Rallou Thomopoulos

67 papers B 4C 4Misc 7Journal 23Unranked 25
YearRankTypeTitle / Venue / Authors
2025 J jnl
J. Artif. Soc. Soc. Simul.
Loïc Sadou, Stéphane Couture, Rallou Thomopoulos, Patrick Taillandier
2025 C conf
ISAGA
Nicolás Méndez Barreto, Lamprini Chartofylaka, Aurélie Maurice, Nicolas Darcel, Rallou Thomopoulos
2023 conf
EGC
Camille Vivas, Christelle Planche, Catherine Macombe, Patrick Borel, Erwan Engel, Rallou Thomopoulos
2023 J jnl
Frontiers Artif. Intell.
Sherman Aline, Gilles Hubert, Yoann Pitarch, Rallou Thomopoulos
2023 J jnl
CoRR
Romy Lynn Chaib, Rallou Thomopoulos, Catherine Macombe
2023 J jnl
Frontiers Appl. Math. Stat.
Meritxell Vinyals, Régis Sabbadin, Stéphane Couture, Loïc Sadou, Rallou Thomopoulos, Kevin Chapuis, Baptiste Lesquoy, Patrick Taillandier
2022 J jnl
Decis. Support Syst.
Benjamin Delhomme, Franck Taillandier, Irène Abi-Zeid, Rallou Thomopoulos, Cédric Baudrit, Laurent Mora
2022 conf
WI/IAT
Lucas Simonne, Nathalie Pernelle, Fatiha Saïs, Rallou Thomopoulos
2022 conf
IC
Lucas Simonne, Nathalie Pernelle, Fatiha Saïs, Rallou Thomopoulos
2022 J jnl
Frontiers Artif. Intell.
Romy Lynn Chaib, Catherine Macombe, Rallou Thomopoulos
2021 conf
RIVF
François Ledoyen, Rallou Thomopoulos, Stéphane Couture, Loïc Sadou, Patrick Taillandier
2021 conf
ESSA
Loïc Sadou, Stéphane Couture, Rallou Thomopoulos, Patrick Taillandier
2021 B conf
K-CAP
Lucas Simonne, Nathalie Pernelle, Fatiha Saïs, Rallou Thomopoulos
2021 J jnl
J. Artif. Soc. Soc. Simul.
Patrick Taillandier, Nicolas Salliou, Rallou Thomopoulos
2021 J jnl
Rev. Ouverte Intell. Artif.
Loïc Sadou, Stéphane Couture, Rallou Thomopoulos, Patrick Taillandier
2019 conf
ESSA
Patrick Taillandier, Nicolas Salliou, Rallou Thomopoulos
2018 J jnl
Int. J. Agric. Environ. Inf. Syst.
Nikos Karanikolas, Pierre Bisquert, Patrice Buche, Christos Kaklamanis, Rallou Thomopoulos
2018 C conf
WETICE
Fatiha Saïs, Rallou Thomopoulos, Anderson Carlos Ferreira Da Silva
2018 J jnl
Ecol. Informatics
Bruno Yun, Pierre Bisquert, Patrice Buche, Madalina Croitoru, Valérie Guillard, Rallou Thomopoulos
2018 Misc conf
ICCS
Bruno Yun, Rallou Thomopoulos, Pierre Bisquert, Madalina Croitoru
2018 conf
SGAI Conf.
Nikos Karanikolas, Madalina Croitoru, Pierre Bisquert, Christos Kaklamanis, Rallou Thomopoulos, Bruno Yun
2018 J jnl
Int. J. Agric. Environ. Inf. Syst.
Rallou Thomopoulos, Bernard Moulin, Laurent Bedoussac
2017 B conf
IDA
Bruno Yun, Srdjan Vesic, Madalina Croitoru, Pierre Bisquert, Rallou Thomopoulos
2017 conf
IEA/AIE (2)
Rallou Thomopoulos, Bernard Moulin, Laurent Bedoussac
2017 conf
IEA/AIE (2)
Rallou Thomopoulos, Dominique Paturel
2016 conf
IPMU (1)
Madalina Croitoru, Patrice Buche, Brigitte Charnomordic, Jérôme Fortin, Hazaël Jones, Pascal Neveu, Danai Symeonidou, Rallou Thomopoulos
2016 conf
EGC
Rallou Thomopoulos, Sébastien Gaucel, Bernard Moulin
2016 conf
EGC
Fatiha Saïs, Rallou Thomopoulos
2015 J jnl
Ecol. Informatics
Rallou Thomopoulos, Madalina Croitoru, Nouredine Tamani
2015 B conf
RCIS
Rallou Thomopoulos, Ahmed Chadli, Madalina Croitoru, Joël Abécassis, Gerard Brochoire, Hubert Chiron
2015 B conf
PRIMA
Madalina Croitoru, Rallou Thomopoulos, Srdjan Vesic
2015 conf
EGC
Ioanna Giannopoulou, Fatiha Saïs, Rallou Thomopoulos
2014 conf
IPMU (1)
Madalina Croitoru, Rallou Thomopoulos, Nouredine Tamani
