Mansour Al Ghanim

13 papers A* 1A 1B 1C 1Misc 1Journal 6Unranked 2
YearRankTypeTitle / Venue / Authors
2025 conf
EMNLP (Findings)
Mansour Al Ghanim, Jiaqi Xue, Rochana Prih Hastuti, Mengxin Zheng, Yan Solihin, Qian Lou
2025 conf
EMNLP (Findings)
Rochana Prih Hastuti, Rian Adam Rajagede, Mansour Al Ghanim, Mengxin Zheng, Qian Lou
2025 J jnl
CoRR
Rochana Prih Hastuti, Rian Adam Rajagede, Mansour Al Ghanim, Mengxin Zheng, Qian Lou
2025 J jnl
CoRR
Jiaqi Xue, Yifei Zhao, Mansour Al Ghanim, Shangqian Gao, Ruimin Sun, Qian Lou, Mengxin Zheng
2025 B conf
IJCNN
Saleh Almohaimeed, May Alsofyani, Saad Almohaimeed, Mansour Al Ghanim, Liqiang Wang
2025 J jnl
CoRR
Saleh Almohaimeed, May Alsofyani, Saad Almohaimeed, Mansour Al Ghanim, Liqiang Wang
2025 J jnl
CoRR
Mansour Al Ghanim, Jiaqi Xue, Rochana Prih Hastuti, Mengxin Zheng, Yan Solihin, Qian Lou
2024 Misc conf
SAC
Saleh Almohaimeed, Saad Almohaimeed, Mansour Al Ghanim, Liqiang Wang
2024 J jnl
CoRR
Saleh Almohaimeed, Saad Almohaimeed, Mansour Al Ghanim, Liqiang Wang
2024 A* conf
EMNLP
Mansour Al Ghanim, Saleh Almohaimeed, Mengxin Zheng, Yan Solihin, Qian Lou
2024 J jnl
CoRR
Mansour Al Ghanim, Saleh Almohaimeed, Mengxin Zheng, Yan Solihin, Qian Lou
2023 A conf
ECAI
Mansour Al Ghanim, Muhammad Santriaji, Qian Lou, Yan Solihin
2022 C conf
ISCC
Mnassar Alyami, Mohammed Alkhowaiter, Mansour Al Ghanim, Cliff C. Zou, Yan Solihin
redb/extractors/decompiler/bninja/similarity/minhashcustom.py
← Index redb/extractors/decompiler/bninja/similarity/minhashcustom.py python
import numpy as np
import mmh3

class MinHashCustom:
    """
    DTO for an actual MinHash
    <minhash>: a binary sequence of packed int8/32 values
    <minhash_int>: the equivalent representation of <minhash> but as list of int8/32
    """

    _HASH_MAX = 0xFFFFFFFF
    _MINHASH_BITS = 32

    def getSignatureEntrySize(self):
        return 1 if self.MINHASH_BITS <= 8 else 4

    def __init__(self, function_addr=None, minhash_bytes=None, minhash_signature=None, minhash_bits=32):
        self.minhash = b""
        self.minhash_int = []
        if minhash_bits:
            self._MINHASH_BITS = minhash_bits
        if minhash_bytes and minhash_signature:
            raise ValueError("Can use only one keyword argument")
        if minhash_bytes:
            if self._MINHASH_BITS <= 8:
                minhash_signature = np.frombuffer(minhash_bytes, dtype=np.uint8)
            else:
                minhash_signature = np.frombuffer(minhash_bytes, dtype=np.uint32)
            self.setMinHash(minhash_signature)
        elif minhash_signature:
            self.setMinHash(minhash_signature)

        self.shingler_composition = {}
        self.function_addr = function_addr

    def hasMinHash(self):
        return len(self.minhash) > 0

    def getMinHash(self):
        return self.minhash

    def getMinHashInt(self):
        return self.minhash_int

    def setMinHash(self, minhash_signature):
        self.minhash_int = [i % 2 ** self._MINHASH_BITS for i in minhash_signature]
        if self._MINHASH_BITS <= 8:
            self.minhash = np.array(self.minhash_int, dtype=np.uint8).tobytes()
        else:
            self.minhash = np.array(self.minhash_int, dtype=np.uint32).tobytes()

    def getComposition(self):
        return self.shingler_composition

    def scoreAgainst(self, other):
        return self.calculateMinHashScore(self.minhash, other.minhash, minhash_bits=self._MINHASH_BITS)

    @staticmethod
    def getHashMax():
        return MinHashCustom._HASH_MAX

    @staticmethod
    def hashData(data, seed) -> int:
        if isinstance(data, (str, bytes, bytearray)):
            return mmh3.hash(data, seed) & MinHashCustom._HASH_MAX
        elif isinstance(data, (list, tuple)):
            to_hash = "|".join(str(elem) for elem in data)
            return mmh3.hash(to_hash, seed) & MinHashCustom._HASH_MAX
        else:
            raise NotImplementedError(
                f"Type not supported for hashData: {type(data).__name__}"
            )

    @staticmethod
    def calculateMinHashScore(first, second, minhash_bits=32):
        if minhash_bits <= 8:
            first_np = np.frombuffer(first, dtype=np.uint8)
            second_np = np.frombuffer(second, dtype=np.uint8)
        else:
            first_np = np.frombuffer(first, dtype=np.uint32)
            second_np = np.frombuffer(second, dtype=np.uint32)
        return 100.0 * sum(first_np == second_np) / len(first_np)

    @staticmethod
    def calculateMinHashIntScore(first, second):
        score = 0
        num_hashes = len(first)
        if num_hashes:
            for index, part in enumerate(first):
                score += 1 if part == second[index] else 0
            return 100.0 * score / num_hashes
        return 0.0

    @property
    def MINHASH_BITS(self):
        return self._MINHASH_BITS