Jaime Campos

29 papers B 1C 12Misc 1Journal 2Unranked 13
YearRankTypeTitle / Venue / Authors
2025 conf
HCI (54)
Jaime Campos, Nataliya Shakhovska
2024 conf
XR (2)
Miguel Nunes, Sílvia Gonçalves, Alexandre Carrança, Nuno Sousa, Jaime Campos, Luís Magalhães, João Ribeiro
2024 Misc conf
CSIT
Oleh Basystiuk, Nataliya Melnykova, Jaime Campos
2024 conf
SMARTINDUSTRY
Nataliya Shakhovska, Jaime Campos
2023 conf
MWSCAS
Andalib Nizam, Shaghayegh Aslanzadeh, Jaime Campos, Bathiya Senevirathna, Pamela Abshire, Brian Thompson, Abhishek Motayed, Nicole McFarlane
2022 C conf
IDDM
Jaime Campos
2022 C ed.
IDDM
Natalia Shakhovska, Stéphane Chrétien, Ivan Izonin, Jaime Campos
2021 C ed.
IDDM
Nataliya Shakhovska, Addisson Salazar, Ivan Izonin, Jaime Campos
2020 C conf
IDDM
Yuriy Bashtyk, Jaime Campos, Andriy Fechan, Sviatoslav Konstantyniv, Vitaliy Yakovyna
2020 conf
CCECE
Jaime Campos, Philip Ferguson
2020 C conf
IDDM
Yaroslav Sokolovskyy, Volodymyr Shymanskyi, Maryana Levkovych, Ivan Sokolovskyy, Jaime Campos
2020 conf
CSIT (1)
Ivan Sokolovskyy, Jaime Campos
2020 C ed.
IDDM
Nataliya Shakhovska, Jaime Campos, Nataliia Melnykova, Ivan Izonin
2020 C conf
IDDM
Vitaliy Yakovyna, Natalya Shakhovska, Khrystyna Shakhovska, Jaime Campos
2019 C conf
CoDIT
Jaime Campos, Pankaj Sharma, Michele Albano, Erkki Jantunen, David Baglee, Luis Lino Ferreira
2019 C conf
IDDM
Nataliya Boyko, Olena Pylypiv, Yulia Peleshchak, Yurii Kryvenchuk, Jaime Campos
2019 conf
DCSMart
Nataliya Boyko, Khrystyna Shakhovska, Lesia I. Mochurad, Jaime Campos
2019 conf
CCECE
Amin Yahyaabadi, Matt Driedger, Varsha Parthasarathy, Rishabh Sahani, Aimee Carvey, Tamkin Rahman, Valorie Platero, Jaime Campos, Philip Ferguson
2019 conf
CSIT (1)
Jaime Campos, Linda Askenäs
2019 C ed.
IDDM
Nataliya Shakhovska, Ivan Izonin, Sergio Montenegro, Yannick Estève, Jaime Campos, Natalia Kryvinska
2018 conf
WebSci
Hernan Sarmiento, Barbara Poblete, Jaime Campos
2018 C conf
IDDM
Jaime Campos, Linda Askenäs
2018 C conf
CoDIT
Erkki Jantunen, Jaime Campos, Pankaj Sharma, Mark McKay
2018 J jnl
J. Syst. Control. Eng.
Erkki Jantunen, Unai Gorostegui, Urko Zurutuza, Michele Albano, Luis Lino Ferreira, Csaba Hegedüs, Jaime Campos
2017 conf
ICSRS
Erkki Jantunen, Jaime Campos, Pankaj Sharma, David Baglee
2015 conf
ISAmI
Ana Coelho, João Pedro Ribeiro, Jaime Campos, Sara Silva, Victor Alves
2010 B conf
WCNC
Kandeepan Sithamparanathan, Ana Sierra, Jaime Campos, Imrich Chlamtac
2009 J jnl
Comput. Ind.
Jaime Campos
2009 conf
WPNC
Ana Sierra, Juan Chóliz, Bruno Selva, Jaime Campos, Ángela Hernández-Solana
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)