2014 J jnl
Knowl. Based Syst.
Fatiha Saïs, Rallou Thomopoulos
2013 book
Rallou Thomopoulos
2013 J jnl
Rev. d'Intelligence Artif.
Rallou Thomopoulos, Madalina Croitoru
2013 J jnl
Expert Syst. Appl.
Jean-Rémi Bourguet, Rallou Thomopoulos, Marie-Laure Mugnier, Joël Abécassis
2013 J jnl
Inf. Sci.
Rallou Thomopoulos, Sébastien Destercke, Brigitte Charnomordic, Iyan Johnson, Joël Abécassis
2013 J jnl
Rev. d'Intelligence Artif.
Patrice Buche, Madalina Croitoru, Jérôme Fortin, Patricio Mosse, Nouredine Tamani, Rallou Thomopoulos
2013 ch.
Flexible Approaches in Data, Information and Knowledge Management
Patrice Buche, Sébastien Destercke, Valérie Guillard, Ollivier Haemmerlé, Rallou Thomopoulos
2011 conf
GKR
Jérôme Fortin, Rallou Thomopoulos, Jean-Rémi Bourguet, Marie-Laure Mugnier
2010 J jnl
Knowl. Based Syst.
Rallou Thomopoulos, Jean-Rémi Bourguet, Bernard Cuq, Amadou Ndiaye
2010 C conf
KSEM
Iyan Johnson, Joël Abécassis, Brigitte Charnomordic, Sébastien Destercke, Rallou Thomopoulos
2010 conf
OTM Conferences (2)
Fatiha Saïs, Rallou Thomopoulos, Sébastien Destercke
2010 conf
FoIKS
Jean-Rémi Bourguet, Leila Amgoud, Rallou Thomopoulos
2009 Misc conf
ICCS
Jean-François Baget, Madalina Croitoru, Jérôme Fortin, Rallou Thomopoulos
2009 ch.
Encyclopedia of Data Warehousing and Mining
Rallou Thomopoulos
2009 Misc conf
ICCS
Madalina Croitoru, Rallou Thomopoulos
2008 Misc conf
ICCS
Jean-François Baget, Olivier Corby, Rose Dieng-Kuntz, Catherine Faron-Zucker, Fabien Gandon, Alain Giboin, Alain Gutierrez, Michel Leclère, Marie-Laure Mugnier, Rallou Thomopoulos
2008 ch.
Handbook of Research on Fuzzy Information Processing in Databases
Rallou Thomopoulos, Patrice Buche, Ollivier Haemmerlé
2008 conf
ICCS Supplement
Jean-Rémi Bourguet, Bernard Cuq, Amadou Ndiaye, Rallou Thomopoulos
2008 conf
OTM Conferences (2)
Fatiha Saïs, Rallou Thomopoulos
2008 conf
EDA
Fatiha Saïs, Rallou Thomopoulos
2007 Misc conf
ICCS
Rallou Thomopoulos, Jean-François Baget, Ollivier Haemmerlé
2007 J jnl
J. Intell. Inf. Syst.
Ollivier Haemmerlé, Patrice Buche, Rallou Thomopoulos
2006 conf
EGC
Rallou Thomopoulos, Patrice Buche, Ollivier Haemmerlé, Frédéric Mabille, Nongyao Mueangdee
2006 J jnl
IEEE Trans. Knowl. Data Eng.
Rallou Thomopoulos, Patrice Buche, Ollivier Haemmerlé
2006 J jnl
Fuzzy Sets Syst.
Patrice Buche, Juliette Dibie-Barthélemy, Ollivier Haemmerlé, Rallou Thomopoulos
2006 conf
C&O@ECAI
Rallou Thomopoulos, Marie-Laure Mugnier, Michel Leclère
2006 Misc conf
ICCS
Patrice Buche, Juliette Dibie-Barthélemy, Ollivier Haemmerlé, Rallou Thomopoulos
2005 conf
EDA
Patrice Buche, Juliette Dibie-Barthélemy, Ollivier Haemmerlé, Rallou Thomopoulos
2005 conf
OTM Conferences (2)
Rallou Thomopoulos
2005 J jnl
IEEE Trans. Fuzzy Syst.
Patrice Buche, Catherine Dervin, Ollivier Haemmerlé, Rallou Thomopoulos
2004 conf
EGC
Rallou Thomopoulos, Patrice Buche, Ollivier Haemmerlé
2003 Misc conf
ICCS
Rallou Thomopoulos, Patrice Buche, Ollivier Haemmerlé
2003 C conf
ISMIS
Patrice Buche, Ollivier Haemmerlé, Rallou Thomopoulos
2003 J jnl
Fuzzy Sets Syst.
Rallou Thomopoulos, Patrice Buche, Ollivier Haemmerlé
redb/extractors/js_extractors/js_context.py
← Index redb/extractors/js_extractors/js_context.py python
"""Per-sample shared state for the JavaScript extractor pipeline.

