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SETS-THIRAL-AES128-Power-UnProtected-MC

SETS-THIRAL-AES128-Power-UnProtected-MC

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 unprotected AES-128 cryptographic implementation executed on STM32F microcontroller platform.

About Dataset

The traces were obtained by measuring the real-time power consumption of an AES-128 encryption process during its first round. 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 the ChipWhisperer CW1200 platform connected to an STM32F microcontroller. 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 150,000 power traces, each containing 6,001 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.

Purpose of Dataset

This Dataset Is Developed 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
  • Deep Learning
  • Machine Learnin
  • statistical analysis
  • AI For All
  • ai4science

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

SETS_AES128_Power_UnProtected.h5 ( 3.84 GB )


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  • N Eswari Devi·1 month(s) ago
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      SETS_AES128_Power_UnProtected.h5