Operational controls are a must to protect an organization’s assets, data, and reputation. Broadly speaking, controls could be categorized into two types: those that are preventive in nature and those of detection type-a certain incidence is detected upon occurrence, and action is taken.
This posting explores various operational preventive and detective controls including firewalls; web application firewalls, or WAFs; sandboxing; endpoint security; continuous monitoring; threat intelligence; intrusion detection systems, or IDS; egress monitoring; security information and event management, or SIEM; user and entity behavior analytics, or UEBA; machine learning and AI-based tools; third-party security services; honeypots; and honeynets.
Firewalls: The First Line of Defense
Firewalls are some of the most basic preventive controls in cybersecurity. They form a barrier between trusted internal networks and untrusted external networks, filtering incoming and outgoing traffic based on predetermined security rules.
Real-World Example: Corporate Network Protection
Firewalls separate the internal network from outside threats. Firewalls block unauthorized access attempts and allow legitimate traffic. For instance, when a working employee tries to open any website that contains malware in it and which is reported too, such connectivity will be prevented by the firewall. This helps in saving organizational data.
Web Application Firewall: This is designed for the security of web applications.
A WAF is specifically designed to protect web applications by filtering and monitoring HTTP traffic between a web application and the Internet. WAFs help defend against common threats like SQL injection and cross-site scripting (XSS).
Scenario: Securing an E-Commerce Platform
An e-commerce company deploys WAFs to secure its online store from cyber threats. Due to a surge in shopping, WAF detects a pattern that seems out of place and signals a SQL injection hack intended to steal customer information. The WAF blocks such requests in real time to ensure customer information remains secure, allowing legitimate transactions to take place.
Sandboxing: Isolating Threats
As a prevention control, the aim of sandboxing would be the execution of untrusted code in an environment to study its behavior without causing any harm to the host system. Hence, this technique is helpful when viewing suspicious files or applications.
Example: Reviewing Suspicious Email Attachments
An organization receives an email with an attachment that has a suspicious look. Before allowing it to interact with their systems, the IT department opens the attachment in a sandboxing solution. The analysis identifies the attachment as malware crafted to leak information. Due to sandboxing, the organization just avoided a potential breach.
Endpoint Security: Protecting Devices
Endpoint security will mean the security of the laptops, desktops, and mobile devices that connect to the corporate network. This is a very critical control, as usually in operations, this is where the attack is directly pointed. Scenario: Implementation of Endpoint Protection Solutions
Example:
A health-care organization installs endpoint protection software on all employee endpoints. If a user tries to download unauthorized software that could introduce vulnerabilities, the endpoint protection solution would block the action and alert IT staff. The result is to proactively help stay in compliance with regulations around health care while protecting sensitive patient data.
Continuous Monitoring: Proactive Threat Detection
Continuous monitoring refers to the regular inspection of systems and networks for signs of suspicious activity or vulnerabilities. In such ways, organizations are endowed with the capability to discover potential threats in real time.
Example: Network Traffic Monitoring
A financial organization deploys continuous monitoring network tools that analyze traffic patterns for anomalies. Once the unusual outbound traffic is detected by the monitoring system, alerts are automatically triggered for investigation by the security team.
Threat Intelligence: Staying a Step Ahead of Threats
Threat intelligence is generally defined as the collection and analysis of data regarding current or emerging threats that may have an adverse impact on an organization. As a proactive control, threat intelligence allows organizations to prepare for attacks, perhaps before they occur.
Scenario: Using Threat Intelligence Feeds
This would be the case with an IT security team that subscribes to threat intelligence feeds for updates on emerging vulnerabilities and attack vectors. On receiving information about a new ransomware variant targeting businesses in their industry, recommended patches and preventive measures would quickly be implemented to mitigate this risk.
Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS)
Intrusion Detection Systems monitor network traffic for suspicious activities, whereas Intrusion Prevention Systems proactively block detected threats by using a set of predefined rules.
Example: Network Intrusion Detection
A university deploys both IDS and IPS solutions on the university network. The IDS detects unusual login attempts from multiple locations for a single account-a symptom of a brute-force attack-and sends an alert to the administrators. The IPS then automatically blocks these IP addresses to prevent unauthorized access.
Egress Monitoring: Data Flow Control Out
Egress monitoring monitors traffic from an organization’s network to the outside, checking that no sensitive data accidentally or intentionally leaks outside, and unauthorized transmission of sensitive data does not take place.
Scenario: Data Exfiltration Prevention
A technology company deploys egress monitoring tools that scan each outgoing e-mail for patterns of sensitive data, such as credit card numbers or personally identifiable information. When an employee tries to send an e-mail with sensitive customer information outside the organization without proper encryption, the system catches it and requires that the e-mail be reviewed prior to sending.
SIEM: Security Information and Event Management
SIEM solutions aggregate security-related data from an organization’s infrastructure in real time and analyze it for the detection of anomalies to allow incident response.
Example: Centralized Security Monitoring
A large enterprise deploys the SIEM software solution to centralize logs from servers, firewalls, and endpoints. Upon detecting multiple failed login attempts followed by a successful login from a strange location, SIEM generates an alert for further investigation by the security team.
User and Entity Behaviour Analytics
User and Entity Behaviour Analytics solutions monitor the organisations’ internal users and entities by creating a baseline of their normal behavior, through machine learning algorithms. The deviations from this shall flag some security incidents.
Scenario: Insider Threat Detection
This would be in the instance when the retail company has deployed UEBA technology to monitor the patterns of employee access. If an employee, for example, accesses sensitive financial records outside of their usual working hours-a deviation from their established behavior-the system automatically notifies the security team for further investigation.
Machine Learning and AI-Based Tools: Enhancement in Security Measures
Machine learning and artificial intelligence are being integrated with cybersecurity applications, detecting threats much more satisfactorily by analyzing large volumes of data for patterns of attacks.
Example: Automate Threat Detection
A cybersecurity company deploys the use of AI-powered solutions to monitor past attack data and networks in near-time. AI quickly detects up-and-coming threats that could not have been possible with traditional methods, thus enabling quick responses to potential breaches.
Third-Party Provided Security Services
Organizations depend on third-party security services to provide a certain level of specialized expertise and resources that organizations cannot accomplish in-house. These services range from MSSPs to cloud-based security solutions.
Scenario: Engaging MSSPs for Enhanced Protection
Because a small business is often too short of staff, it may outsource the management of its cybersecurity to a managed security service provider. It would provide 24×7 network traffic monitoring, incident response, and periodic vulnerability testing, considerably enhancing its security posture with limited in-house expertise.
Honeypots and Honeynets: Deceptive Security Controls
Honeypots are decoy systems that are put out to attract an attacker, while honeynets are networks of honeypots emulating real environments. Both these become significant tools in gathering intelligence from the attack methodologies without exposing real assets.
Example: Learning from Attack Patterns
It sets up honeypots within the network infrastructure of the organization. Any time attackers attempt to exploit such decoys, their methods will be logged for analysis. Such information helps improve defensive measures across real systems of an organization by understanding how the attacker operates.
Conclusion
In-depth security controls include both operational preventive and detective controls that form part of an all-rounded cybersecurity strategy. These would encompass firewalls, WAFs, sandboxing solutions, endpoint protection, continuous monitoring systems, threat intelligence platforms, IDS/IPS technologies, egress monitoring tools, SIEM systems, UEBA solutions, machine learning tools, third-party services, honeypots, and honeynets. Such controls applied in depth can effectively safeguard assets from evolving cyber threats while facilitating timely detection and response.