As cyber threats are becoming increasingly sophisticated, the protection of digital infrastructure has never been more critical. In an era where data underpins every government service, decision, and interaction, stringent protection measures are essential to safeguard this strategic asset.
To effectively safeguard data and its underlying infrastructure, leveraging innovations such as Search AI becomes essential. Search AI combines the power of artificial intelligence (AI) with the precision of search to give agencies the actionable, mission-critical answers they need in real time, using all their data, at scale. This capability allows agencies to monitor their entire attack surface and detect potential threats within seconds. When public-sector organizations integrate tools and techniques such as data mesh, vector databases, and zero-trust architectures, they can create a resilient and adaptive defense strategy. This ensures data remains secure, accessible, and effectively managed, enhancing the overall cybersecurity posture of local governments.
Cyberattacks on state and local governments continue to rise. In spring 2024, Kansas City faced multiple cyberattacks, including a ransomware attack on the Jackson County Assessment, Collection, and Recorder of Deeds, and attacks on the Kansas City Area Transit Authority and Kansas State court system. In May 2024, Macon-Bibb County, a suburb of Atlanta, experienced a similar attack, just a week after a comparable incident in Wichita, Kansas.
The Potential of AI-driven Security Analytics
Many security operations centers (SOCs) have thousands of cybersecurity notifications to sift through daily, and cybersecurity analysts suffer from alert fatigue. Integrating AI-driven security analytics with automation, attack discovery, and auto-import capabilities into core SOC workflows can make every user a “power user,” boosting efficiency and reducing the strain on human analysts. For example, an attack discovery function can filter through hundreds of alerts in minutes, not days, prioritizing the attacks that need attention so security teams can better understand them and take immediate follow-up actions.
An automatic-import data capability can speed up labor-intensive SecOps tasks, such as transitioning from legacy to new security information and event management (SIEM) tools, by automating the creation of custom data integrations. Security teams require comprehensive visibility across the entire attack surface and access to extensive, actionable archives — capabilities that outdated SIEM tools lack.
The Role of Data Mesh
A data mesh approach can further enhance the security and efficiency of data management in government agencies. By decentralizing data ownership and enabling cross-functional teams to manage their own data domains, data mesh allows data to be searched, analyzed, and used in its original location. This approach aligns well with the principles of zero-trust architecture (ZTA), as it promotes granular access control and continuous monitoring. Ultimately, adopting a data-mesh architecture empowers state and local governments to enhance data accessibility, streamline operations, and adopt a culture of data-driven decision-making across all levels of governance.
Accurate Data Retrieval: Vector Databases
Vector databases, which are optimized for handling high-dimensional data, can significantly improve the performance of Search AI technologies. These databases enable faster and more accurate data retrieval, which is crucial for real-time threat detection and response. Vector databases enhance the ability to recognize complex patterns and anomalies in data. This is vital for identifying sophisticated cyber threats that might otherwise go unnoticed. By integrating vector databases, agencies can enhance their ability to analyze complex datasets, identify patterns, and predict potential cyber threats.
Unified Data and Zero-Trust Architecture
To ensure strong cyber defenses, government agencies must adopt a zero-trust cybersecurity framework. The zero-trust architecture operates on the principle of “Never Trust, Always Verify,” ensuring that every access request is authenticated and authorized based on all available data points, such as user identity, location, device health, and data classification. Users are granted just enough access to perform their tasks, reducing the risk of data exposure. Moreover, by segmenting networks and requiring end-to-end encryption, ZTA minimizes the impact of any unauthorized access.
A unified data layer is indispensable for ZTA. For a ZTA to be effective, all of an agency’s data needs to be observable, available, and correlatable within a unified data plane. It’s the linchpin that holds together the various elements of ZTA, ensuring seamless integration and operation. This common data layer is not just a technical requirement; it’s a strategic asset that enables public-sector agencies to adhere to federal mandates and guidelines.
A unified data platform serves multiple functions within a ZTA framework:
- Facilitates zero-trust policy decisions
- Enables centralized monitoring and reporting
- Supports validation and cross-correlation of access decisions
Without a search AI-based data platform, each zero-trust tool risks becoming yet another isolated data silo, complicating the work of analysts and potentially leading to fragile, custom integrations between tools.
Faster, More Resilient Response
By prioritizing data protection and leveraging the analytic capabilities of Search AI, state and local government agencies can enhance their cybersecurity posture, making it more robust and resilient against evolving threats. This integration not only helps in preventing attacks but also ensures a faster and more efficient response when incidents occur. Moreover, this approach ensures the safeguarding of citizen data and the continuous functioning of our digital infrastructure — which is essential for the well-being and prosperity of our society.
Mr. Harmon leads the Elastic US Public Sector Cyber Solutions business for Department of Defense, US Intelligence Community, Federal Law Enforcement, Civilian Agency, State, Local, and Education customers. He has spent the past 21 years in the US Intelligence Community as a SIGINT analyst, cyber capabilities developer, technical team lead, and federal leader in cyber security. He is also an adjunct professor at Georgetown University, where he teaches Cybersecurity Strategy.
From 2015 to 2019, Mr. Harmon was the VP – Federal at Endgame, leading its federal sales team. He was a Partner at Tactical Network Solutions (TNS) from 2009 to 2015 and led TNS federal and commercial business development, sales, capture, recruiting, and teaming efforts.
From 2002 to 2009, Mr. Harmon was a Global Network Exploitation Analyst at the National Security Agency, receiving six awards during his time there, including a Deckert/Foster Engineering Award. He earned a Master of Science in Network Security from Capitol College and a Bachelor of Science in Management Information Systems from Auburn University.
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