INTERNET-DRAFT                                           R. Bouziane
Intended status: Standards Track                         SecRoot.io
Expires: December 26, 2025                               June 26, 2025


       OODA-HTTP: Adaptive Security Framework
              for HTTP Communications
          draft-secroot-ooda-http-01


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Abstract

This document defines OODA-HTTP, a protocol extension and adaptive
security framework that applies the Observe-Orient-Decide-Act loop to
HTTP/HTTPS communications. OODA-HTTP introduces dynamic behavior at the
application layer, enabling real-time detection, decision, and mitigation
based on evolving threat contexts. Each HTTP request becomes not just a
message, but an observation signal, a decision vector, and a defensive
act. This framework introduces headers such as X-OODA-Action to carry
contextual scores or actions across clients, servers, and intermediaries.
OODA-HTTP transforms passive transport into active self-defense, offering
resilience against classic and quantum threats. It is designed as a native
defender of the World Wide Web \[Gupta23]\[Martinez22]\[Wang21]\[Kim23].

1. Introduction
Strategic Positioning Note

In warfare, if we do not have the same weapons, we do not even consider 
engaging. We remain passive.This is the current reality: the HTTP protocol, 
even when secured via TLS (HTTPS), remains passive in the face of 
next-generation threats — especially automated intelligent agents.

OODA-HTTP introduces a paradigm shift. It transforms HTTP from a passive 
transport protocol into an active defensive actor, capable of observing, 
orienting, deciding, and acting in context — a necessary evolution in 
the age of automated attacks.

   HTTP and HTTPS communications face increasingly sophisticated
   threats, including quantum computing-based attacks such as those
   leveraging Shor's algorithm. OODA-HTTP introduces a real-time
   adaptive security mechanism based on the OODA loop (Observe-Orient-
   Decide-Act) to enhance resilience. The framework leverages adaptive
   security paradigms demonstrated in enterprise networks \[Wang21],
   cryptographic key rotation in TLS \[Gupta23], and intrusion detection
   methodologies using OODA principles \[Martinez22].

   Traditional HTTPS treats security as a static, pre-negotiated layer,
   focused on encryption, authentication, and transport integrity. It
   lacks the ability to adapt to runtime behavior or evolving threat
   conditions during a session. OODA-HTTP fills this gap by enabling
   context-aware decision loops and dynamic protocol responses.

   This capability can also benefit application-layer components.
   Client-side applications may interpret OODA-HTTP signals to adjust
   their behavior in real time. Suspicious sessions can trigger
   interface restrictions, challenges, or warnings, enabling proactive
   defense at the user interaction layer.

2. Terminology

   The following terms are used throughout this document:

   OODA Loop:
   A decision-making model consisting of four sequential phases:
   Observe, Orient, Decide, and Act. Originally developed for military
   strategy, it is applied here to network communications.

   Threat Score:
   A numeric or categorical indicator representing the risk level
   associated with a session, request, or identity. It can be computed
   locally or distributed, and may evolve over time.

   X-OODA-Action:
   A custom HTTP header used to transmit OODA-driven decisions or
   scores between entities (clients, servers, intermediaries).

   Post-Quantum Cryptography:
   Cryptographic algorithms designed to resist attacks from quantum
   computers. Mentioned in this draft in relation to resilience
   against Shor's algorithm.

   Shor's Algorithm:
   A quantum algorithm \[Shor94] capable of factoring large integers
   exponentially faster than classical algorithms, posing a threat
   to widely-used public-key cryptosystems.

   Contextual Adaptation:
   The ability of an endpoint or middleware to adjust its behavior
   based on environmental, behavioral, or risk-related context.

   Self-Defending Protocol:
   A protocol that is capable of taking real-time protective actions
   based on observed conditions, without requiring external triggers.

3. Architectural Overview

   OODA-HTTP introduces a modular security architecture that integrates
   decision-making capabilities into existing HTTP and HTTPS infrastructures.
   The architecture is composed of four key components that operate along
   the OODA loop: telemetry collection (Observe), threat analysis (Orient),
   decision engines (Decide), and enforcement mechanisms (Act).

   The framework can be deployed at various levels: client applications,
   web servers, reverse proxies, smart edge routers, CDN nodes, or security
   middleware. It does not replace existing TLS or HTTP protocols but extends
   them by introducing headers and context-aware evaluation.