A `JSContext` is built exactly once per JS sample (in `workers.py`) and threaded
into every extractor that runs against that sample. It owns the disk read, the
decoded source text, the line-split cache, the Shannon text-entropy figure, the
shared `scan_source()` results, and the pyjsparser AST. Each of those is
computed lazily through `cached_property` so an extractor that doesn't need a
particular artefact does not pay for it.

Without this object, every JS extractor instance redoes the same disk read,
decode, scan, and (for any consumer) AST parse. With it, every extractor
shares one set of results.

`JSExtractor.__init__` accepts the context via a `context=` kwarg; if absent
(e.g. unit tests instantiating an extractor directly with `source=...`) it
builds a fresh context from the constructor arguments. Either path produces a
fully-populated context, so extractor code can always rely on
`self._context.scan` / `self._context.ast` / etc.
"""

from __future__ import annotations

import math
from collections import Counter
from dataclasses import dataclass
from functools import cached_property
from typing import Any, Dict, List, Optional

import chardet

from redb.extractors.js_extractors.js_patterns import scan_source


def decode_source(raw_bytes: bytes) -> str:
    """Decode raw JS bytes to text, honouring BOMs and falling back to chardet.

    Mirrors the historical `JSExtractor._decode_source` logic so existing tests
    continue to round-trip identically.
    """
    if not raw_bytes:
        return ""

    if raw_bytes[:3] == b"\xef\xbb\xbf":
        return raw_bytes[3:].decode("utf-8", errors="replace")
    if raw_bytes[:2] in (b"\xff\xfe", b"\xfe\xff"):
        return raw_bytes.decode("utf-16", errors="replace")

    try:
        return raw_bytes.decode("utf-8")
    except UnicodeDecodeError:
        pass

    try:
        detected = chardet.detect(raw_bytes)
        if detected and detected.get("encoding"):
            return raw_bytes.decode(detected["encoding"], errors="replace")
    except Exception:
        pass

    return raw_bytes.decode("latin-1", errors="replace")


def _text_entropy(text: str) -> float:
    """Shannon entropy of the character distribution of `text`, rounded to 4dp."""
    if not text:
        return 0.0
    counter = Counter(text)
    length = len(text)
    entropy = 0.0
    for count in counter.values():
        p = count / length
        if p > 0:
            entropy -= p * math.log2(p)
    return round(entropy, 4)


@dataclass
class JSContext:
    """Shared raw materials for one JS sample, consumed by every JS extractor.

    Cheap attributes (raw_bytes, source) are populated eagerly by the factory.
    Expensive ones (scan, ast) are cached_property — computed on first access
    and reused across every extractor that holds the same context.

