Neha Sharma

20 papers Journal 9Unranked 11
YearRankTypeTitle / Venue / Authors
2025 J jnl
Multim. Tools Appl.
Gaurav Srivastav, Shri Kant, Durgesh Srivastava, Neha Sharma, Yu-Chen Hu
2025 J jnl
Multim. Tools Appl.
Pushpak Jain, Dewansh Anand, Rajni, Vansh Behal, Vipul Kapoor, Neha Sharma, Neeru Jindal
2024 J jnl
Multim. Tools Appl.
Neha Sharma, Neeru Jindal
2024 conf
IC3I
Amit Kumar, Neha Sharma, Rahul Chauhan, Kireet Joshi, Dipra Mitra, Vijay Madaan
2024 J jnl
IET Quantum Commun.
Amit Kumar, Neha Sharma, Nikhil Marriwala, Sunita Panda, M. Aruna, Jeetendra Kumar
2023 conf
RTIP2R (2)
Amit Kumar, Neha Sharma, Rahul Chauhan, Akhilendra Khare, Abhineet Anand, Manish Sharma
2023 conf
IC3I
Vivek Arya, Meet Kumari, Rahul Chauhan, Neha Sharma
2023 conf
IC3I
Sunil Gupta, Neha Sharma, Deepak Thakur, Jatin Arora, Vikas Solanki, Rahul Chauhan
2023 conf
IC3I
Vivek Arya, Meet Kumari, Rahul Chauhan, Neha Sharma
2023 conf
IC3I
Vivek Arya, Meet Kumari, Rahul Chauhan, Neha Sharma
2023 J jnl
Multim. Syst.
Neha Sharma, Chinmay Chakraborty, Rajeev Kumar
2023 J jnl
ACM Trans. Asian Low Resour. Lang. Inf. Process.
Neha Sharma, Mukesh Soni, Sumit Kumar, Rajeev Kumar, Nabamita Deb, Anurag Shrivastava
2022 conf
IC3I
Gaurav Srivastav, Mamoon Rashid, Richa Singh, Anita Gehlot, Neha Sharma
2022 conf
IC3I
Dipra Mitra, Neha Sharma, Mamoon Rashid, Rajesh Singh
2022 conf
IC3I
R. Shashidhar, Sanjay S. Tippannavar, Krishnakumar Balachandra Bhat, Neha Sharma, Mamoon Rashid, Arti Rana
2022 conf
IC3I
Meet Kumari, Vivek Arya, Neha Sharma, Mamoon Rashid, Rajesh Singh
2022 conf
IC3I
Geerija Lavania, Vivek Arya, Neha Sharma, Mamoon Rashid, Shaik Vaseem Akram
2021 J jnl
Genet. Program. Evolvable Mach.
Neha Sharma, Usha Batra
2021 J jnl
EAI Endorsed Trans. Pervasive Health Technol.
Nagaraj M. Lutimath, Neha Sharma, Byregowda B. K
2020 J jnl
EAI Endorsed Trans. Scalable Inf. Syst.
Neha Sharma, Usha Batra
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)