Beyond Immediate Activation: Temporally Decoupled Backdoor Attacks on Time Series Forecasting

TL;DR

This paper introduces TDBA, a novel backdoor attack framework for multivariate time series forecasting that enables flexible, delayed, and variable-specific activation of malicious patterns, surpassing existing methods in effectiveness and stealth.

Contribution

TDBA is the first framework to enable temporally decoupled backdoor attacks on time series forecasting, allowing flexible activation timing and variable-specific triggers.

Findings

TDBA outperforms existing baselines in attack success rate.

TDBA maintains high stealthiness in real-world datasets.

Ablation studies validate the controllability and robustness of TDBA.

Abstract

Existing backdoor attacks on multivariate time series (MTS) forecasting enforce strict temporal and dimensional coupling between triggers and target patterns, requiring synchronous activation at fixed positions across variables. However, realistic scenarios often demand delayed and variable-specific activation. We identify this critical unmet need and propose TDBA, a temporally decoupled backdoor attack framework for MTS forecasting. By injecting triggers that encode the expected location of the target pattern, TDBA enables the activation of the target pattern at any positions within the forecasted data, with the activation position flexibly varying across different variable dimensions. TDBA introduces two core modules: (1) a position-guided trigger generation mechanism that leverages smoothed Gaussian priors to generate triggers that are position-related to the predefined target pattern; and (2) a position-aware optimization module that assigns soft weights based on trigger completeness, pattern coverage, and temporal offset, facilitating targeted and stealthy attack optimization. Extensive experiments on real-world datasets show that TDBA consistently outperforms existing baselines in effectiveness while maintaining good stealthiness. Ablation studies confirm the controllability and robustness of its design.