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Cybersecurity analysts in government organizations are inundated with vast amounts of security data, making it challenging to keep pace with the growing number of cyber threats, vulnerabilities, and required mitigations. Lazarus AI’s ATLS provides a solution that has demonstrated correlation, analysis and fusion of over 500,000 individual data points, resulting in a 141,000% increase in analysis speed compared to manual methods while maintaining the same high level of accuracy.
Cybersecurity analysts in government organizations are inundated with vast amounts of security data, making it challenging to keep pace with the growing number of cyber threats, vulnerabilities, and required mitigations. The Department of Defense has sought a $1 billion increase to the cybersecurity budget to $14.5 billion. This increase is up from FY23s budget of $11.2 billion. This case study will explore the challenges the Department of Defense faces when addressing cybersecurity and will provide a suggested solution, a brief background of a cybersecurity use case, the analysis of the data provided to solve the challenge, and a proposed solution using Lazarus AI capabilities for this specific use case.
Cybersecurity in the Department of Defense faces many of the same threats any commercial organization faces. Moreover, defense faces significant challenges in maintaining a manual process for cybersecurity posture management due to the rapidly evolving threat landscape and increasing complexity of IT environments. Manual approaches to assessing and improving security posture are becoming increasingly inadequate and risky in today's cybersecurity climate. Recent studies have shown that automating IT processes can reduce workloads up to 25%. That reduced workload can enable efficient use of personnel and resources.
Evolving threats across the globe from independent and nation state actors continue to increase. The specific threats laid out below identify the need for the Department of Defense to rapidly respond:
Addressing these issues requires a comprehensive approach involving government agencies, private sector organizations, and individuals to strengthen cyber defenses and build resilience against evolving threats.
Lazarus AI’s ATLS provides a solution that has demonstrated correlation, analysis and fusion of over 500,000 individual data points, resulting in a 141,000% increase in analysis speed compared to manual methods while maintaining the same high level of accuracy. ATLS efficiently ingested and processed data from diverse sources, including network logs, threat intelligence feeds, and security incident reports. This enhanced data fusion enables faster detection and response to cyber threats. Its advanced analytics capabilities empower organizations with proactive threat hunting, streamlined incident investigation, and deeper threat analysis, ultimately bolstering the cybersecurity posture of critical government networks and infrastructures.
ATLS not only improved operational efficiency but also provided real-time insights to ensure that government agencies stay ahead of evolving cyber threats.
To maximize the effectiveness of cybersecurity measures and safeguard national interests, the following strategies are recommended for implementing ATLS.
The primary goal is to ensure that relevant personnel across Law Enforcement Organizations (LEO) and the Department of Defense (DoD) are fully equipped to adopt the system. To achieve this, comprehensive staff training programs should be implemented, focusing on ATLS' unique features and capabilities. These initiatives aim to increase user proficiency, ensuring that the benefits of the system are fully realized. Additionally, to facilitate a smooth integration process, dedicated IT support teams should be assigned to address any technical challenges that may arise during the adoption phase.
For successful long-term utilization, it is essential to incorporate ATLS into existing workflows and ensure compatibility with current operational systems. Customization of the platform according to the specific needs of different departments will ensure user engagement and optimization of the platform's capabilities.
Given the sensitive nature of the data processed by ATLS, robust security protocols must be prioritized. Safeguarding measures such as encryption and access restriction are recommended to ensure that the system remains secure and compliant with relevant data protection regulations. Furthermore, regular security audits and updates will be crucial to maintaining the robustness of cybersecurity defenses.
Lastly, to encourage user engagement and expedite issue resolution, technical support channels should be established. These could take the form of dedicated online forums or direct communication lines, enabling swift assistance and continuous improvement of the platform based on user feedback.
These strategic recommendations, in conjunction with the implementation of ATLS, will empower analysts and law enforcement personnel to leverage advanced artificial intelligence (AI) tools, enhancing their ability to safeguard national security.
The Department of Defense and supporting agencies face a challenge in manually identifying and responding to cybersecurity threats due to the nature of the threat vectors outlined in the case study above. Lazarus AI can provide a 140,000% increase in efficiency via automated solutions enabling operators to identify and react to those threats in real-time using the Automated Tactical Learning System (ATLS). This increased efficiency will provide cost savings to the DoD’s cybersecurity request of more than $14 billion over the next fiscal year.