness concepts
include metrics, scanning, and assessments.
Metrics are quantitative measures
used to evaluate the performance
and impact of security controls.
They provide insights into areas
like incident response times
or the number of vulnerabilities that have been mitigated.
Scanning involves using tools to detect vulnerabilities
or misconfigurations within the system.
This allows the vulnerabilities to be prioritized
for remediation.
Assessments involve an evaluation
of security controls through audits, penetration testing,
or compliance checks,
which ensure that controls are functioning as intended
and identifying any areas for improvement.
To finish things off, we'll take a short quiz
to see what you learned during this section of the course,
and we will review each of those quiz questions fully
to ensure you can explain why the right answers were right
and the wrong answers were wrong.
So, let's get ready to dive into Security Architecture
in this section of the course!