Carole Bernon

42 papers A 2B 1C 1Misc 6Journal 10Unranked 21
YearRankTypeTitle / Venue / Authors
2023 Misc conf
PAAMS
Quentin Pouvreau, Jean-Pierre Georgé, Carole Bernon, Sébastien Maignan
2022 conf
OLA
Quentin Pouvreau, Jean-Pierre Georgé, Carole Bernon, Sébastien Maignan
2022 Misc conf
PAAMS
Félix Furger, Carole Bernon, Jean-Pierre Georgé, Nazim Pigenet, Paul Valiere
2019 A conf
AAMAS
Tanguy Esteoule, Carole Bernon, Marie-Pierre Gleizes, Morgane Barthod
2018 Misc conf
PAAMS
Tanguy Esteoule, Alexandre Perles, Carole Bernon, Marie-Pierre Gleizes, Morgane Barthod
2018 conf
SASO
Nicolas Verstaevel, Jean-Pierre Georgé, Carole Bernon, Marie-Pierre Gleizes
2018 conf
JFSMA
Sébastien Maignan, Carole Bernon
2018 conf
ICAART (1)
Valérian Guivarch, Carole Bernon, Marie-Pierre Gleizes
2018 conf
ICAART (1)
Sébastien Maignan, Carole Bernon, Pierre Glize
2014 Misc conf
PACBB
Sebastien Alameda, Carole Bernon, Jean-Pierre Mano
2014 J jnl
J. Comput. Neurosci.
Önder Gürcan, Kemal S. Türker, Jean-Pierre Mano, Carole Bernon, Oguz Dikenelli, Pierre Glize
2013 B conf
SMC
Luc Pons, Carole Bernon
2013 J jnl
J. Simulation
Önder Gürcan, Oguz Dikenelli, Carole Bernon
2012 conf
SASO
Önder Gürcan, Carole Bernon, Kemal S. Türker, Jean-Pierre Mano, Pierre Glize, Oguz Dikenelli
2012 J jnl
Inf. Softw. Technol.
Carole Bernon, Alfredo Garro, Jorge J. Gómez-Sanz
2012 J jnl
CoRR
Önder Gürcan, Carole Bernon, Kemal S. Türker
2011 Misc conf
PAAMS
Sylvain Videau, Carole Bernon, Pierre Glize, Jean-Louis Uribelarrea
2011 ch.
Self-organising Software
Carole Bernon, Marie-Pierre Gleizes, Frédéric Migeon, Giovanna Di Marzo Serugendo
2011 C conf
FedCSIS
Önder Gürcan, Oguz Dikenelli, Carole Bernon
2010 conf
ICAART (2)
Sylvain Videau, Carole Bernon, Pierre Glize
2010 conf
ICAART (Revised Selected Papers)
Sylvain Videau, Carole Bernon, Pierre Glize
2010 J jnl
Simul. Model. Pract. Theory
Noélie Bonjean, Carole Bernon, Pierre Glize
2009 J jnl
Rev. d'Intelligence Artif.
Sylvain Lemouzy, Carole Bernon, Marie-Pierre Gleizes
2009 conf
MALLOW
Noélie Bonjean, Carole Bernon, Pierre Glize
2009 conf
AOSE
Cu D. Nguyen, Anna Perini, Carole Bernon, Juan Pavón, John Thangarajah
2008 conf
ESAW
Carole Bernon, Davy Capera, Jean-Pierre Mano
2008 conf
JFSMA
Sylvain Lemouzy, Carole Bernon, Marie-Pierre Gleizes
2006 J jnl
Informatica (Slovenia)
Carole Bernon, Vincent Chevrier, Vincent Hilaire, Paul Marrow
2006 conf
ESAW
Carole Bernon, Marie-Pierre Gleizes, Gauthier Picard
2005 J jnl
Knowl. Eng. Rev.
Carole Bernon, Massimo Cossentino, Juan Pavón
2005 J jnl
Informatica (Slovenia)
Carole Bernon, Massimo Cossentino, Juan Pavón
2005 conf
Engineering Self-Organising Systems
Gauthier Picard, Carole Bernon, Marie-Pierre Gleizes
2005 conf
CEEMAS
Gauthier Picard, Carole Bernon, Marie-Pierre Gleizes
2004 conf
AOSE
Carole Bernon, Massimo Cossentino, Marie-Pierre Gleizes, Paola Turci, Franco Zambonelli
2004 A conf
AAMAS
Gauthier Picard, Carole Bernon, Marie-Pierre Gleizes
2003 J jnl
Tech. Sci. Informatiques
Carole Bernon, Valérie Camps, Marie-Pierre Gleizes, Gauthier Picard
2003 conf
ESAW
Carole Bernon, Valérie Camps, Marie-Pierre Gleizes, Gauthier Picard
2003 conf
Engineering Self-Organising Systems
Carole Bernon, Valérie Camps, Marie-Pierre Gleizes, Gauthier Picard
2002 conf
ESAW
Carole Bernon, Marie-Pierre Gleizes, Sylvain Peyruqueou, Gauthier Picard
2002 conf
AOIS@CAiSE
Carole Bernon, Marie-Pierre Gleizes, Gauthier Picard, Pierre Glize
1996 conf
Software Engineering for Parallel and Distributed Systems
Carole Bernon, Claude Bétourné, A. Sayah
1992 Misc conf
Ada-Europe
G. Bazalgette, D. Bekele, Carole Bernon, Mamoun Filali, J. M. Rigaud, A. Sayah
redb/extractors/decompiler/apk/method_extractor.py
← Index redb/extractors/decompiler/apk/method_extractor.py python
"""Per-method content extraction, hashing, and similarity computation.