   A central concept in the architecture is the notion of local or distributed
   threat scores. These scores guide decisions that may be enforced via the
   X-OODA-Action header or other configured policies. The system may operate
   in standalone mode or integrate with machine learning models for adaptive
   behavior.

   The following sections describe how each phase of the OODA loop is
   implemented within this architecture.

4. OODA-HTTP Phases

   OODA-HTTP applies the four phases of the Observe-Orient-Decide-Act
   (OODA) loop to HTTP communications. Each phase is mapped to
   technical operations that collectively enable adaptive security
   in real time.

4.1. Observe

The Observe phase consists of collecting telemetry data from HTTP
requests, TLS handshake metadata, timing information, user-agent
patterns, and behavioral signals. This data may be extracted by
edge devices, proxies, or endpoints and stored locally or streamed
to a threat evaluation engine.

4.2. Orient

In the Orient phase, collected data is contextualized and interpreted
using rule-based logic or machine learning models. Features may
include request frequency, signature anomalies, protocol violations,
or correlation with known attack patterns. This phase results in
assigning a threat score to the current session or request.

4.3. Decide

Based on the threat score and predefined security policies, the Decide
phase selects an appropriate mitigation strategy. The decision may
include allowing, delaying, challenging, throttling, or blocking the
request. Optionally, the decision can be embedded into the request
via the X-OODA-Action header for downstream enforcement.

4.4. Act

The Act phase enforces the decision selected in the previous phase.
This may include applying rate limits, returning captchas, rotating
TLS keys, logging events, or updating dynamic filters. The act phase
may also emit metadata that becomes observable in future requests,
enabling feedback loops.

5. Message Formats and Protocol

   OODA-HTTP introduces protocol-level extensions for transmitting
   threat context and decisions using HTTP headers and JSON-based
   structures.

   The primary extension is the X-OODA-Action header, which carries a
   compact JSON object encoding the outcome of the Orient and Decide
   phases.

   Example format:

   X-OODA-Action: {
   "score": 72,
   "category": "suspicious",
   "action": "challenge",
   "timestamp": "2025-06-28T15:42:10Z"
   }

   Fields:

   * score (integer): A numeric threat score (e.g., 0–100).
   * category (string): A textual label for the threat level
     (e.g., "normal", "suspicious", "malicious").
   * action (string): Suggested enforcement action (e.g., "allow",
     "block", "challenge", "throttle").
   * timestamp (string): ISO 8601 UTC timestamp of the decision.

   Servers, clients, or intermediaries such as edge devices or security
   gateways may consume this header and apply local policies accordingly. The header is optional and may
   be stripped or overwritten depending on policy scope and trust
   boundaries.

6. Threat Models and Detection

   Un paquet peut tout changer.
   OODA-HTTP transforms each request into an opportunity for defense,
   analysis, and adaptation.

   OODA-HTTP is designed to detect and mitigate a broad range of
   threats, spanning classical, behavioral, and quantum-enabled
   attacks. The threat model includes both protocol-level and
   application-level vectors, and supports both static and adaptive
   detection methods.

6.1. Classical Threats

These include traditional attacks such as:

* Denial of Service (DoS) and Distributed DoS (DDoS)
* Slowloris and application-layer flooding
* Bot impersonation and session replay
* Payload manipulation and malformed headers

6.2. Behavioral Threats

These cover attacks identified via patterns of behavior, including:

* Unusual request rates or frequency spikes
* Time-based anomalies (e.g., bursts, silent intervals)
* Identity inconsistency or rotating user agents
* Suspicious navigation or incomplete flows

6.3. Quantum-Adaptive Threats

OODA-HTTP anticipates emerging post-quantum scenarios, such as:

* Precursor attacks preparing for future quantum decryptions
* TLS handshake manipulation to record and break sessions later
* Exploitation of weak randomness or low entropy in key negotiation
* Threats leveraging Shor’s algorithm \[Shor94] to factor captured
  session keys from classical cryptosystems

Adaptive defenses can preemptively respond by applying key
rotations \[Gupta23], adjusting handshake profiles, or introducing
entropy-hardening techniques.

7. Applications: Case Studies and Practical Validations

   OODA-HTTP has been evaluated across simulated and real-world
   environments to validate its adaptability and effectiveness.
   The following use cases highlight its potential in operational
   deployments.

