Weihang Peng

23 papers A* 9Journal 14
YearRankTypeTitle / Venue / Authors
2026 J jnl
IEEE Signal Process. Lett.
Yuhan Zhang, Jie Zhou, Weihang Peng, Xiaode Liu, Yuanpei Chen
2025 J jnl
Complex Intell. Syst.
Xiaode Liu, Yufei Guo, Yuanpei Chen, Jie Zhou, Yuhan Zhang, Weihang Peng, Xuhui Huang, Zhe Ma
2025 J jnl
Neural Networks
Yufei Guo, Zecheng Hao, Jiahang Shao, Jie Zhou, Xiaode Liu, Xin Tong, Yuhan Zhang, Yuanpei Chen, Weihang Peng, Zhe Ma
2025 A* conf
ICML
Yufei Guo, Yuhan Zhang, Jie Zhou, Xiaode Liu, Xin Tong, Yuanpei Chen, Weihang Peng, Zhe Ma
2025 J jnl
CoRR
Yufei Guo, Yuhan Zhang, Zhou Jie, Xiaode Liu, Xin Tong, Yuanpei Chen, Weihang Peng, Zhe Ma
2025 A* conf
CVPR
Yufei Guo, Xiaode Liu, Yuanpei Chen, Weihang Peng, Yuhan Zhang, Zhe Ma
2025 J jnl
CoRR
Yufei Guo, Xiaode Liu, Yuanpei Chen, Weihang Peng, Yuhan Zhang, Zhe Ma
2024 A* conf
NeurIPS
Yufei Guo, Weihang Peng, Xiaode Liu, Yuanpei Chen, Yuhan Zhang, Xin Tong, Zhou Jie, Zhe Ma
2024 A* conf
AAAI
Yuhan Zhang, Xiaode Liu, Yuanpei Chen, Weihang Peng, Yufei Guo, Xuhui Huang, Zhe Ma
2024 J jnl
IEEE Signal Process. Lett.
Yufei Guo, Weihang Peng, Yuanpei Chen, Jie Zhou, Zhe Ma
2024 A* conf
NeurIPS
Yufei Guo, Yuanpei Chen, Zecheng Hao, Weihang Peng, Zhou Jie, Yuhan Zhang, Xiaode Liu, Zhe Ma
2024 J jnl
CoRR
Yufei Guo, Yuanpei Chen, Zecheng Hao, Weihang Peng, Zhou Jie, Yuhan Zhang, Xiaode Liu, Zhe Ma
2024 J jnl
CoRR
Ying Fu, Yu Li, Shaodi You, Boxin Shi, Jose Alvarez, Coert Van Gemeren, Linwei Chen, Yunhao Zou, Zichun Wang, Yichen Li, Yuze Han, Yingkai Zhang, Jianan Wang, Qinglin Liu, Wei Yu, Xiaoqian Lv, Jianing Li, Shengping Zhang, Xiangyang Ji, Yuanpei Chen, Yuhan Zhang, Weihang Peng, Liwen Zhang, Zhe Xu, Dingyong Gou, Cong Li, Senyan Xu, Yunkang Zhang, Siyuan Jiang, Xiaoqiang Lu, Licheng Jiao, Fang Liu, Xu Liu, Lingling Li, Wenping Ma, Shuyuan Yang, Haiyang Xie, Jian Zhao, Shihuang Huang, Peng Cheng, Xi Shen, Zheng Wang, Shuai An, Caizhi Zhu, Xuelong Li, Tao Zhang, Liang Li, Yu Liu, Chenggang Yan, Gengchen Zhang, Linyan Jiang, Bingyi Song, Zhuoyu An, Haibo Lei, Qing Luo, Jie Song, Yuan Liu, Qihang Li, Haoyuan Zhang, Lingfeng Wang, Wei Chen, Aling Luo, Cheng Li, Jun Cao, Shu Chen, Zifei Dou, Xinyu Liu, Jing Zhang, Kexin Zhang, Yuting Yang, Xuejian Gou, Qinliang Wang, Yang Liu, Shizhan Zhao, Yanzhao Zhang, Libo Yan, Yuwei Guo, Guoxin Li, Qiong Gao, Chenyue Che, Long Sun, Xiang Chen, Hao Li, Jinshan Pan, Chuanlong Xie, Hongming Chen, Mingrui Li, Tianchen Deng, Jingwei Huang, Yufeng Li, Fei Wan, Bingxin Xu, Jian Cheng, Hongzhe Liu, Cheng Xu, Yuxiang Zou, Weiguo Pan, Songyin Dai, Sen Jia, Junpei Zhang
2024 A* conf
AAAI
Yufei Guo, Yuanpei Chen, Xiaode Liu, Weihang Peng, Yuhan Zhang, Xuhui Huang, Zhe Ma
2023 J jnl
CoRR
Yufei Guo, Weihang Peng, Yuanpei Chen, Liwen Zhang, Xiaode Liu, Xuhui Huang, Zhe Ma
2023 J jnl
Pattern Recognit.
Yufei Guo, Weihang Peng, Yuanpei Chen, Liwen Zhang, Xiaode Liu, Xuhui Huang, Zhe Ma
2023 A* conf
ICCV
Yufei Guo, Yuhan Zhang, Yuanpei Chen, Weihang Peng, Xiaode Liu, Liwen Zhang, Xuhui Huang, Zhe Ma
2023 J jnl
CoRR
Yufei Guo, Yuhan Zhang, Yuanpei Chen, Weihang Peng, Xiaode Liu, Liwen Zhang, Xuhui Huang, Zhe Ma
2023 A* conf
ICCV
Yufei Guo, Xiaode Liu, Yuanpei Chen, Liwen Zhang, Weihang Peng, Yuhan Zhang, Xuhui Huang, Zhe Ma
2023 J jnl
CoRR
Yufei Guo, Xiaode Liu, Yuanpei Chen, Liwen Zhang, Weihang Peng, Yuhan Zhang, Xuhui Huang, Zhe Ma
2023 A* conf
NeurIPS
Dayong Ren, Zhe Ma, Yuanpei Chen, Weihang Peng, Xiaode Liu, Yuhan Zhang, Yufei Guo
2023 J jnl
CoRR
Dayong Ren, Zhe Ma, Yuanpei Chen, Weihang Peng, Xiaode Liu, Yuhan Zhang, Yufei Guo
2023 J jnl
CoRR
Yufei Guo, Yuanpei Chen, Xiaode Liu, Weihang Peng, Yuhan Zhang, Xuhui Huang, Zhe Ma
redb/extractors/decompiler/bninja/similarity/minhasher.py
← Index redb/extractors/decompiler/bninja/similarity/minhasher.py python
import logging
import random
from enum import Enum