    `content_type` is the magika label (e.g. `"javascript"`) carried alongside
    the source so the new code_text_content writer (and any future generic
    text-content writer) can record it without re-running magika. Defaults to
    `"javascript"` because by construction this context type is JS-specific;
    workers.py supplies the actual magika value when it builds the context.
    """

    filepath: str
    raw_bytes: bytes
    source: str
    log: Any = None
    content_type: str = "javascript"
    # Populated by JSStringsExtractor.extract() (the decoded/reconstructed
    # strings — hex/unicode/charcode/base64/concat unpacked into plaintext).
    # Read post-loop by the IOC plumbing in workers.py so any IOCs hidden
    # behind those encodings get scraped from the decoded form. Stays None
    # if JSStringsExtractor didn't run for this sample.
    decoded_strings: Optional[list] = None

    @cached_property
    def lines(self) -> List[str]:
        return self.source.splitlines() if self.source else []

    @cached_property
    def text_entropy(self) -> float:
        return _text_entropy(self.source)

    @cached_property
    def scan(self) -> Dict[str, Dict[str, object]]:
        """Result of running scan_source() exactly once over self.source."""
        return scan_source(self.source) if self.source else {}

    @cached_property
    def ast(self) -> Optional[Any]:
        """Lazy pyjsparser AST. Returns None if the parser is missing or fails.

        Extractors should treat None AST as "fall back to regex" — every
        AST-consuming extractor already handles that path.
        """
        if not self.source:
            return None
        try:
            import pyjsparser
            return pyjsparser.parse(self.source)
        except ImportError:
            if self.log is not None:
                self.log.debug("pyjsparser not installed, AST analysis skipped")
        except Exception as e:
            if self.log is not None:
                self.log.warning(f"AST parsing failed for {self.filepath}: {e}")
        return None

    @cached_property
    def deobfuscated(self) -> "tuple[Optional[str], Optional[str]]":
        """Run the configured JS deobfuscator (with jsbeautifier fallback) once
        per sample and cache the result. Returns `(text, normalizer_used)` or
        `(None, None)` if neither path produced output.

        Computed lazily on first access — samples whose pipeline never reads
        this don't pay the subprocess cost.
        """
        from redb.extractors.js_extractors.js_deobfuscator import deobfuscate
        return deobfuscate(self.source, self.log)

    @cached_property
    def scan_deobfuscated(self) -> Dict[str, Dict[str, object]]:
        """Result of running scan_source() exactly once over the deobfuscated
        text, keyed by PATTERNS only (FEATURE_PATTERNS are not consulted by
        the dual-pass consumers). Empty dict when there is no deobfuscated
        text or it equals the raw source.

        Two extractors consume the post-deobf API surface:
        `JSSuspiciousAPIsExtractor` (for revealed_by_deobf rows) and
        `JSDeobfuscationExtractor` (for the new_apis_found diff). Caching here
        means we scan the deobfuscated text once instead of twice per sample.
        """
        from redb.extractors.js_extractors.js_patterns import PATTERNS
        deobf_text, _ = self.deobfuscated
        if not deobf_text or deobf_text == self.source:
            return {}
        return scan_source(deobf_text, patterns=(PATTERNS,))

    @cached_property
    def xray(self):
        """Run @nodesecure/js-x-ray once per sample and cache the result.

        Returns an `XRayResult` (always — the function collapses every failure
        path to an empty result so callers don't have to special-case missing
        Node, missing package, timeouts, or parse errors). The
        `JSFeaturesExtractor` reads it for the obfuscator family name and for
        corroborating warning kinds; the heuristic falls back cleanly when
        `xray.obfuscator is None`.
        """
        from redb.extractors.js_extractors.js_xray import run
        return run(self.source, self.log)

    @classmethod
    def from_path(
        cls,
        filepath: str,
        log: Any = None,
        source: Optional[str] = None,
        raw_bytes: Optional[bytes] = None,
        content_type: str = "javascript",
    ) -> "JSContext":
        """Build a context from disk. `raw_bytes` and `source` are optional
        overrides — useful when the caller has already read or decoded the file.
        `content_type` is the magika label workers.py dispatched on; it lands
        on the context for the code_text_content writer to record.
        """
        if raw_bytes is None:
            with open(filepath, "rb") as f:
                raw_bytes = f.read()
        if source is None:
            source = decode_source(raw_bytes)
        return cls(
            filepath=filepath,
            raw_bytes=raw_bytes,
            source=source,
            log=log,
            content_type=content_type,
        )