Ovidiu Stan

14 papers B 1Journal 1Unranked 12
YearRankTypeTitle / Venue / Authors
2025 B conf
ETS
Maksim Jenihhin, Jaan Raik, Artur Jutman, Natalia Cherezova, Raimund Ubar, Liviu Miclea, Szilárd Enyedi, I. Stefan, Ovidiu Stan, Cosmina Corches, Z. Peng, Petru Eles, Rolf Drechsler, S. Eggersglüß, Görschwin Fey, Andreas Glowatz, Daniel Tille, Georges G. E. Gielen, Anthony Coyette, Wim Dobbelaere, Ronny Vanhooren, P.-Y. Chuang, Erik Jan Marinissen, Giorgio Di Natale, M. Barragan, Paolo Maistri, S. Mir, Vatajelu I. Vatajelu, Paolo Bernardi, S. Di Carlo, Paolo Prinetto, Matteo Sonza Reorda, Massimo Violante, Haralampos-G. Stratigopoulos, M. K. Michael, Stelios Neophytou, Stavros Hadjitheophanous, Kyriakos Christou, M. Skitsas, Alberto Bosio, Bastien Deveautour, P. Girard, Marcello Traiola, Arnaud Virazel, F. Fernandes Dos Santos, Angeliki Kritikakou, Gioele Casagranda, Marzio Vallero, Flavio Vella, Paolo Rech, Letícia Maria Bolzani Poehls, Milos Krstic, Marko S. Andjelkovic, F. Vargas, Grigor Tshagharyan, Gurgen Harutyunyan, Valery A. Vardanian, Samvel K. Shoukourian, Yervant Zorian, Jennifer Dworak, Kundan Nepal, Theodore W. Manikas, Mottaqiallah Taouil, Moritz Fieback, Anteneh Gebregiorgis, Rajendra Bishnoi, Said Hamdioui, Abhijit Chatterjee, A. Saha, Suhasini Komarraju, K. Ma, Chandramouli N. Amarnath, Mehdi Baradaran Tahoori, Mahta Mayahinia, Maryam Rajabalipanah, Katayoon Basharkhah, N. Nosrati, Zahra Jahanpeima, Zain Navabi, Hans-Joachim Wunderlich, Sybille Hellebrand
2025 J jnl
Comput. Biol. Medicine
Ponduri Vasanthi, Lingamallu Naga Srinivasu, Ventrapragada Teju, Kambhampati Venkata Sowmya, Anca Stan, Valentin Sita, Liviu Miclea, Ovidiu Stan
2024 conf
ICECET
Oliver-Grigorie Cosma, Dan Gota, Alexandru Ciobotaru, Marius Misaros, Ovidiu Stan, Honoriu Valean, Liviu Miclea
2023 conf
ICECET
Oliver-Grigorie Cosma, Claudiu Domuta, Dan Gota, Ovidiu Stan, Alexandra Fanca, Adela Pop Puscasiu, Honoriu Valean, Liviu Miclea
2022 conf
AQTR
Ionut-Catalin Donca, Ovidiu Stan, Liviu Miclea
2022 conf
AQTR
Dan Gota, Ruxandra Miron-Onciul, Claudiu Domuta, Alexandra Fanca, Adela Pop Puscasiu, Ovidiu Stan, Honoriu Valean, Liviu Miclea
2022 conf
AQTR
Dan Gota, Claudiu Domuta, Alexandra Fanca, Adela Pop Puscasiu, Ovidiu Stan, Honoriu Valean, Liviu Miclea
2020 conf
AQTR
Roxana Rusu-Both, Alexandra Popa, Bianca Toderean, Ovidiu Stan
2020 conf
AQTR
Bianca Toderean, Roxana Rusu-Both, Ovidiu Stan
2020 conf
AQTR
Camelia Avram, Ovidiu Stan, Claudiu Domuta, Vlad Muresan, Corina Racasan, Valentin Sita, Adina Astilean
2018 conf
AQTR
Ovidiu Stan, Liviu Miclea
2016 conf
AQTR
Ovidiu Stan, Camelia Avram, Iulia Adina Stefan, Adina Astilean
2014 conf
AQTR
A. T. Popescu, Ovidiu Stan, Liviu Miclea
2014 conf
AQTR
Ovidiu Stan, Liviu Miclea
redb/extractors/decompiler/apk/smali_normalization.py
← Index redb/extractors/decompiler/apk/smali_normalization.py python
"""Semantic normalization of Dalvik/smali instructions.

