Xiaojun Qi

82 papers A* 1A 9B 14C 1Misc 3Journal 33Unranked 21
YearRankTypeTitle / Venue / Authors
2026 A* conf
WWW
Soheila Farokhi, Xiaojun Qi, Hamid Karimi
2025 J jnl
CoRR
Soheila Farokhi, Xiaojun Qi, Hamid Karimi
2024 J jnl
Vis. Comput.
Hamidreza Farhadi Tolie, Mohammad Reza Faraji, Xiaojun Qi
2024 B conf
IEEE Big Data
Supriyo Sadhya, Xiaojun Qi
2024 conf
ICPR (Workshops and Challenges, 6)
Supriyo Sadhya, Xiaojun Qi
2024 conf
ASONAM (1)
Soheila Farokhi, Arash Azizian Foumani, Xiaojun Qi, Tyler Derr, Hamid Karimi
2024 B conf
IEEE Big Data
Supriyo Sadhya, Xiaojun Qi
2024 A conf
WACV
Qiuxiao Chen, Xiaojun Qi
2024 J jnl
CoRR
Ashkan Nejad, Mohammad Reza Faraji, Xiaojun Qi
2023 J jnl
IEEE Access
Meng Xu, Kuan Huang, Xiaojun Qi
2023 C conf
ICVS
Qiuxiao Chen, Hung-Shuo Tai, Pengfei Li, Ke Wang, Xiaojun Qi
2023 B conf
IEEE Big Data
Supriyo Sadhya, Xiaojun Qi
2023 B conf
DSAA
Soheila Farokhi, Aswani Yaramala, Jiangtao Huang, Muhammad Fawad Akbar Khan, Xiaojun Qi, Hamid Karimi
2023 J jnl
CoRR
Soheila Farokhi, Aswani Yaramala, Jiangtao Huang, Muhammad Fawad Akbar Khan, Xiaojun Qi, Hamid Karimi
2023 J jnl
CoRR
Qiuxiao Chen, Xiaojun Qi
2022 conf
ISBI
Meng Xu, Kuan Huang, Xiaojun Qi
2022 B conf
ICPR
Qiuxiao Chen, Xiaojun Qi, Ziqi Song
2021 A conf
WACV
Amir Hossein Farzaneh, Xiaojun Qi
2021 conf
ISBI
Meng Xu, Kuan Huang, Qiuxiao Chen, Xiaojun Qi
2021 conf
EMBC
Kuan Huang, Meng Xu, Xiaojun Qi
2021 J jnl
IET Comput. Vis.
Brendan Robeson, Mohammadreza Javanmardi, Xiaojun Qi
2021 conf
CVPR Workshops
Qiuxiao Chen, Pengfei Li, Meng Xu, Xiaojun Qi
2020 J jnl
Neural Networks
Mohammadreza Javanmardi, Xiaojun Qi
2020 J jnl
Mach. Vis. Appl.
Amir Hossein Farzaneh, Xiaojun Qi
2020 conf
CVPR Workshops
Amir Hossein Farzaneh, Xiaojun Qi
2019 conf
AIED (2)
Amir Hossein Farzaneh, Yanghee Kim, Mengxi Zhou, Xiaojun Qi
2019 J jnl
CoRR
Mohammadreza Javanmardi, Xiaojun Qi
2019 J jnl
IET Image Process.
Mohammadreza Javanmardi, Xiaojun Qi
2018 J jnl
Neurocomputing
Mohammad Reza Faraji, Xiaojun Qi
2018 A conf
ICME
Amir Hossein Farzaneh, Xiaojun Qi
2018 A conf
ICME
Mohammadreza Javanmardi, Xiaojun Qi
2018 J jnl
CoRR
Mohammadreza Javanmardi, Xiaojun Qi
2018 J jnl
Mach. Vis. Appl.
Mohammadreza Javanmardi, Xiaojun Qi
2017 J jnl
Multim. Tools Appl.
Kazuki Minemura, KokSheik Wong, Xiaojun Qi, Kiyoshi Tanaka
2016 J jnl
J. Intell. Fuzzy Syst.
Liang Peng, Xiaojun Qi
2016 J jnl
Neurocomputing
Mohammad Reza Faraji, Xiaojun Qi
2016 J jnl
Pattern Recognit.
Jiandong Tian, Xiaojun Qi, Liangqiong Qu, Yandong Tang
2016 B conf
ICIP
Liang Peng, Xiaojun Qi
2015 J jnl
J. Vis. Commun. Image Represent.
Xiaojun Qi, Xing Xin