7.1. Burst Attack Detection in CDN Edge Routers

OODA-HTTP deployed on CDN edge nodes enabled the early detection
of short-duration, high-intensity traffic bursts aimed at exhausting
caching layers. By integrating local telemetry and threat scoring,
edge routers adapted QoS and activated throttling rules dynamically.

7.2. Slowloris Mitigation in Reverse Proxies

In reverse proxy deployments, OODA-HTTP successfully identified
slow request patterns through timing and header irregularities,
triggering `X-OODA-Action: block` to terminate low-rate attacks
before reaching backend applications.

7.3. Bot Detection in Application Gateways

Application-layer integrations combined behavioral scoring and
fingerprint rotation detection. OODA-HTTP headers propagated
context to frontend gateways, where requests flagged as "malicious"
were challenged or dropped.

7.4. Post-Quantum Resilience Simulation

A TLS testbed integrated OODA-HTTP to react to low-entropy handshakes
and detect clients using weak key negotiation. Upon scoring these
sessions as high-risk, the system enforced real-time key rotation
\[Gupta23] and triggered entropy hardening for subsequent sessions.

7.5. Frontend Integration with Reactive Applications

In client-side environments such as single-page applications, OODA-HTTP
enables dynamic UI adjustments based on the threat context. For example,
an application may read the X-OODA-Action header from server responses
and respond accordingly:

* If action = "challenge", trigger a CAPTCHA or 2FA prompt.
* If category = "suspicious", restrict certain UI interactions.
* If score > threshold, log session metadata or notify the user.

This integration supports self-defending application logic, where
frontend components become adaptive actors within the OODA loop.
Security is no longer passive but embedded into user-facing flows.

OODA-HTTP is the first protocol where the user interface,
HTTP transport, and adaptive security speak the same language.

8. Integration with TLS/HTTPS

   OODA-HTTP is designed to complement and extend existing TLS and HTTPS
   infrastructures without breaking compatibility. It operates at the
   application layer while observing and interacting with the TLS stack
   through termination proxies, inspection agents, or endpoints.

   The protocol can integrate with TLS in the following ways:

   * Observing handshake metadata such as cipher suite selection,
     handshake timing, and session reuse patterns.

   * Reacting to entropy metrics or randomness sources used in key
     negotiation to detect low-entropy or anomalous handshakes.

   * Coordinating key rotation triggers based on observed threat
     thresholds \[Gupta23], especially in environments preparing for
     post-quantum resilience.

   * Tagging TLS sessions with contextual scores or identifiers via
     out-of-band headers, shared memory, or internal metadata systems.

   OODA-HTTP does not alter the TLS protocol itself but enhances its
   observability and adaptive response capabilities from the HTTP layer.

9. Protocol Engineering Foundations

   OODA-HTTP is grounded in classic protocol engineering principles,
   including modularity, state-awareness, error handling, and feedback
   loops. It leverages established design techniques to ensure resilience
   and extensibility across HTTP/TLS infrastructures.

   The protocol supports the following foundational characteristics:

   * State-driven logic: Each phase of the OODA loop transitions
     deterministically based on observable input.

   * Extensibility: Headers such as X-OODA-Action are optional and can
     evolve independently of core protocol semantics.

   * Backward compatibility: OODA-HTTP does not modify HTTP or TLS
     wire formats, ensuring that legacy systems can interoperate without
     disruption.

   * Fault tolerance: If any OODA component fails or becomes unreachable,
     systems default to standard HTTP behavior, maintaining service
     continuity.

   * Measurability: All actions and scores are loggable, audit-friendly,
     and interpretable by external observers.

   These principles align with long-standing guidance in protocol
   architecture and testing methodologies \[Sar93].

10. Security Considerations

Unlike purely defensive frameworks, OODA-HTTP is both a protocol
and a security engine, embedded directly into HTTP interactions.

OODA-HTTP introduces new information flows through headers and
decision logic. The following considerations apply:

* Confidentiality: OODA-HTTP headers such as X-OODA-Action may
  reveal threat assessment details or system behavior. These headers
  should not be exposed across trust boundaries unless encrypted
  or filtered.

* Integrity: Decisions derived from threat scores should be protected
  against tampering. Systems must ensure that OODA headers cannot be
  forged or overwritten by untrusted intermediaries.

* Fallback safety: If OODA-HTTP components are disabled or unavailable,
  systems should gracefully default to standard HTTP/TLS behavior to
  maintain availability.

