Xiaohui Hou

32 papers A* 2A 1Journal 25Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
Unmanned Syst.
Bo Zhang, Xiaohui Hou, Wei Wu, Minggang Gan
2026 J jnl
IEEE Trans. Veh. Technol.
Xiaohui Hou, Minggang Gan, Wei Wu, Yuan Ji, Shiyue Zhao, Jie Chen
2026 J jnl
Expert Syst. Appl.
Wei Wu, Xiaohui Hou, Minggang Gan, Jie Chen
2025 conf
HCI (76)
Zihan Mei, Qimeng Mei, Jun Liu, Xiaohui Hou
2025 J jnl
IEEE Trans. Intell. Transp. Syst.
Xiaohui Hou, Minggang Gan, Wei Wu, Yuan Ji, Shiyue Zhao, Jie Chen
2025 J jnl
Expert Syst. Appl.
Xiaohui Hou, Minggang Gan, Wei Wu, Tiantong Zhao, Jie Chen
2025 J jnl
CoRR
Shiyue Zhao, Junzhi Zhang, Neda Masoud, Jianxiong Li, Yinan Zheng, Xiaohui Hou
2025 J jnl
IEEE Trans. Cybern.
Xiaohui Hou, Minggang Gan, Wei Wu, Shiyue Zhao, Yuan Ji, Jie Chen
2024 J jnl
IEEE Trans. Intell. Transp. Syst.
Shiyue Zhao, Junzhi Zhang, Xiaoxia He, Chengkun He, Xiaohui Hou, Heye Huang, Jinheng Han
2024 conf
WWW (Companion Volume)
Ganjun Liu, Xiaohui Hou, Meng Ge, Tao Zhang, Haizhou Li
2024 J jnl
IEEE Trans. Ind. Electron.
Shiyue Zhao, Junzhi Zhang, Chengkun He, Xiaohui Hou, Heye Huang
2024 J jnl
Adv. Eng. Informatics
Shiyue Zhao, Junzhi Zhang, Chengkun He, Yuan Ji, Heye Huang, Xiaohui Hou
2024 J jnl
IEEE Trans. Intell. Transp. Syst.
Xiaohui Hou, Minggang Gan, Wei Wu, Yuan Ji, Shiyue Zhao, Jie Chen
2024 A conf
INTERSPEECH
Haojie Zhang, Tao Zhang, Ganjun Liu, Dehui Fu, Xiaohui Hou, Ying Lv
2024 J jnl
Complex.
Song Chen, Rui Yang, Xiaohui Hou, Jingwen Zhao
2024 J jnl
Knowl. Based Syst.
Xiaohui Hou, Minggang Gan, Wei Wu, Chenyu Wang, Yuan Ji, Shiyue Zhao
2024 J jnl
IEEE J. Biomed. Health Informatics
Ganjun Liu, Tao Zhang, Xiaonan Liu, Xiaohui Hou, Biyun Ding, Dehui Fu, Zhibo Pang
2024 J jnl
Adv. Eng. Informatics
Xiaohui Hou, Minggang Gan, Wei Wu, Tiantong Zhao, Jie Chen
2023 J jnl
IEEE Trans. Veh. Technol.
Jinheng Han, Junzhi Zhang, Chengkun He, Chen Lv, Xiaohui Hou, Yuan Ji
2023 J jnl
IEEE Trans. Veh. Technol.
Yuan Ji, Junzhi Zhang, Chen Lv, Chengkun He, Xiaohui Hou, Jinheng Han
2023 J jnl
IEEE Trans. Intell. Transp. Syst.
Yuan Ji, Junzhi Zhang, Chen Lv, Chengkun He, Hao Chen, Jinheng Han, Xiaohui Hou
2023 J jnl
IEEE Trans. Intell. Transp. Syst.
Jinheng Han, Junzhi Zhang, Chengkun He, Chen Lv, Chao Li, Yuan Ji, Xiaohui Hou
2023 J jnl
Adv. Eng. Informatics
Xiaohui Hou, Minggang Gan, Junzhi Zhang, Shiyue Zhao, Yuan Ji
2023 J jnl
Adv. Eng. Informatics
Xiaohui Hou, Minggang Gan, Junzhi Zhang, Shiyue Zhao, Yuan Ji
2022 J jnl
Adv. Eng. Informatics
Xiaohui Hou, Junzhi Zhang, Chengkun He, Yuan Ji, Junfeng Zhang, Jinheng Han
2021 J jnl
Complex.
Xiaohui Hou, Wei He, Kong-Lin Ke
2021 conf
ICAIIS
Xiaohui Hou, Yuan Ji, Weilong Liu, Jinheng Han, Junzhi Zhang, Chengkun He
2020 J jnl
IEEE Trans. Circuits Syst. Video Technol.
Fulin Tang, Yihong Wu, Xiaohui Hou, Haibin Ling
2020 A* conf
CVPR
Tao Wang, He Liu, Yidong Li, Yi Jin, Xiaohui Hou, Haibin Ling
2019 A* conf
ICCV
Tao Wang, Haibin Ling, Congyan Lang, Songhe Feng, Xiaohui Hou
2018 J jnl
Complex.
Yang Liu, Xiaohui Hou
2010 conf
Geoinformatics
Lianjun Zhang, Jing Zhang, Dapeng Zhang, Xiaohui Hou, Gang Yang
redb/extractors/ioc_extractor/ioc_extractor.py
← Index redb/extractors/ioc_extractor/ioc_extractor.py python
"""
IOC Extractor - Extractor class for extracting IOCs from decompilation results.