2015 J jnl
Signal Process. Image Commun.
Simying Ong, KokSheik Wong, Xiaojun Qi, Kiyoshi Tanaka
2015 J jnl
IET Biom.
Mohammad Reza Faraji, Xiaojun Qi
2015 J jnl
IET Comput. Vis.
Mohammad Reza Faraji, Xiaojun Qi
2014 J jnl
Multim. Tools Appl.
Zhongmiao Xiao, Xiaojun Qi
2014 J jnl
IEEE Signal Process. Lett.
Mohammad Reza Faraji, Xiaojun Qi
2014 Misc conf
ICNC
Liang Peng, Yimin Yang, Xiaojun Qi, Haohong Wang
2014 B conf
ICIP
Hongkai Yu, Min Xian, Xiaojun Qi
2014 A conf
ICME
Hongkai Yu, Xiaojun Qi
2013 J jnl
Int. J. Multim. Data Eng. Manag.
Xiaojun Qi, Ran Chang
2013 A conf
ICME
Ran Chang, Xiaojun Qi
2013 conf
ICME Workshops
Mohammad Reza Faraji, Xiaojun Qi
2012 Misc conf
ICASSP
Zhongmiao Xiao, Matthew J. Clark, KokSheik Wong, Xiaojun Qi
2012 B conf
ICIP
Kazuki Minemura, Zahra Moayed, KokSheik Wong, Xiaojun Qi, Kiyoshi Tanaka
2012 B conf
ICIP
Ran Chang, Zhongmiao Xiao, KokSheik Wong, Xiaojun Qi
2011 J jnl
Trans. Comput. Sci.
Minghui Jiang, Xiaojun Qi, Pedro J. Tejada
2011 J jnl
Int. J. Intell. Syst.
Xiaojun Qi, Samuel Barrett, Ran Chang
2011 conf
ISPACS
KokSheik Wong, Simying Ong, Kiyoshi Tanaka, Xiaojun Qi
2011 B conf
ICIP
Ran Chang, Xiaojun Qi
2010 B conf
ICIP
Adam D. Gilbert, Ran Chang, Xiaojun Qi
2010 Misc conf
ICASSP
Scott Fechser, Ran Chang, Xiaojun Qi
2009 J jnl
Trans. Data Hiding Multim. Secur.
Xiaojun Qi, Ji Qi
2009 A conf
ICME
Samuel Barrett, Ran Chang, Xiaojun Qi
2009 conf
CCCG
Pedro J. Tejada, Xiaojun Qi, Minghui Jiang
2009 B conf
ICIP
Xiaojun Qi, Xing Xin, Ran Chang
2008 A conf
ICME
Xiaojun Qi, Ran Chang
2007 J jnl
Signal Process.
KokSheik Wong, Xiaojun Qi, Kiyoshi Tanaka
2007 J jnl
Signal Process.
Xiaojun Qi, Ji Qi
2007 conf
ICIAR
Xiaojun Qi, Ran Chang
2007 J jnl
Pattern Recognit.
Xiaojun Qi, Yutao Han
2007 A conf
ICME
Matthew Royal, Ran Chang, Xiaojun Qi
2006 conf
MRCS
KokSheik Wong, Kiyoshi Tanaka, Xiaojun Qi
2006 B conf
ICIP
Jonathan Weinheimer, Xiaojun Qi, Ji Qi
2005 conf
ICIP (1)
Yutao Han, Xiaojun Qi
2005 conf
SIP
Xiaojun Qi, Ji Qi
2005 J jnl
Pattern Recognit.
Xiaojun Qi, Yutao Han
2005 J jnl
Inf. Sci.
Xiaojun Qi, John M. Tyler
2005 conf
ICIP (2)
Xiaojun Qi, KokSheik Wong
2005 conf
ICASSP (2)
Xiaojun Qi, Ji Qi
2005 conf
ICIAR
Yutao Han, Xiaojun Qi
2004 conf
ICETE (3)
Xiaojun Qi, Yutao Han
2004 conf
CISST
Rahman Mitchel Tashakkori, John M. Tyler, Oleg S. Pianykh, Xiaojun Qi
2004 conf
ICASSP (3)
Xiaojun Qi, Ji Qi
2003 B conf
DCC
Xiaojun Qi, John M. Tyler
redb/extractors/macho_extractors/macho_dylibs.py
← Index redb/extractors/macho_extractors/macho_dylibs.py python
import hashlib
import inspect
from datetime import datetime, timezone
from typing import Any

