Attacks by threat actors and nation-states against government targets increased by nearly 95% in the last half of 2022 and jumped again by more than 40% in the first half of 2023.
Yet, with more than 30,000 cybersecurity incidents reported to the DHS United States Computer Emergency Readiness Team (US-CERT) annually, most government entities have failed to fully address cybersecurity holistically.
A December 2023 GAO report highlighted a significant obstacle in effectively dealing with cyber incidents. After reviewing a broad section of government agencies' cybersecurity practices, it noted that 20 agencies had yet to meet federal requirements for investigation and remediation. The Office of Management and Budget (OMB) required agencies to reach level 3 compliance by August 2023, which included logging at all critical levels. As of the date, however, just three of the 23 agencies studied had met the requirements.
“Until the agencies implement all event logging requirements, the federal government’s ability to fully detect, investigate, and remediate cyber threats will be constrained.” – GAO Report: Federal Agencies Made Progress, but Need to Fully Implement Incident Response Requirements.
What prevented these agencies from deploying the required cybersecurity measures to identify and respond to cyber incidents? According to the GAO:
- Lack of staff
- Event logging technical challenges
- Limitations in Cyber threat information sharing
Using Data Analytics to Detect Security Incidents Earlier
With an ever-expanding number of endpoints, proliferation of systems across cloud, and legacy systems, monitoring and managing cybersecurity is challenging. Security teams need the tools and expertise to isolate and respond effectively to potential threats.
Comprehensive logging of network activity, system events, and endpoint data provides the foundation for leveraging data analytics to detect potential security incidents faster. Analysts can establish baselines for normal behavior across users, devices, applications, and networks by collecting and aggregating logs into a central repository. Utilizing statistical analysis, artificial intelligence, and machine learning methodologies aids in detecting deviations from typical patterns of activity. Instances such as unexpected surges in outbound network traffic, unfamiliar user login locations, familiar users’ odd time of login, or abnormal CPU usage on endpoints serve as indicative signals.
Data analytics models can search log data for known attack patterns, tactics, techniques, and procedures adversary groups use. Alerting security teams about potential breaches and Indicators of Compromise (IOC) enables quicker responses, avoiding the need to wait for attacks to unfold entirely. This is crucial, especially given the alarming fact that, on average, it takes up to 207 days to identify a breach and an additional 70 days to contain it, as reported by IBM. Allowing threat actors to linger within systems for such extended periods poses a significant risk and further increases the breach’s impact.
Breaches never get better with age.
Security information and event management (SIEM) solutions can help aggregate and analyze log data to detect potential incidents.
Making Data Science a Core Element of Cybersecurity Incident Response
Leveraging logs and data analytics fuels faster incident investigation. Correlating threat intelligence on current campaigns with unusual security events helps connect the dots. Analysts can then pivot through this data to accurately determine the initial entry point of compromise, total scope impacted, specific assets affected, and the intention behind the attack.
Identifying every system touched, command executed, and network segment compromised is key to understanding the severity and containing breaches. Analyzing the attack’s TTPs (tactics, techniques, and procedures) aids in classifying the adversary and their campaign.
Leveraging Data to Analyze IOCs
Analyzing IOCs is the first step in understanding an attack’s nature and scope. Analysts sift through logs, network traffic, and system artifacts to identify and correlate IOCs. Pattern recognition, anomaly detection, and correlation analysis help identify attack vectors and trace the attack’s origin.
Isolating Impacted Resources
It’s crucial to isolate attacks quickly to prevent further damage. Containment and isolation fall into two categories: short-term and long-term.
- Short-term containment isolates threats. For example, you might need to segment an area of your network to take a service offline.
- Long-term containment strategies can come once the threat has been eliminated, such as applying additional access controls to unaffected systems and ensuring clean, patched systems and resources are created for the recovery phase.
Assessing Attack Patterns on Remaining Assets
As part of the isolating attacks, you must also assess the potential impact on other assets. Data analytics can help uncover similar indicators throughout your infrastructure to help detect and mitigate potential threats while preventing further compromise.
Performing Forensic Analysis and Impact Analysis
Forensic and impact analysis help fully understand the sequence of events that led to a breach and uncover the attacker’s tactics, techniques, and procedures (TTPs). This helps create a roadmap for network remediation and identify areas where stronger security protocols are needed.
Leveraging AI Tools
Analysts need a systematic approach to data that leverages AI and ML to sort and prioritize incidents that demand urgent response. Security orchestration, automation, and response (SOAR) platforms incorporate AI/ML for alert prioritization.
Configuring these tools properly can significantly reduce false positives. A significant challenge for digital forensics and incident response (DFIR) teams has been alert fatigue. With increased attack signals and a never-ending list of items to checkout, it’s no surprise that 83% of analysts say they are struggling to cope with the volume of alerts and data. More than half of security teams report burnout on the job — an increase of 50% from 2022. AI tools can help prioritize high-level incidents that demand immediate response.
Continuous Data-driven Improvements
Cybersecurity is an ongoing process, and data also plays a role in your post-incident analysis. By evaluating metrics like response time and containment effectiveness, organizations gain the insights needed to improve their cybersecurity strategies proactively. Using standards like NIST Cybersecurity Frameworks or MITRE ATT&CK as benchmarks allows for pinpointing areas where tools, policies, and response playbooks can be improved for better response.
The Importance of Having a Robust IR Plan
A well-designed and data-driven incident response plan ensures the identification, containment, and resolution of security incidents. Data analysis plays a central role and delivers significant benefits. A robust IR plan will:
- Minimize downtime
- Minimize data and financial loss
- Identify the impact and take corrective measures
- Identify the root cause of attacks and prevent similar attacks
- Restore operational to normal
Trust i-Link Solutions for Proactive Cybersecurity Consulting and Risk Mitigation
i-Link Solutions provides industry-leading IT consultation services for federal government agencies, including cybersecurity. We understand the unique needs of the federal sector and the importance of protecting critical data and infrastructure. By augmenting your cybersecurity efforts and staffing, we can provide IT support services to meet and exceed federal requirements.
i-Link Solutions is a trusted, proactive, and reliable partner in cybersecurity for:
Contact the cybersecurity experts at i-Link Solutions today to discuss your cybersecurity needs.
Harness Data Analytics for Enhanced Cybersecurity Incident Response: Unlock the Power of Data for Stronger Defense.
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