This extractor works with in-memory data from DecompileBinja, following the
standard Extractor pattern to support both ClickHouse and PrintExporter (dry-run).

Usage:
    # After DecompileBinja completes:
    ioc_extractor = IOCExtractorFromResults(
        analysis_results=decompiler.analysis_results,
        sha256=sha256,
        log=logger,
        exporters=exporters,
        index_prefix=index_prefix
    )
    ioc_extractor.export_data()
"""

import inspect
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, List, Dict, Optional

from redb.extractors.enum import Tag
from redb.extractors.database_exporters import DatabaseExporter

# Import the IOCScraper and related classes from standalone module
from redb.extractors.ioc_extractor.standalone_ioc_extractor import (
    IOCScraper,
    IOCType,
    SourceType,
    ExtractedIOC,
)
from typing import Set


class IOCExtractorFromResults:
    """
    Extracts IOCs from in-memory decompilation results.

    This follows a simplified Extractor pattern but doesn't inherit from Extractor
    since it doesn't read from a binary file - instead it takes already-processed
    analysis results from DecompileBinja.
    """

    def __init__(
        self,
        analysis_results: Dict[str, Any],
        sha256: str,
        log: Any,
        exporters: Optional[List[DatabaseExporter]] = None,
        index_prefix: Optional[str] = None,
        tld_file: Optional[Path] = None,
        suppress_types: Optional[Set[IOCType]] = None,
        js_context: bool = False,
    ):
        """
        Initialize IOC Extractor with analysis results.

        Args:
            analysis_results: Dict containing 'strings' and 'decompiled' lists from DecompileBinja
            sha256: Sample SHA256 hash
            log: Logger instance
            exporters: List of database exporters (ClickHouse, Print, etc.)
            index_prefix: Index prefix for database
            tld_file: Optional path to TLD list file
            js_context: When True, the underlying IOCScraper rejects FQDN
                candidates that match JS object-access syntax (see
                JS_FP_TLDS / JS_FP_SLDS). Set this for the JS pipeline only;
                APK suppresses FQDN entirely via suppress_types and binary
                callers leave it disabled.
        """
        self.log = log
        self.log.debug(f"Creating {self.__class__.__name__}")
        self.analysis_results = analysis_results
        self.sha256 = sha256
        self.exporters = exporters or []
        self.index_prefix = index_prefix
        self.scraper = IOCScraper(
            tld_file, suppress_types=suppress_types, js_context=js_context,
        )
        self.extracted_iocs: List[ExtractedIOC] = []

    def extract(self) -> List[ExtractedIOC]:
        """
        Extract IOCs from strings and decompiled functions in analysis_results.