from redb.extractors.enum import Tag
from redb.extractors.macho_extractor import MachOExtractor
from redb.models.dataclasses import MachODylib


class MachODylibExtractor(MachOExtractor):

    def __init__(
        self,
        filepath,
        log,
        exporters=None,
        index_prefix=None,
        elastic_index=None,
        known_benign=False,
        known_malicious=False,
        macho=None,
    ):
        super().__init__(
            filepath,
            log,
            exporters,
            index_prefix,
            elastic_index,
            known_benign,
            known_malicious,
            macho,
        )
        self.elastic_index = self.index_prefix + "-macho_dylibs"
        self.log.debug(inspect.currentframe().f_code.co_name)

    def tag(self):
        return Tag.MACHO_DYLIB.value

    def _extract_dylibs(self):
        """Extract dynamic library information from all architectures in the MachO binary."""
        self.log.debug(inspect.currentframe().f_code.co_name)
        dylibs = []

        if not self.macho:
            return dylibs

        try:
            # Get architectures using new API (already parsed in base class)
            architectures = self.macho.get_architectures()
            if not architectures:
                return dylibs

            # Process each architecture
            for arch_name in architectures:
                # Get dylib commands using new API with architecture parameter
                dylib_commands = self.macho.get_dylib_commands(arch=arch_name)
                if not dylib_commands:
                    continue

                # Extract dylib commands for this architecture
                for dylib_cmd in dylib_commands:
                    try:
                        dylib_name = dylib_cmd.get('dylib_name', 'Unknown')
                        if isinstance(dylib_name, bytes):
                            dylib_name = dylib_name.decode('utf-8', errors='replace')

                        # Create dylib dataclass with architecture info
                        macho_dylib = MachODylib(
                            dylib_name=dylib_name,
                            dylib_timestamp=dylib_cmd.get('dylib_timestamp', 0),
                            dylib_current_version=dylib_cmd.get('dylib_current_version', 0),
                            dylib_compat_version=dylib_cmd.get('dylib_compat_version', 0),
                        )
                        # Add architecture info to the dylib
                        macho_dylib.architecture = arch_name
                        dylibs.append(macho_dylib)

                    except Exception as e:
                        self.log.warning(
                            f'Unable to process dylib "{dylib_cmd.get("dylib_name", "Unknown")}" for architecture {arch_name} in {self.hash.sha256}: {e}'
                        )
                        continue

            return dylibs

        except Exception as e:
            self.log.error(f"Error extracting MachO dylibs: {e}")
            return dylibs

    def extract(self):
        self.log.debug(inspect.currentframe().f_code.co_name)
        try:
            dylibs = self._extract_dylibs()
            return dylibs
        except Exception as e:
            self.log.error(f"Error extracting MachO dylibs: {e}")
            return None

    def prepare_export_data(self, exporter_type: str) -> Any:
        if exporter_type == "ElasticsearchExporter":
            return self.extract()
        elif exporter_type == "ClickHouseExporter":
            if not self.macho:
                return None

            # Get architectures (macho is already parsed in base class)
            try:
                architectures = self.macho.get_architectures()
                is_fat = len(architectures) > 1
            except Exception as e:
                self.log.error(f"Could not get architectures: {e}")
                return None

            data = []
            current_time = datetime.now(timezone.utc)

            # Loop through each architecture (1 for single, multiple for FAT)
            for arch_name in architectures:
                # Get architecture-specific sha256
                try:
                    arch_general_info = self.macho.get_general_info(arch=arch_name)
                    arch_header_raw = self.macho.get_macho_header(arch=arch_name)
                    arch_sha256 = arch_general_info.get('SHA256', self.sha256)
                    arch_cputype_raw = arch_header_raw.get('cputype', 0) if arch_header_raw else 0
                except Exception as e:
                    self.log.warning(f"Could not get arch-specific data for {arch_name}: {e}")
                    arch_sha256 = self.sha256
                    arch_cputype_raw = 0

                # Get dylib commands for this architecture
                dylib_commands = self.macho.get_dylib_commands(arch=arch_name)
                if not dylib_commands:
                    continue

                # Process each dylib for this architecture
                for dylib_cmd in dylib_commands:
                    try:
                        dylib_name = dylib_cmd.get('dylib_name', 'Unknown')
                        if isinstance(dylib_name, bytes):
                            dylib_name = dylib_name.decode('utf-8', errors='replace')

                        data.append([
                            arch_sha256,                          # sha256 (architecture-specific)
                            dylib_name,                           # dylib_name
                            dylib_cmd.get('dylib_timestamp', 0), # dylib_timestamp
                            dylib_cmd.get('dylib_current_version', 0), # dylib_current_version
                            dylib_cmd.get('dylib_compat_version', 0),  # dylib_compat_version
                            current_time,                         # analysis_date
                        ])
                    except Exception as e:
                        self.log.warning(
                            f'Unable to process dylib "{dylib_cmd.get("dylib_name", "Unknown")}" for architecture {arch_name}: {e}'
                        )
                        continue

            column_names = [
                'sha256',
                'dylib_name', 'dylib_timestamp', 'dylib_current_version',
                'dylib_compat_version', 'analysis_date'
            ]

            if not data:
                return None

            column_type_names = [
                'FixedString(64)',
                'String', 'UInt32', 'UInt32',
                'UInt32', 'DateTime64(3, \'UTC\')'
            ]

            return (data, column_names, column_type_names)

        return None

    def get_clickhouse_table(self) -> str:
        return "redb_macho_dylibs"