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SETS-THIRAL-AES128-Power-Protected-TI-FPGA

SETS-THIRAL-AES128-Power-Protected-TI-FPGA

This dataset is part of the SETS-THIRAL dataset repository, which comprises multiple datasets suitable for performing AI-assisted Side-Channel Analysis (SCA). It consists of Power consumption traces obtained from an TI(Threshold Implementation) protected AES-128 cryptographic implementation executed on Kintex-7 FPGA (SAKURA-X /SASEBO GIII).

About Dataset

The traces were obtained by measuring the real-time power consumption of an TI protected AES-128 encryption process. These measurements are highly suitable for Side-Channel Analysis (SCA), enabling cryptographic key recovery through both statistical techniques and deep learning–based approaches. Power consumption data were collected using Agilent Technologies MSO7104B Oscilloscope, with the bandwidth of 1GHz and Sampling rate of 4GS/s connected to an Kintex-7 FPGA. Trigger-based synchronization is used during acquisition process to align the captured traces with encryption operations. After collection, the traces were formatted and annotated with appropriate labels to support side-channel analysis experiments and AI model development. The dataset is provided in HDF5 (.h5) format and is divided into Profiling_traces and Attack_traces groups. The Profiling_traces group consists of 100,000 power traces, each containing 10,000 sample points along with a metadata structured array containing the corresponding plaintext, key, and ciphertext values and a label array. The Attack_traces group contains 20,000 power traces together with the corresponding metadata structured array. Labels are generated from the first-round S-box output of the AES-128 encryption algorithm. For each trace, plaintext byte 2 (PT[2]) is XORed with byte 2 of the secret key (K[2]). The resulting value is passed through the AES S-box, and the resulting 8-bit S-box output is used to derive the label. The labels correspond to the complete S-box output value, resulting in 256 possible classes ranging from 0 to 255. Threshold Implementation (TI) is a masking-based countermeasure that provides resistance against side-channel attacks by decomposing sensitive intermediate values into multiple shares while satisfying the properties of correctness, non-completeness and uniformity. By ensuring that no individual share reveals information about the secret, TI reduces exploitable leakage from cryptographic computations. In the SETS-THIRAL repository, TI-protected implementation was incorporated to generate datasets corresponding to masked cryptographic executions. The resulting datasets enable the evaluation of leakage assessment methodologies using conventional side-channel attacks and AI-assisted attack techniques against masking-based countermeasures.

Purpose of Dataset

This Dataset Is Generated For Research And Educational Purposes In Side-channel Analysis (Sca). It Provides Labelled Power Traces Captured From Cryptographic Computations And Can Be Used To Develop, Evaluate And Benchmark Classical And Ai-assisted Attack Methodologies. The Dataset Also Facilitates The Study Of Leakage Characteristics, Feature Extraction Techniques, Model Interpretability And The Evaluation Of Cryptographic Countermeasures.

Activity Overview Activity Overview

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Tags Tags

  • Cybersecurity
  • AI4Bharat
  • Machine Learning
  • Deep Learning
  • statistical analysis
  • AI For All
  • ai for science

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Attribution-Non-Commercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)

SETS_THIRAL_AES128_Power_Protected_TI_FPGA.h5 ( 655.52 MB )


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