C. Natalie van der Wal

39 papers B 4C 5Misc 2Journal 11Unranked 16
YearRankTypeTitle / Venue / Authors
2022 J jnl
IEEE Trans. Circuits Syst. II Express Briefs
Jaber Valinejad, Lamine Mili, C. Natalie van der Wal, Yijun Xu
2022 conf
ESSA
Jakob Irnich, C. Natalie van der Wal, Dorine C. Duives, Willem L. Auping
2022 J jnl
J. Soc. Comput.
Jaber Valinejad, Lamine Mili, C. Natalie van der Wal
2022 C conf
MABS
Elvira Van Damme, C. Natalie van der Wal, Gert Jan Hofstede, Frances M. T. Brazier
2020 J jnl
CoRR
Jaber Valinejad, Lamine Mili, C. Natalie van der Wal
2020 J jnl
CoRR
Jaber Valinejad, Lamine Mili, Konstantinos P. Triantis, Michael von Spakovsky, C. Natalie van der Wal
2018 J jnl
Trans. Comput. Collect. Intell.
Berend Jutte, C. Natalie van der Wal
2018 conf
SocInfo (2)
Daniel Formolo, Tibor Bosse, C. Natalie van der Wal
2017 Misc conf
EPIA
Daniel Formolo, C. Natalie van der Wal
2017 conf
IEA/AIE (1)
C. Natalie van der Wal, Daniel Formolo, Tibor Bosse
2017 Misc conf
EPIA
Lenin Medeiros, C. Natalie van der Wal
2017 J jnl
Simul.
Tibor Bosse, Rob Duell, Zulfiqar Ali Memon, Jan Treur, C. Natalie van der Wal
2017 conf
IEA/AIE (1)
C. Natalie van der Wal, Maik Couwenberg, Tibor Bosse
2017 conf
HCI (1)
C. Natalie van der Wal, Annabella Hermans, Tibor Bosse
2017 conf
ICCCI (1)
Daniel Formolo, C. Natalie van der Wal
2017 J jnl
Trans. Comput. Collect. Intell.
C. Natalie van der Wal, Daniel Formolo, Mark A. Robinson, Michael Minkov, Tibor Bosse
2016 conf
ICCCI (1)
Berend Jutte, C. Natalie van der Wal
2015 J jnl
Cogn. Comput.
Tibor Bosse, Rob Duell, Zulfiqar Ali Memon, Jan Treur, C. Natalie van der Wal
2015 conf
BIH
C. Natalie van der Wal, Mona Irrmischer
2015 conf
BIH
C. Natalie van der Wal, Mona Irrmischer
2013 B conf
PRIMA
Julia S. Mollee, C. Natalie van der Wal
2013 J jnl
Appl. Intell.
C. Natalie van der Wal, Wojtek Kowalczyk
2013 J jnl
Auton. Agents Multi Agent Syst.
Tibor Bosse, Mark Hoogendoorn, Michel C. A. Klein, Jan Treur, C. Natalie van der Wal, Arlette van Wissen
2012 ch.
Agents and Ambient Intelligence
Rob Duell, Zulfiqar Ali Memon, Jan Treur, C. Natalie van der Wal
2012 C conf
IEA/AIE
Azizi Ab Aziz, Jan Treur, C. Natalie van der Wal
2012 C conf
ECMS
Kees Boersma, David Passenier, Julia S. Mollee, C. Natalie van der Wal
2012 C conf
IEA/AIE
Wojtek Kowalczyk, C. Natalie van der Wal
2011 conf
IEA/AIE (2)
Tibor Bosse, Mark Hoogendoorn, Michel C. A. Klein, Jan Treur, C. Natalie van der Wal
2011 J jnl
Trans. Comput. Collect. Intell.
Mark Hoogendoorn, Jan Treur, C. Natalie van der Wal, Arlette van Wissen
2011 B conf
PRIMA
Azizi Ab Aziz, Jan Treur, C. Natalie van der Wal
2011 conf
ICONIP (1)
Tibor Bosse, Vikas Chandra, Eve Mitleton-Kelly, C. Natalie van der Wal
2010 conf
IAT
Mark Hoogendoorn, Jan Treur, C. Natalie van der Wal, Arlette van Wissen
2010 conf
Brain Informatics
Azizi Ab Aziz, Jan Treur, C. Natalie van der Wal
2010 conf
Brain Informatics
Mark Hoogendoorn, Jan Treur, C. Natalie van der Wal, Arlette van Wissen
2010 conf
ICONIP (1)
Mark Hoogendoorn, Jan Treur, C. Natalie van der Wal, Arlette van Wissen
2009 B conf
PRIMA
Tibor Bosse, Rob Duell, Zulfiqar Ali Memon, Jan Treur, C. Natalie van der Wal
2009 conf
IAT
Tibor Bosse, Rob Duell, Zulfiqar Ali Memon, Jan Treur, C. Natalie van der Wal
2009 B conf
ACII
Rob Duell, Zulfiqar Ali Memon, Jan Treur, C. Natalie van der Wal
2009 C conf
ECMS
Tibor Bosse, Rob Duell, Zulfiqar Ali Memon, Jan Treur, C. Natalie van der Wal
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