        Returns:
            List of ExtractedIOC objects
        """
        self.log.debug(inspect.currentframe().f_code.co_name)
        self.extracted_iocs = []

        # Extract from strings
        strings_count = self._extract_from_strings()

        # Extract from decompiled functions
        functions_count = self._extract_from_decompiled()

        # Extract from text-based artefact surfaces (JS, PowerShell, etc.)
        text_count = self._extract_from_text()

        self.log.info(
            f"Extracted {len(self.extracted_iocs)} IOCs for {self.sha256[:16]}... "
            f"(strings: {strings_count}, functions: {functions_count}, "
            f"text: {text_count})"
        )

        return self.extracted_iocs

    def _extract_from_strings(self) -> int:
        """Extract IOCs from sample's strings."""
        count = 0
        strings = self.analysis_results.get("strings", [])

        for s in strings:
            string_value = s.get("string", "")
            string_offset = s.get("string_offset", 0)

            if isinstance(string_value, bytes):
                string_value = string_value.decode('utf-8', errors='replace')

            for ioc in self.scraper.scrape(string_value, SourceType.STRING, str(string_offset)):
                self.extracted_iocs.append(ioc)
                count += 1

        return count

    def _extract_from_decompiled(self) -> int:
        """Extract IOCs from sample's decompiled functions.

        Supports both Binja format (key: "decompiled", fields: "decompiled_function",
        "decompiled_function_hash", "function_type") and APK format (key:
        "decompiled_content", fields: "decompiled_method", "decompiled_method_hash",
        "method_type").
        """
        count = 0

        # Binja format
        decompiled = self.analysis_results.get("decompiled", [])
        for func in decompiled:
            func_type = func.get("function_type", "UNKNOWN")
            if func_type in ("LIBRARY", "THUNK"):
                continue

            func_content = func.get("decompiled_function", "")
            func_hash = func.get("decompiled_function_hash", "unknown")

            if isinstance(func_content, bytes):
                func_content = func_content.decode('utf-8', errors='replace')

            for ioc in self.scraper.scrape(func_content, SourceType.DECOMPILED_FUNCTION, func_hash):
                self.extracted_iocs.append(ioc)
                count += 1

        # APK format (decompiled_content with method-level fields)
        decompiled_content = self.analysis_results.get("decompiled_content", [])
        for func in decompiled_content:
            func_type = func.get("method_type", "UNKNOWN")
            if func_type in ("LIBRARY", "THUNK"):
                continue

            func_content = func.get("decompiled_method", "")
            func_hash = func.get("decompiled_method_hash", "unknown")

            if isinstance(func_content, bytes):
                func_content = func_content.decode('utf-8', errors='replace')

            for ioc in self.scraper.scrape(func_content, SourceType.DECOMPILED_FUNCTION, func_hash):
                self.extracted_iocs.append(ioc)
                count += 1

        return count

    def _extract_from_text(self) -> int:
        """Extract IOCs from text-based artefact surfaces.

        Walks `analysis_results["text_raw"]` and `analysis_results["text_normalized"]`,
        each a list of `{"content": str, "content_hash": str}` dicts. Each
        list is routed through its own SourceType (`TEXT_RAW` /
        `TEXT_NORMALIZED`) so analysts can distinguish IOCs that were already
        present in the raw source from those exposed only after normalisation
        (deobfuscation/beautification). Generic across text-based formats —
        used by JS today, intended for PowerShell, Python, email body,
        extracted PDF/Office text in the future.
        """
        count = 0

        for key, source_type in (
            ("text_raw", SourceType.TEXT_RAW),
            ("text_normalized", SourceType.TEXT_NORMALIZED),
        ):
            for entry in self.analysis_results.get(key, []):
                content = entry.get("content", "")
                content_hash = entry.get("content_hash", "unknown")

                if isinstance(content, bytes):
                    content = content.decode('utf-8', errors='replace')

                for ioc in self.scraper.scrape(content, source_type, content_hash):
                    self.extracted_iocs.append(ioc)
                    count += 1

        return count

    def prepare_export_data(self, exporter_type: str) -> Any:
        """
        Prepare data for specific export type.