Analogous to Binary Ninja's LLIL normalization: strips register allocation
noise and instruction encoding variants while preserving semantic operations.

Three normalization levels (most aggressive to most detailed):
  - 'category':    semantic category only (MOV, ALU, CALL, ...)
  - 'opcode':      base opcode, width-invariant (add, sub, invoke, ...)
  - 'opcode_api':  opcode category + API method/field references for
                   invoke/field/alloc instructions (default for MinHash)

References:
  - Smali+ 12-category reduction (Canfora et al.)
  - MOSDroid opcode family grouping
  - DroidSIFT/DroidSim API-sensitive similarity
"""

import re
from typing import List

# ---------------------------------------------------------------------------
# Dalvik opcode -> semantic category mapping
# ---------------------------------------------------------------------------
# Prefix-matched against instruction opcodes. Order matters for overlapping
# prefixes (longer/more-specific prefixes should come first in iteration,
# but since we use startswith and break on first match, we order by
# specificity within the list).

OPCODE_CATEGORIES = {
    # Arithmetic/logic
    "add": "ALU", "sub": "ALU", "mul": "ALU", "div": "ALU",
    "rem": "ALU", "and": "ALU", "or": "ALU", "xor": "ALU",
    "shl": "ALU", "shr": "ALU", "ushr": "ALU", "neg": "ALU",
    "not": "ALU",
    # Data movement
    "move": "MOV", "const": "CONST",
    # Memory access (field/array)
    "iget": "LOAD", "sget": "LOAD", "aget": "LOAD",
    "iput": "STORE", "sput": "STORE", "aput": "STORE",
    # Invocations
    "invoke": "CALL",
    # Control flow
    "if": "BRANCH", "goto": "JMP",
    "switch": "SWITCH",
    "return": "RET",
    # Object/type
    "new": "ALLOC", "check": "TYPE", "instance": "TYPE",
    # Array
    "fill": "ARR", "array": "ARR",
    # Comparison
    "cmpl": "CMP", "cmpg": "CMP", "cmp": "CMP",
    # Exception / synchronization
    "throw": "EXC", "monitor": "SYNC",
    # Conversion (int-to-long, float-to-int, etc.)
    "int-to": "CONV", "long-to": "CONV", "float-to": "CONV",
    "double-to": "CONV",
}

# Pre-compiled regexes for operand extraction
_METHOD_REF_RE = re.compile(r"(L[\w/$]+;->[\w<>]+\(.*?\)[\w/$;\[]*)")
_FIELD_REF_RE = re.compile(r"(L[\w/$]+;->[\w]+:[\w/$;\[]+)")
_CLASS_REF_RE = re.compile(r"(L[\w/$]+;)")
_CONST_STRING_RE = re.compile(r'^const-string(?:/jumbo)?\s')


def categorize_opcode(opcode: str) -> str:
    """Map a Dalvik opcode to its semantic category.

    Prefix-matched: 'add-int/2addr' matches 'add' -> 'ALU'.
    Returns 'OTHER' for unrecognized opcodes.
    """
    for prefix, cat in OPCODE_CATEGORIES.items():
        if opcode.startswith(prefix):
            return cat
    return "OTHER"


