Network Spectral Encoding for Encrypted Traffic Threat Detection
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Solution Overview
Problem
Current network security technologies face challenges in real-time detection of malware and network threats, particularly with encrypted traffic, as existing methods like network web proxies and HTTPS key escrow impose significant operational overhead and are not scalable, and are often intrusive, limiting their deployment outside highly secure sites.
Innovation Solution
The approach involves encoding network traffic patterns into 'network spectrals' which are payload-neutral, allowing for real-time comparison against reference patterns, enabling fast identification of threats without decrypting traffic, using interval-bound traffic rate measurements, directionality, and metadata, with optional time-series compression for compact representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If network web proxies or HTTPS key escrow are used to detect threats in encrypted traffic, then threat detection capability is improved, but operational overhead and processing complexity increase significantly
Solution Approach 1:
The patent extracts only the essential traffic flow metadata (packet counts, byte counts, timing information) from the encrypted traffic without attempting to decrypt the payload content. This selective extraction of relevant features enables threat detection while avoiding the computational burden of decrypting and analyzing entire traffic streams, thus resolving the contradiction between detection capability and operational overhead
Solution Approach 2:
The patent segments the traffic analysis process into distinct components: flow metadata collection, spectral encoding, and pattern matching. By separating these functions and processing only the metadata layer rather than the full encrypted payload, the system achieves effective threat detection with reduced processing complexity and operational overhead
2Measurement precision
If real-time attack detection is implemented with full packet inspection, then detection accuracy is improved, but processing overhead and scalability deteriorate
Solution Approach 1:
The patent applies partial action by analyzing only the necessary portion of traffic data - specifically the flow metadata and timing characteristics - rather than performing complete packet inspection. This selective analysis maintains detection accuracy for threats that manifest in traffic patterns while preserving processing throughput by avoiding unnecessary decryption and payload analysis
Solution Approach 2:
The patent transforms traffic data into a different parameter space through spectral encoding, converting raw packet flows into frequency-domain representations. This parameter transformation enables efficient pattern recognition and maintains detection accuracy while significantly reducing the computational complexity compared to traditional deep packet inspection methods
3Reliability
If encrypted traffic is analyzed using traditional methods, then security protection is improved, but operational intrusiveness and deployment limitations increase
Solution Approach 1:
The patent introduces spectral encoding as an intermediary representation layer between the encrypted traffic and the analysis engine. This intermediary transformation allows security analysis to proceed on the encoded spectral features without requiring decryption of the original traffic, thereby maintaining security protection while enabling non-intrusive deployment in production environments
Data Source
AI summary
A method, apparatus and computer system to identify threats on a TCP/IP-based network. The approach leverages a set of reference patterns (or “network spectrals”) associated with one or more defined Indicators of Compromise (IoCs). At least one reference pattern is time-bounded and profiles a network traffic pattern using a set of session data (e.g., volume, direction, traffic metadata) that is payload-neutral and may be derived in part by time-series compression of at least one non-varying encoding interval. Network traffic data associated with a traffic pattern under test is received and encoded to generate a test spectral. A stream-based real-time comparison is performed to determine whether the test spectral matches against any of the reference spectrals. Responsive to identifying a match, a given remediation or mitigation action is then taken. A reference spectral may represent a bi- or multi-directional flow, and the multi-directional flow may involve multiple entities.