* Score manipulation: Care must be taken to avoid creating exploitable
  feedback loops or incentives for malicious actors to influence threat
  scores through adversarial behavior. However, attempted score
  manipulation may itself serve as a signal of systemic vulnerability,
  revealing weaknesses in session-level security or orchestration flow.

* Human supervision: Automated decisions must be auditable and, where
  appropriate, overrideable by human operators, especially in sensitive
  applications.

Implementations should ensure secure defaults, minimize information
leakage, and respect separation of concerns between detection,
decision, and enforcement layers.

11. IANA Considerations

This document registers a new HTTP header field under the "Permanent
Message Header Field Names" registry maintained by IANA.

Header Field Name: X-OODA-Action
Applicable Protocol: HTTP
Status: Provisional
Author/Change Controller: IETF
Specification Document: This document

No new TLS parameters or ALPN identifiers are requested at this time.
Future versions may introduce identifiers for deeper protocol-level
integration.
12. Vector Engine and Temporal Memory
OODA-HTTP introduces a semantic vector engine that transforms each 
request into a multi-dimensional observation vector. This engine 
supports temporal memory, pattern accumulation, and learning-based 
refinement, enabling the protocol to mature over time.

12.1. Observation Vectors
During the Observe phase, each HTTP interaction is converted into
 a structured vector containing metadata fields such as:

TLS fingerprint: cipher suite, handshake entropy, session reuse

HTTP metadata: method, headers, frequency, burst timing

Client behavior: agent string variability, navigation flow, interaction
 latency Environment: IP locality, ASN, device type

These vectors are timestamped and stored in short- or long-term memory 
modules.

12.2. Orientation Space and Semantic Patterns
The Orient phase processes these vectors using rule-based 
classification or ML inference models. Similar vectors are grouped and
 compared across:
Known attack patterns (e.g., slowloris, botnets, smart agents)
Session anomalies (e.g., inconsistent headers, entropy irregularities)
Behavioral deviations from normative baselines

The system learns correlations over time, allowing it to recognize 
increasingly complex or obfuscated threats.

12.3. Temporal Threat Memory
Unlike static HTTP/HTTPS stacks, OODA-HTTP maintains an evolving threat
memory:

Short-term memory detects bursts, replay attempts, and adaptive scanning.

Long-term memory builds threat reputation for agents, sessions, or IP zones.

This memory enables cross-request correlation, historical fingerprinting, 
and context-based threat anticipation.

12.4. Maturity Through Activity
As OODA-HTTP observes more traffic, it becomes more effective. Each 
request strengthens its adaptive models, building resilience without 
explicit retraining. This contrasts with traditional HTTP/HTTPS 
protocols, which remain blind to behavioral evolution.

OODA-HTTP becomes smarter, faster, and more precise the more it is 
used—turning activity into capability.


13. References
13.1. Normative References
[Sarikaya19] B. Sarikaya, "Adaptive Security in Wireless Networks:
A QoS Perspective," IEEE Communications Surveys & Tutorials, 2019.

[Sar93] B. Sarikaya, "Principles of Protocol Engineering and Protocol
Testing," Ellis Horwood, 1993.

13.2. Informative References
[Gupta23] S. Gupta et al., "Automatic Key Rotation for TLS Sessions
to Mitigate Quantum Threats," IEEE INFOCOM, 2023.

[Kim23] J. Kim et al., "Real-Time QoS and Security Adaptation in
Software-Defined Networking," ACM SIGCOMM, 2023.

[Martinez22] L. Martinez et al., "Applying the OODA Loop to Intrusion
Detection: A Case Study," USENIX Security Symposium, 2022.

[Wang21] D. Wang et al., "Implementation and Evaluation of Adaptive
Security Frameworks in Enterprise Networks," IEEE Transactions on
Network and Service Management, 2021.

[Zhang21] X. Zhang et al., "Threat-aware QoS Management for Secure
Wireless Networks," IEEE Transactions on Network and Service
Management, 2021.

[Shor94] P. Shor, "Algorithms for Quantum Computation: Discrete
Logarithms and Factoring," Proceedings of the 35th Annual Symposium
on Foundations of Computer Science, 1994.

Authors' Addresses

   Rachid Bouziane
   SecRoot.io
   Villa El Majd 171, Tamsna Temara
   Rabat, Morocco
   Email: contact@secroot.io

Expires: December 26, 2025