# Mapping from semantic categories to the ACFG feature vector indices
# used by Binary Ninja's build_block_features (cfg_features.py).
# This enables cross-platform ACFG feature comparison.
CATEGORY_TO_ACFG_INDEX = {
    "ALU": 0,       # CAT_ARITHMETIC
    "CONV": 0,      # arithmetic-adjacent
    "CMP": 4,       # CAT_COMPARISON
    "MOV": 2,       # CAT_TRANSFER
    "CONST": 2,     # transfer-adjacent (loading constants)
    "LOAD": 5,      # CAT_MEMORY
    "STORE": 5,     # CAT_MEMORY
    "CALL": 3,      # CAT_CALL
    "BRANCH": 1,    # CAT_LOGIC (conditional logic)
    "JMP": 1,       # CAT_LOGIC
    "SWITCH": 1,    # CAT_LOGIC
    "RET": 2,       # CAT_TRANSFER
    "ALLOC": 5,     # CAT_MEMORY (heap allocation)
    "TYPE": 6,      # CAT_OTHER
    "ARR": 5,       # CAT_MEMORY
    "EXC": 6,       # CAT_OTHER
    "SYNC": 6,      # CAT_OTHER
    "OTHER": 6,     # CAT_OTHER
}


def normalize_instruction(line: str, level: str = "opcode_api") -> str:
    """Normalize a single smali instruction line.

    Args:
        line: A single smali instruction (whitespace-stripped).
        level: Normalization level:
            'category'   - most aggressive: just semantic category
            'opcode'     - base opcode only, width/addressing-mode invariant
            'opcode_api' - category + API references for invoke/field/alloc
                          (default, best for MinHash similarity)

    Returns:
        Normalized instruction string, or empty string for non-instructions.
    """
    stripped = line.strip()
    if not stripped:
        return ""

    parts = stripped.split(None, 1)
    opcode = parts[0]
    operands = parts[1] if len(parts) > 1 else ""

    if level == "category":
        return categorize_opcode(opcode)

    if level == "opcode":
        # Strip type/width suffixes for invariance:
        # add-int, add-long, add-float -> 'add'
        # add-int/2addr -> 'add'
        base = re.split(r"[-/]", opcode)[0]
        return base

    if level == "opcode_api":
        # const-string: preserve string content (encrypted strings are a
        # key malware indicator)
        if _CONST_STRING_RE.match(stripped):
            # Extract the string literal
            str_match = re.search(r'"(.*)"', operands)
            if str_match:
                return f"CONST_STR \"{str_match.group(1)}\""
            return "CONST_STR"

        # invoke-*: preserve method reference
        if opcode.startswith("invoke"):
            ref = _METHOD_REF_RE.search(operands)
            if ref:
                return f"CALL {ref.group(1)}"
            return "CALL"

        # Field access: preserve field reference
        if opcode.startswith(("iget", "iput", "sget", "sput")):
            ref = _FIELD_REF_RE.search(operands)
            if ref:
                cat = "LOAD" if "get" in opcode else "STORE"
                return f"{cat} {ref.group(1)}"
            # Fallback: try space-separated format from androguard
            # e.g. "iget v0, p0, Lcom/Foo;->field Ljava/lang/String;"
            space_ref = re.search(
                r"(L[\w/$]+;->[\w]+)\s+([\w/$;\[]+)", operands
            )
            if space_ref:
                cat = "LOAD" if "get" in opcode else "STORE"
                return f"{cat} {space_ref.group(1)}:{space_ref.group(2)}"
            cat = "LOAD" if "get" in opcode else "STORE"
            return cat

        # new-instance: preserve allocated type
        if opcode.startswith("new-instance") or opcode == "new-array":
            ref = _CLASS_REF_RE.search(operands)
            if ref:
                return f"ALLOC {ref.group(1)}"
            return "ALLOC"

        # Everything else: just the category
        return categorize_opcode(opcode)

    # Unknown level: return raw opcode
    return opcode


def normalize_method_body(
    body: str, level: str = "opcode_api"
) -> List[str]:
    """Normalize all instructions in a smali method body.

    Filters out directives (.), labels (:), comments (#), and blank lines.
    Returns a list of normalized instruction strings.

    Args:
        body: Raw smali method body text.
        level: Normalization level (see normalize_instruction).

    Returns:
        List of normalized instruction strings (no empty strings).
    """
    normalized = []
    for line in body.split("\n"):
        stripped = line.strip()
        # Skip non-instructions
        if not stripped:
            continue
        if stripped.startswith((".",":", "#")):
            continue
        result = normalize_instruction(stripped, level)
        if result:
            normalized.append(result)
    return normalized