Handles SHA-256 content hashing, ssdeep/TLSH fuzzy hashing, MinHash
computation, and obfuscation indicator detection for APK methods.
"""

import hashlib
import re
from typing import Dict, List, Optional

from redb.extractors.decompiler.apk.smali_normalization import (
    categorize_opcode,
    normalize_method_body,
)
from redb.extractors.decompiler.apk.smali_parser import SmaliParser


# ---------------------------------------------------------------------------
# Smali Prime Product — semantic primes matching Binary Ninja's LLIL primes
# ---------------------------------------------------------------------------
# Each Dalvik semantic category maps to the same prime its LLIL counterpart
# uses in cfg_features.py. This makes prime products semantically comparable
# for APK-vs-APK similarity (not numerically comparable to Binja values).

SMALI_OP_PRIMES = {
    "ALU": 37,       # ADD/SUB → same prime as LLIL_ADD
    "CONV": 131,     # Type conversions → same as LLIL_SX
    "CMP": 103,      # Comparisons → same as LLIL_CMP_E
    "MOV": 2,        # Register moves → same as LLIL_SET_REG
    "CONST": 2,      # Constants → SET_REG equivalent
    "LOAD": 5,       # Field/array reads → same as LLIL_LOAD
    "STORE": 7,      # Field/array writes → same as LLIL_STORE
    "CALL": 17,      # invoke-* → same as LLIL_CALL
    "BRANCH": 29,    # if-* → same as LLIL_IF
    "JMP": 31,       # goto → same as LLIL_GOTO
    "SWITCH": 151,   # switch → same as LLIL_JUMP_TO
    "RET": 23,       # return → same as LLIL_RET
    "ALLOC": 5,      # new-instance/new-array → LOAD-adjacent (heap access)
    "TYPE": 1,       # check-cast/instance-of → identity (metadata)
    "ARR": 5,        # array-length/fill-array → LOAD-adjacent
    "EXC": 23,       # throw → RET-adjacent (control transfer out)
    "SYNC": 1,       # monitor → identity (no LLIL equivalent)
    "OTHER": 1,      # Unknown → identity
}


def compute_prime_product_smali(smali_body: str) -> int:
    """Multiplicative hash of normalized Dalvik opcodes. Mod 2^64.

    Same algorithm as cfg_features.compute_prime_product but using
    Dalvik semantic categories instead of LLIL operation enums.
    """
    if not smali_body:
        return 0

    product = 1
    for line in smali_body.splitlines():
        stripped = line.strip()
        if not stripped or stripped.startswith((".", ":", "#")):
            continue
        opcode = stripped.split()[0].split("/")[0] if stripped else ""
        category = categorize_opcode(opcode)
        prime = SMALI_OP_PRIMES.get(category, 1)
        product = (product * prime) % (2**64)

    return product


def count_call_instructions(smali_body: str) -> int:
    """Count invoke-* instructions in a smali method body."""
    if not smali_body:
        return 0
    count = 0
    for line in smali_body.splitlines():
        stripped = line.strip()
        if stripped.startswith("invoke-"):
            count += 1
    return count


