{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-9853988","patent":{"patent_number":"US-9853988","title":"Method and system for detecting threats using metadata vectors","assignee":null,"inventors":[],"filing_date":"2015-11-17T00:00:00.000Z","publication_date":"2017-12-26T00:00:00.000Z","cpc_codes":["H04L","G06F","G06F","G06F","H04L","H04L"],"num_claims":24,"abstract":"An approach for detecting network attacks using metadata vectors may initially involve receiving network communications or packets, extracting metadata items from the packets. The metadata items describe the communications without requiring deep content inspection of the data payload or contents. The communications may be clustered into groups using the metadata items. If a cluster exceeds a threshold, an alarm may be generated."},"analysis":{"summary":"The Method and System for Detecting Threats Using Metadata Vectors patent introduces an innovative approach to network security by analyzing metadata rather than relying on deep packet inspection. The core innovation lies in extracting key metadata items from network packets, clustering these items, and identifying anomalous patterns that may indicate malicious activity. This approach solves the problem of slow, resource-intensive threat detection methods that struggle to keep pace with evolving cyber threats. By focusing on metadata, the system can quickly analyze large volumes of network traffic and identify suspicious patterns without the need for deep content inspection. This technology offers significant business value by improving network security, reducing computational overhead, and enhancing threat detection accuracy. The market opportunity for this invention is substantial, as organizations worldwide seek more efficient and effective ways to protect their networks and data from cyberattacks. This patent represents a significant advancement in network security and has the potential to transform the way organizations approach threat detection and mitigation.","layman_explanation":"The Method and System for Detecting Threats Using Metadata Vectors patent addresses the growing need for more efficient and effective network security. Traditional methods of detecting threats often rely on examining the full content of network communications, a process called deep packet inspection. While effective, this approach is computationally intensive and can slow down network performance. Furthermore, it raises privacy concerns as it involves scrutinizing the actual data being transmitted.\n\nThis invention takes a different approach by focusing on metadata. Metadata is essentially data about data. In the context of network communications, it includes information such as the sender's and receiver's addresses, the size of the data packets, and the type of communication protocol being used. Think of it like looking at the envelope of a letter instead of reading the letter itself. By analyzing these metadata elements, the system can identify suspicious patterns and anomalies without needing to inspect the actual content of the communication.\n\nThis approach matters because it offers several significant advantages. First, it's much faster and less resource-intensive than deep packet inspection, allowing for real-time threat detection without slowing down network performance. Second, it's more scalable, meaning it can handle large volumes of network traffic without becoming overwhelmed. Third, it helps to protect privacy by avoiding the need to inspect the actual content of communications.\n\nLooking ahead, this technology has the potential to be integrated into a wide range of security solutions, from firewalls and intrusion detection systems to security information and event management (SIEM) platforms. As cyber threats continue to evolve and become more sophisticated, the need for efficient and scalable threat detection methods will only increase. This invention represents a significant step forward in addressing this challenge and offers a promising approach to enhancing network security.","technical_analysis":"The Method and System for Detecting Threats Using Metadata Vectors patent outlines a system that enhances network security by analyzing metadata instead of relying on deep packet inspection. The technical architecture involves several key components: a packet capture module, a metadata extraction module, a clustering module, and an anomaly detection module. The packet capture module intercepts network traffic and forwards it to the metadata extraction module. This module extracts key metadata items from the packets, such as source and destination IP addresses, port numbers, packet sizes, and protocol types. The clustering module then groups the network communications based on their metadata characteristics, using algorithms such as k-means or hierarchical clustering. The anomaly detection module identifies patterns that deviate significantly from normal network behavior, indicating potential malicious activity. The implementation details involve using programming languages such as Python or C++ for the core modules, and leveraging network analysis libraries such as Scapy or Wireshark. The system can be integrated with existing security solutions, such as intrusion detection systems (IDS) and security information and event management (SIEM) platforms, through APIs. The performance characteristics of the system are highly dependent on the efficiency of the clustering algorithm and the volume of network traffic. The system is designed to handle high-bandwidth networks by distributing the processing load across multiple servers. The code-level implications involve careful optimization of the metadata extraction and clustering algorithms to minimize latency and maximize throughput.","business_analysis":"The Method and System for Detecting Threats Using Metadata Vectors patent presents a significant business opportunity in the cybersecurity market. The market opportunity size is substantial, as organizations worldwide seek more efficient and effective ways to protect their networks and data from cyberattacks. The competitive advantages of this technology include improved threat detection accuracy, reduced computational overhead, and enhanced scalability. The revenue potential is significant, as the system can be sold as a standalone product or integrated into existing security solutions. The business models include licensing the technology to security vendors, offering subscription-based threat detection services, and providing consulting services to help organizations implement the system. The strategic positioning involves targeting organizations that require high-performance network security solutions, such as financial institutions, government agencies, and healthcare providers. The ROI projections are favorable, as the system can significantly reduce the cost of security breaches and improve the efficiency of security operations.","faqs":null,"topics":["network security","threat detection","metadata analysis","cybersecurity","intrusion detection","method","system","detecting"],"tech_cluster":null},"seo":{"title":"Method and System for Detecting Threats Using Metadata Vectors - Patent US-9853988","description":"Discover how this innovative system detects network threats using metadata vectors instead of deep packet inspection. Full patent analysis, claims, and technical details.","keywords":["network security","threat detection","metadata analysis","cybersecurity","intrusion detection","patent","patent US-9853988"]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-9853988","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-9853988","citation_suggestion":"Patentable. \"Method and system for detecting threats using metadata vectors\" (US-9853988). https://patentable.app/patents/US-9853988","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-9853988","json":"https://patentable.app/api/llm-context/US-9853988","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-30T10:30:25.604Z"}