Mahnane Lamia

36 papers B 1Journal 20Unranked 15
YearRankTypeTitle / Venue / Authors
2025 J jnl
J. Supercomput.
Rania Zaimi, Khouloud Safi Eljil, Mohamed Hafidi, Mahnane Lamia, Farid Naït-Abdesselam
2024 J jnl
J. Supercomput.
Rania Zaimi, Mohamed Hafidi, Mahnane Lamia
2024 J jnl
Educ. Inf. Technol.
Noura Zeroual, Mahnane Lamia, Mohamed Hafidi
2024 conf
ISPR (3)
Samiha Besnaci, Mohamed Hafidi, Mahnane Lamia
2024 conf
IAM
Noura Zeroual, Mahnane Lamia, Mohamed Hafidi
2023 J jnl
Intell. Decis. Technol.
Rania Zaimi, Mohamed Hafidi, Mahnane Lamia
2023 J jnl
Interact. Learn. Environ.
Ouissem Benmesbah, Mahnane Lamia, Mohamed Hafidi
2023 conf
ISPR (1)
Samiha Besnaci, Mohamed Hafidi, Mahnane Lamia
2023 conf
ISPR (1)
Noura Zeroual, Mahnane Lamia, Mohamed Hafidi
2021 J jnl
Int. J. Web Based Learn. Teach. Technol.
Ouissem Benmesbah, Mahnane Lamia, Mohamed Hafidi
2021 conf
NISS (ACM)
Rania Zaimi, Mohamed Hafidi, Mahnane Lamia
2021 J jnl
Intell. Decis. Technol.
Ouissem Benmesbah, Mahnane Lamia, Mohamed Hafidi
2021 J jnl
Educ. Inf. Technol.
Ouissem Benmesbah, Mahnane Lamia, Mohamed Hafidi
2021 conf
NISS (Springer)
Noureddine Gouasmi, Mahnane Lamia, Yassine Lafifi
2020 conf
SNAMS
Rania Zaimi, Mohamed Hafidi, Mahnane Lamia
2019 J jnl
Int. J. Web Based Learn. Teach. Technol.
Mahnane Lamia, Mohamed Hafidi
2019 conf
CITSC
Ouissem Benmesbah, Mahnane Lamia, Mohamed Hafidi
2019 B conf
SCA
Samira Aouidi, Mahnane Lamia, Mohamed Hafidi
2019 conf
NISS
Teimzit Amira, Mahnane Lamia, Mohamed Hafidi
2019 J jnl
Int. J. Inf. Commun. Technol. Educ.
Teimzit Amira, Mahnane Lamia, Mohamed Hafidi
2019 J jnl
J. Univers. Comput. Sci.
Mahnane Lamia, Mohamed Hafidi, André Tricot, Ouissem Benmesbah
2019 J jnl
Rev. Socionetwork Strateg.
Teimzit Amira, Mahnane Lamia, Mohamed Hafidi
2019 conf
SNAMS
Samira Aouidi, Mahnane Lamia, Mohamed Hafidi
2019 conf
ICIST
Samira Aouidi, Mahnane Lamia, Mohamed Hafidi
2019 conf
WMNC
Ouissem Benmesbah, Mahnane Lamia, Mohamed Hafidi, Ishaq Zouaghi
2018 conf
MISNC
Teimzit Amira, Mahnane Lamia, Mohamed Hafidi
2018 conf
MISNC
Mahnane Lamia, Mohamed Hafidi, Samira Aouidi
2018 J jnl
Comput. Educ.
Mohamed Hafidi, Mahnane Lamia
2017 J jnl
J. Educ. Technol. Soc.
Mahnane Lamia
2015 J jnl
Int. J. Web Based Learn. Teach. Technol.
Mohamed Hafidi, Mahnane Lamia
2015 J jnl
Int. J. Inf. Technol. Web Eng.
Mahnane Lamia, Mohamed Hafidi
2013 J jnl
Int. J. Inf. Commun. Technol. Educ.
Mahnane Lamia, Laskri Mohamed Tayeb, Philippe Trigano
2013 J jnl
J. Univers. Comput. Sci.
Mahnane Lamia, Laskri Mohamed Tayeb
2013 J jnl
Intell. Decis. Technol.
Mahnane Lamia, Laskri Mohamed Tayeb
2012 J jnl
Int. J. Web Based Learn. Teach. Technol.
Mahnane Lamia, Laskri Mohamed Tayeb
2010 conf
Erog'IA
Mahnane Lamia, Mohamed Tayeb Laskri
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)