def compute_sha256(content: str) -> str:
    """Compute SHA-256 hash of normalized content."""
    return hashlib.sha256(content.encode("utf-8")).hexdigest()


def compute_ssdeep(content: str) -> Optional[str]:
    """Compute ssdeep fuzzy hash of content."""
    try:
        import ppdeep
        data = content.encode("utf-8")
        if len(data) < 50:
            return None
        result = ppdeep.hash(data)
        return result if result else None
    except (ImportError, Exception):
        return None


def compute_tlsh(content: str) -> Optional[str]:
    """Compute TLSH fuzzy hash of content."""
    try:
        import tlsh
        data = content.encode("utf-8")
        if len(data) < 50:
            return None
        result = tlsh.hash(data)
        return result if result else None
    except (ImportError, Exception):
        return None


def compute_minhash(
    content: str,
    n: int = 3,
    normalization_level: str = "opcode_api",
) -> Optional[List[int]]:
    """Compute MinHash signature from semantically normalized smali n-grams.

    Applies semantic normalization (analogous to Binary Ninja's LLIL) before
    computing the MinHash. This strips register allocation noise and
    instruction encoding variants while preserving operation semantics and
    API references.

    Uses the same algorithm and parameters as the Binary Ninja MinHasher
    (64 seeds from master seed 0xdeadbeef, 8-bit signature elements, mmh3)
    to ensure cross-platform similarity comparisons are compatible.

    Args:
        content: Raw smali method body.
        n: N-gram size (default 3).
        normalization_level: Normalization level for instructions.
            'opcode_api' (default) preserves API call/field references.
            'category' uses only semantic categories.
            'opcode' uses base opcodes without operands.
    """
    try:
        import mmh3
    except ImportError:
        return None

    HASH_MAX = 0xFFFFFFFF
    SIGNATURE_LENGTH = 64
    SIGNATURE_BITS = 8

    # Semantically normalize instructions (like LLIL for native code)
    lines = normalize_method_body(content, level=normalization_level)

    if len(lines) < n:
        return None

    # Build n-grams (tuples of normalized instruction strings)
    shingles = [tuple(lines[i:i + n]) for i in range(len(lines) - n + 1)]

    if not shingles:
        return None

    # Generate deterministic seeds matching the Binary Ninja pipeline
    import random
    rng = random.Random(0xDEADBEEF)
    seeds = [rng.randint(0, HASH_MAX) for _ in range(SIGNATURE_LENGTH)]

    # For each seed, hash all shingles and take the minimum
    signature = []
    for seed in seeds:
        min_val = HASH_MAX
        for shingle in shingles:
            text = "|".join(str(elem) for elem in shingle)
            h = mmh3.hash(text, seed) & HASH_MAX
            if h < min_val:
                min_val = h
        # Truncate to signature bits
        if SIGNATURE_BITS < 32:
            min_val %= (2 ** SIGNATURE_BITS)
        signature.append(min_val)

    return signature


def detect_obfuscation_indicators(
    method_name: str,
    class_name: str,
    smali_body: str,
    instruction_count: int,
) -> Dict[str, bool]:
    """Compute obfuscation indicators for a method.

    Returns dict with boolean indicators.
    """
    indicators = {}

    # Short method name (typical R8/ProGuard output)
    indicators["short_method_name"] = len(method_name) <= 2

    # Short class name — extract simple name from Dalvik descriptor
    simple_class = class_name
    if "/" in simple_class:
        simple_class = simple_class.rsplit("/", 1)[-1]
    simple_class = simple_class.rstrip(";")
    indicators["short_class_name"] = len(simple_class) <= 2

    # String encryption: const-string followed by decryption-pattern call
    indicators["has_string_encryption"] = _detect_string_encryption(smali_body)

