💻 computer science

X-NegoBox: An Explainable Privacy-Budget Negotiation Framework for Secure Peer-to-Peer Energy Data Exchange

X-NegoBox is an explainable framework that enables secure peer-to-peer energy data exchange by locally managing prosumer data through an autonomous privacy budget negotiation protocol and an explainable agreement layer to adaptively balance privacy protection with trading needs while providing transparent decision justifications.

Original authors: Poushali Sengupta, Sabita Maharjan, Frank Eliassen, Yan Zhang

Published 2026-04-28

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CC BY 4.0

Original authors: Poushali Sengupta, Sabita Maharjan, Frank Eliassen, Yan Zhang

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine your home energy data (like your smart meter readings) is a treasure chest filled with valuable secrets about your daily life: when you wake up, what appliances you use, and when you are home. In the modern energy world, neighbors and energy companies want to borrow items from this chest to help balance the grid or trade energy.

However, handing over the whole chest is dangerous—it could reveal your private habits. Traditional systems are like a bouncer with a rigid rulebook: "No entry unless you have a specific badge," or "We only give you a blurry photo, no matter who asks." This is frustrating because it doesn't adapt to who is asking or why.

X-NegoBox is a new, smarter system that acts like a diplomatic negotiator for your data. Here is how it works, broken down into simple concepts:

1. The Private DataBox: Your Secure Vault

Instead of sending your raw data out, you keep it in a secure, locked vault right in your home (called a "Private DataBox").

The Rule: "Run code, not data."
The Analogy: Imagine a chef (the data requester) wants to taste your soup to see if it needs salt. Instead of sending your soup out to their kitchen, they send their own recipe card into your kitchen. Your vault cooks the soup inside the vault, adds a little bit of "noise" (like a pinch of salt that hides the exact flavor), and only sends the final taste back to the chef. The chef never sees your actual ingredients or the raw soup.

2. The Negotiator (APBNP): The Smart Bouncer

When someone wants to access your data, a smart robot called APBNP (Autonomous Privacy-Budget Negotiation Protocol) steps in. It doesn't just say "Yes" or "No." It negotiates based on four things:

Trust: Do I know this person? Have they been good neighbors before? (High trust = more data access).
Sensitivity: How private is the data? (Knowing your exact appliance usage is riskier than knowing your total monthly bill).
Purpose: Why do they need it? (Fixing the power grid is a good reason; guessing your lifestyle habits is a bad reason).
The Budget: You have a limited "privacy budget" (like a currency). Every time you share data, you spend some of it. The negotiator checks if you have enough left.

The Magic: If the request is too risky, the negotiator doesn't just reject it. It says, "I can't give you 5-minute details, but I can give you 1-hour averages," or "I can't give you this data today, but I can next week." This is called a counter-offer.

3. The Explainer (X-Contract): The "Why" Button

One of the biggest problems with current systems is that you never know why a request was rejected. X-NegoBox fixes this with a layer called X-Contract.

The Analogy: Think of it like a receipt that explains a transaction. If a request is denied, the system gives you a clear, human-readable note: "Your request was rejected because the data is too sensitive for a new neighbor, and you have only 10% of your privacy budget left."
If it's accepted, it explains: "Approved because you trust this neighbor, and the purpose is essential for the grid."
This builds trust because you aren't left guessing.

4. The Security Team (Threshold Secret Sharing)

Even after a deal is made, the system ensures no single person can cheat.

The Analogy: Imagine a bank vault that requires three different keys held by three different people to open. Even if one person is bribed or hacked, the vault stays shut. In X-NegoBox, the "key" to release the final data is split up. It only opens if enough trusted parts agree, preventing any single bad actor from stealing your data.

What Did They Find?

The researchers tested this system using real energy data from different cities and simulated scenarios with 100 households.

Better Success Rate: Unlike old systems that say "No" too often, X-NegoBox found a way to say "Yes" (or "Yes, but with changes") about 60% to 87% of the time, depending on the situation.
Privacy Protection: It successfully prevented privacy leaks by ensuring the "privacy budget" wasn't spent too quickly.
Speed: The negotiation happens in milliseconds, fast enough for real-time use on regular home devices.

In Summary:
X-NegoBox turns data sharing from a rigid "all-or-nothing" game into a flexible conversation. It keeps your raw data locked in your home, negotiates the best deal based on trust and purpose, explains its decisions clearly, and ensures that even if the system is under attack, your secrets remain safe.

1. Problem Statement

The decentralization of modern energy systems has transformed consumers into prosumers who exchange granular energy data (e.g., load curves, PV generation, appliance usage) for peer-to-peer (P2P) trading, demand response, and forecasting. However, this data reveals sensitive household patterns (occupancy, lifestyle, routines), creating significant privacy risks.

Limitations of Existing Solutions:

Static Policies: Current mechanisms rely on fixed access controls or predetermined Differential Privacy (DP) budgets. They lack adaptability to varying data sensitivity, requester intent, or trust levels.
Lack of Transparency: Prosumers rarely receive explanations for why a data request is accepted, rejected, or modified, eroding trust.
Data Exposure: Many approaches require raw data to leave the user's control or rely on centralized "clean rooms," increasing the attack surface.
Rigidity: Fixed DP budgets lead to either premature budget exhaustion (blocking useful data sharing) or excessive privacy leakage.

2. Methodology: The X-NegoBox Framework

X-NegoBox is a distributed framework that enables adaptive privacy budgeting and transparent decision-making while keeping raw data confined locally. It operates on a "Run Code, Not Data" paradigm.