from ..analysis.medium_level_normalization import MediumLevelNormalization

try:
    from .minhashcustom import MinHashCustom
    from ..analysis.low_level_normalization import LowLevelNormalization
except ImportError:
    # Fallback to absolute imports (for multiprocessing spawned processes)
    from redb.extractors.decompiler.bninja.similarity.minhashcustom import MinHashCustom
    from redb.extractors.decompiler.bninja.analysis.low_level_normalization import LowLevelNormalization

## Values for this configuration were extracted from https://github.com/danielplohmann/mcrit/blob/main/mcrit/config/MinHashConfig.py#L10
# Length in number of Shingles of which a minhash consists
# this value represents the length of sha256sum hash truncated
MINHASH_SIGNATURE_LENGTH: int = 64
# Number of bits per signature element (1-32 bits)
MINHASH_SIGNATURE_BITS: int = 8


class TokenKind(Enum):
    LLIL = "llil"
    TYPED_LLIL = "typed_llil"
    MLIL = "mlil"
    TYPED_MLIL = "typed_mlil"


class MinHasher:
    # stick to the default method
    MINHASH_STRATEGY_HASH_ALL = 1

    def __init__(self, seed, il_function, kind: TokenKind = TokenKind.LLIL):
        self._minhash_seeds = []
        self.il_func = il_function
        self.kind = kind
        self._minhash_permutation = []
        self._signature_segments = []
        self._initMinhashing(seed)

    def _initMinhashing(self, MINHASH_SEED=None):
        random.seed(MINHASH_SEED)
        # init sequence of seeds
        self._minhash_seeds = [
            random.randint(0, MinHashCustom.getHashMax()) for _ in range(MINHASH_SIGNATURE_LENGTH)
        ]

    def make_ngrams(self, tokens, n=3):
        """Take the ngrams of the IL we try to pass into the functions"""
        return [tuple(tokens[i:i+n]) for i in range(len(tokens) - n + 1)]

    def _extract_tokens(self):
        """Extract the IL tokens from the IL function, picking the right
        normalizer (LLIL/MLIL) and the right normalization mode
        (skeleton/typed) based on self.kind."""
        if self.kind in (TokenKind.LLIL, TokenKind.TYPED_LLIL):
            normalizer = LowLevelNormalization()
        elif self.kind in (TokenKind.MLIL, TokenKind.TYPED_MLIL):
            normalizer = MediumLevelNormalization()
        else:
            raise ValueError(f"Unsupported token kind: {self.kind}")

        # typed variants include operand type info, skeleton variants don't
        if self.kind in (TokenKind.TYPED_LLIL, TokenKind.TYPED_MLIL):
            normalize = normalizer.normalize_instr_with_operands
        else:
            normalize = normalizer.normalize_instruction_all_levels

        instructions = []
        for basic_block in self.il_func.basic_blocks:
            for il in basic_block:
                instructions.append(normalize(il))

        return instructions

    def calculateMinHash(self):
        """Calculate hash function every time, then take minimum shingle per shingler"""
        minhash_result = MinHashCustom(minhash_bits=MINHASH_SIGNATURE_BITS)
        minhash_signature = []

        tokens = self._extract_tokens()
        shingles = self.make_ngrams(tokens, n=3)

        # Functions with fewer than 3 IL instructions can't produce n-grams
        # Return empty minhash for such small functions (thunks, stubs, etc.)
        # Triggered by 39d8ad95b0323c37bd3134ab93ac4af44c66a1a8443a41c1ac02cec19bb2816a
        if not shingles:
            return []

        # Generate the MinHash
        for seed in self._minhash_seeds:
            hashed_shingles = [
                self.shingle_hash(shingle, seed) for shingle in shingles
            ]
            min_value = min(hashed_shingles)

            if MINHASH_SIGNATURE_BITS < 32:
                min_value %= (2 ** MINHASH_SIGNATURE_BITS)

            minhash_signature.append(min_value)

        minhash_result.setMinHash(minhash_signature)
        return minhash_result.getMinHashInt()

    def shingle_hash(self, shingle, hash_seed=0):
        """Produce a single 32bit UINT hash for a given shingle"""
        return MinHashCustom.hashData(shingle, hash_seed)