    # Reflection calls
    indicators["has_reflection_calls"] = _detect_reflection_calls(smali_body)

    # Excessive goto count (control flow flattening)
    goto_count = _count_goto_instructions(smali_body)
    threshold = max(5, int(instruction_count * 0.15))
    indicators["excessive_goto_count"] = goto_count > threshold

    return indicators


def _detect_string_encryption(smali_body: str) -> bool:
    """Detect const-string followed by decryption-pattern calls."""
    lines = smali_body.split("\n")
    for i, line in enumerate(lines):
        stripped = line.strip()
        if stripped.startswith("const-string"):
            # Check the next 3 lines for invoke-* to potential decryption
            for j in range(i + 1, min(i + 4, len(lines))):
                next_line = lines[j].strip()
                if next_line.startswith("invoke-"):
                    # Common decryption patterns
                    if any(
                        pat in next_line
                        for pat in [
                            "decrypt",
                            "decode",
                            "Cipher",
                            "DES",
                            "AES",
                            "Base64",
                            "getBytes",
                        ]
                    ):
                        return True
    return False


def _detect_reflection_calls(smali_body: str) -> bool:
    """Detect use of Java reflection APIs."""
    reflection_patterns = [
        "Ljava/lang/reflect/",
        "Ljava/lang/Class;->forName",
        "Ljava/lang/Class;->getMethod",
        "Ljava/lang/Class;->getDeclaredMethod",
        "Ljava/lang/Class;->getField",
        "Ljava/lang/Class;->getDeclaredField",
    ]
    for pattern in reflection_patterns:
        if pattern in smali_body:
            return True
    return False


def _count_goto_instructions(smali_body: str) -> int:
    """Count goto/goto_16/goto_32 instructions."""
    count = 0
    for line in smali_body.split("\n"):
        stripped = line.strip()
        if stripped.startswith(("goto ", "goto/16 ", "goto/32 ")):
            count += 1
        elif stripped in ("goto", "goto/16", "goto/32"):
            count += 1
    return count


def dalvik_to_java_class(descriptor: str) -> str:
    """Convert Dalvik class descriptor to Java dot notation.

    Lcom/example/Foo; -> com.example.Foo
    """
    if descriptor.startswith("L") and descriptor.endswith(";"):
        return descriptor[1:-1].replace("/", ".")
    return descriptor.replace("/", ".")


def dalvik_type_to_java(type_desc: str) -> str:
    """Convert a Dalvik type descriptor to Java type name."""
    type_map = {
        "V": "void",
        "Z": "boolean",
        "B": "byte",
        "S": "short",
        "C": "char",
        "I": "int",
        "J": "long",
        "F": "float",
        "D": "double",
    }

    if not type_desc:
        return "void"

    if type_desc in type_map:
        return type_map[type_desc]

    if type_desc.startswith("["):
        return dalvik_type_to_java(type_desc[1:]) + "[]"

    if type_desc.startswith("L") and type_desc.endswith(";"):
        full = type_desc[1:-1].replace("/", ".")
        # Return simple name
        return full.rsplit(".", 1)[-1] if "." in full else full

    return type_desc


def dalvik_to_java_prototype(
    method_name: str, signature: str, class_name: str = ""
) -> str:
    """Convert Dalvik method signature to Java-style prototype.

    Input: method_name='onCreate', signature='(Landroid/os/Bundle;)V'
    Output: 'void onCreate(Bundle)'
    """
    # Parse return type and param types from signature
    if not signature or not signature.startswith("("):
        return f"void {method_name}()"

    close_paren = signature.find(")")
    if close_paren == -1:
        return f"void {method_name}()"

    params_str = signature[1:close_paren]
    return_type_str = signature[close_paren + 1:]

    return_type = dalvik_type_to_java(return_type_str)
    params = _parse_dalvik_params(params_str)
    param_java = ", ".join(dalvik_type_to_java(p) for p in params)

    return f"{return_type} {method_name}({param_java})"


def _parse_dalvik_params(params_str: str) -> List[str]:
    """Parse Dalvik parameter descriptor string into individual types."""
    params = []
    i = 0
    while i < len(params_str):
        ch = params_str[i]
        if ch in "VZBSCIJFD":
            params.append(ch)
            i += 1
        elif ch == "[":
            # Array — find the base type
            array_prefix = "["
            i += 1
            while i < len(params_str) and params_str[i] == "[":
                array_prefix += "["
                i += 1
            if i < len(params_str):
                if params_str[i] == "L":
                    end = params_str.find(";", i)
                    if end != -1:
                        params.append(array_prefix + params_str[i : end + 1])
                        i = end + 1
                    else:
                        break
                else:
                    params.append(array_prefix + params_str[i])
                    i += 1
        elif ch == "L":
            end = params_str.find(";", i)
            if end != -1:
                params.append(params_str[i : end + 1])
                i = end + 1
            else:
                break
        else:
            i += 1
    return params