Core Architecture Components

Private DataBox: A local computation enclave (at the household or edge) where raw data resides. It enforces privacy constraints and ensures raw data never leaves the box.
Autonomous Privacy-Budget Negotiation Protocol (APBNP): The core engine that dynamically calculates an optimal DP budget ( $\epsilon^*$ $ϵ^{*}$ ) for each request.
- Inputs: Feature sensitivity ( $S_x$ ), requester trust ( $T_{ij}$ ), declared purpose compatibility ( $P(p)$ ), and remaining cumulative budget ( $H_j$ ).
- Optimization: Solves for $\epsilon^*$ by maximizing a utility-risk score:
  $\epsilon^* = \arg \max_{\epsilon} \left( \lambda_1 U(\epsilon) - \lambda_2 R(\epsilon) + \lambda_3 T_{ij} + \lambda_4 P(p) - \lambda_5 C(\epsilon) \right)$
- Outcomes:
  - Approval: If $\epsilon^*$ fits constraints.
  - Counter-offer: If the request is too sensitive, APBNP proposes modifications (e.g., lower temporal resolution, shorter duration) to find a feasible $\epsilon^*$ .
  - Rejection: If no feasible configuration exists.
Explainable Agreement Layer (X-Contract): Generates human- and machine-readable explanations for every decision (approval, rejection, or counter-offer). It translates technical scores (sensitivity, trust, budget) into actionable rationale (e.g., "Rejected due to high appliance-level sensitivity and low remaining budget").
Secure Execution Sandbox:
- Requester code is validated and executed inside the DataBox.
- The system applies DP noise ( $\tilde{y} = y + \text{Noise}(\epsilon^*, S_x)$ ) to the output before release.
- Prevents side-channel attacks, code injection, and unauthorized data exfiltration.
Threshold Secret Sharing (TSS): Used for authorization. A signing key is split across $n$ nodes; at least $k$ nodes must cooperate to reconstruct the key and authorize the release of sanitized outputs, preventing unilateral disclosure.

Key Scoring Mechanisms

Feature Sensitivity ( $S_x$ ): Aggregates risk weights of requested features (e.g., location = 1.0, appliance usage = 0.7, aggregated load = 0.2).
Trust Score ( $T_{ij}$ ): Based on historical contract success, output quality, and alignment with declared purpose.
Purpose Compatibility ( $P(p)$ ): A static score (0–1) based on regulatory necessity (e.g., Billing = 1.0, Behavioral Profiling = 0.1).

3. Key Contributions

Explainable Autonomous Negotiation: A framework that allows prosumers to negotiate privacy budgets dynamically with transparent justifications, replacing static policies.
APBNP Protocol: An optimization algorithm that allocates per-request DP budgets based on a multi-factor scoring system (sensitivity, trust, purpose, cost).
X-Contract Layer: A dedicated module for generating interpretable explanations for contract decisions, enhancing trust and regulatory compliance.
Secure "Run Code, Not Data" Sandbox: A local execution environment that validates code, enforces DP, and ensures raw data never leaves the prosumer's control.
Comprehensive Evaluation: Validation on realistic energy market workloads demonstrating improved privacy preservation and acceptance rates.

4. Experimental Results

The framework was evaluated using real-world datasets (UCI Household, DE/FR/IT national loads) and synthetic smart-grid simulations (100 prosumers).

Acceptance Stability: Across 48 scenarios involving different datasets and negotiation patterns, the mean acceptance rate remained stable at ~60% ( $\sigma = 0.013$ ). This indicates the system avoids "all-or-nothing" behavior and adapts well to data heterogeneity.
Privacy Budget Efficiency:
- Compared to a fixed- $\epsilon$ baseline (which exhausted budgets after ~80 requests), APBNP sustained long-term sharing.
- In a 100-prosumer simulation, the system achieved an 87.49% acceptance rate with a mean remaining budget of 0.765 per prosumer, proving it does not prematurely deplete privacy resources.
Budget Sensitivity:
- Scarcity Regime ( $\epsilon_0 \le 2$ ): High rejection rates to protect privacy.
- Stable Regime ( $4 \le \epsilon_0 \le 7$ ): Acceptance saturates near 99%.
- Surplus Regime ( $\epsilon_0 \ge 8$ ): Acceptance reaches 100%, showing diminishing returns on increasing budgets beyond a certain point.
Performance Overhead:
- Negotiation time: 0.32 ms per request.
- Explanation generation: 0.006 ms.
- Sandbox execution overhead: ~121% relative, but absolute time < 0.02 ms, making it suitable for real-time edge deployment.
Robustness: Explanations remained stable (97.25% unchanged) even when input scores were perturbed by ±5%.

5. Significance and Impact

Trust Building: By providing clear, actionable explanations for data-sharing decisions, X-NegoBox addresses the "black box" problem in privacy-preserving systems, encouraging prosumer participation.
Adaptive Privacy: Moves beyond rigid, one-size-fits-all DP budgets to a context-aware model that balances utility and risk based on who is asking, what they want, and why.
Scalability: The low computational overhead and local execution model make it feasible for deployment on resource-constrained edge devices (e.g., smart meters, home gateways).
Regulatory Compliance: The explainability layer and audit logs support compliance with regulations like GDPR, which require transparency in automated decision-making.
Future of P2P Energy: Enables secure, granular data exchange necessary for advanced P2P energy trading and grid balancing without compromising household privacy.

In conclusion, X-NegoBox successfully bridges the gap between the need for granular energy data and the imperative of privacy protection, offering a scalable, explainable, and adaptive solution for the future decentralized energy landscape.