        Returns tuple for ClickHouse or list of dicts for Print/Elasticsearch.
        """
        self.log.debug(inspect.currentframe().f_code.co_name)

        if not self.extracted_iocs:
            return None

        now = datetime.now(timezone.utc)

        if exporter_type == "ClickHouseExporter":
            data = [
                [
                    self.sha256,
                    ioc.ioc_type.value,
                    ioc.ioc_value,
                    ioc.source_type.value,
                    ioc.source_identifier,
                    now,
                ]
                for ioc in self.extracted_iocs
            ]

            column_names = [
                "sha256",
                "ioc_type",
                "ioc_value",
                "source_type",
                "source_identifier",
                "extracted_at",
            ]

            column_type_names = [
                "FixedString(64)",
                "Enum8('ipv4'=1, 'ipv6'=2, 'fqdn'=3, 'url'=4, 'email'=5, 'server'=6, "
                "'hash_md5'=10, 'hash_sha1'=11, 'hash_sha256'=12, 'cve'=20, 'cwe'=21, 'cpe'=22, "
                "'crypto_btc'=30, 'crypto_eth'=31, 'crypto_xrp'=32, 'crypto_bch'=33, "
                "'crypto_ada'=34, 'crypto_substrate'=35, 'path_linux'=40, 'path_windows'=41, "
                "'registry_key'=42, 'onion'=50)",
                "String",
                "Enum8('decompiled_function'=1, 'disassembled_function'=2, 'string'=3, "
                "'text_raw'=4, 'text_normalized'=5)",
                "String",
                "DateTime64(3, 'UTC')",
            ]

            return (data, column_names, column_type_names)

        else:
            # For PrintExporter and others - return list of dicts
            return [
                {
                    "sha256": self.sha256,
                    "ioc_type": ioc.ioc_type.value,
                    "ioc_value": ioc.ioc_value,
                    "source_type": ioc.source_type.value,
                    "source_identifier": ioc.source_identifier,
                    "extracted_at": now.isoformat(),
                }
                for ioc in self.extracted_iocs
            ]

    def get_clickhouse_table(self) -> str:
        """Return the ClickHouse table name for IOCs."""
        return "redb_iocs"

    def tag(self) -> str:
        """Return the tag for this extractor."""
        return Tag.IOC.value if hasattr(Tag, 'IOC') else "ioc"

    def export_data(self) -> bool:
        """
        Export extracted IOCs to all configured exporters.

        Returns:
            True if export succeeded, False if failed, None if no data
        """
        self.log.debug(inspect.currentframe().f_code.co_name)

        # First extract the IOCs
        extracted = self.extract()

        if not extracted:
            self.log.debug("No IOCs extracted, skipping export")
            return None

        success = True

        from redb.extractors.database_exporters import PrintExporter, ClickHouseExporter

        for exporter in self.exporters:
            try:
                if isinstance(exporter, PrintExporter):
                    # For PrintExporter, pass the list of dicts
                    export_data = self.prepare_export_data("PrintExporter")
                    success &= exporter.export(export_data)

                elif isinstance(exporter, ClickHouseExporter):
                    # For ClickHouse, pass tuple with table info
                    export_data = self.prepare_export_data("ClickHouseExporter")
                    if export_data:
                        success &= exporter.export(
                            export_data,
                            table=self.get_clickhouse_table(),
                            column_names=export_data[1],
                            column_type_names=export_data[2]
                        )

            except Exception as e:
                self.log.error(f"Error exporting IOCs to {exporter.__class__.__name__}: {e}")
                success = False

        return success