Xiaohua Xiao

32 papers B 1Journal 22Unranked 9
YearRankTypeTitle / Venue / Authors
2026 J jnl
Medical Image Anal.
Xuegang Song, Kaixiang Shu, Peng Yang, Cheng Zhao, Feng Zhou, Alejandro F. Frangi, Jiuwen Cao, Xiaohua Xiao, Shuqiang Wang, Tianfu Wang, Baiying Lei
2026 J jnl
Neural Networks
Nina Cheng, Gai Li, Yu Liang, Yali Qiu, Xuegang Song, Huoyou Hu, Ee-Leng Tan, Tianfu Wang, Shuqiang Wang, Xiaohua Xiao, Shijie Zhao, Baiying Lei
2026 J jnl
Appl. Soft Comput.
Jiaqiang Li, Yukang Lei, Zhenghua Guan, Peng Yang, Haojie Song, Jing Tian, Guojun Yao, Chunhua Liang, Tianfu Wang, Xiaohua Xiao, Haijun Lei, Baiying Lei
2025 J jnl
IEEE Trans. Medical Imaging
Xuegang Song, Kaixiang Shu, Peng Yang, Cheng Zhao, Feng Zhou, Alejandro F. Frangi, Xiaohua Xiao, Lei Dong, Tianfu Wang, Shuqiang Wang, Baiying Lei
2025 J jnl
Expert Syst. Appl.
Gai Li, Yuwen Zhang, Xuegang Song, Peng Yang, Lei Dong, Yaohui Huang, Xiaohua Xiao, Tianfu Wang, Shuqiang Wang, Baiying Lei
2024 J jnl
IEEE Trans. Medical Imaging
Zifeng Qiu, Peng Yang, Chunlun Xiao, Shuqiang Wang, Xiaohua Xiao, Jing Qin, Chuan-Ming Liu, Tianfu Wang, Baiying Lei
2024 J jnl
Medical Image Anal.
Baiying Lei, Yafeng Li, Wanyi Fu, Peng Yang, Shaobin Chen, Tianfu Wang, Xiaohua Xiao, Tianye Niu, Yu Fu, Shuqiang Wang, Hongbin Han, Jing Qin
2024 conf
EMBC
Jiaqiang Li, Peng Yang, Junlong Qu, Bao Yang, Zhenghua Guan, Xuegang Song, Xiaohua Xiao, Tianfu Wang, Baiying Lei
2024 conf
BI (2)
Tuo Cai, Baiying Lei, Xueqin Yan, Cuimei Wei, Chunhua Liang, Xiaohua Xiao, Yunzhu Yang, Tianfu Wang, Peng Yang
2024 J jnl
Pattern Recognit.
Baiying Lei, Yu Liang, Jiayi Xie, You Wu, Enmin Liang, Yong Liu, Peng Yang, Tianfu Wang, Chuan-Ming Liu, Jichen Du, Xiaohua Xiao, Shuqiang Wang
2024 conf
BI (2)
Jiaqiang Li, Peng Yang, Jiuwen Cao, Zhenghua Guan, Junlong Qu, Lei Dong, Xueqin Yan, Cuimei Wei, Chunhua Liang, Xiaohua Xiao, Tianfu Wang, Baiying Lei
2024 conf
ISBI
Zhenghua Guan, Xuegang Song, Peng Yang, Jiaqiang Li, Bao Yang, Xiaohua Xiao, Chuanming Liu, Tianfu Wang, Baiying Lei
2024 J jnl
Sensors
Weibin Wang, Ling Xia, Xiaohua Xiao, Gongke Li
2024 conf
BI (2)
Zhenghua Guan, Peng Yang, Haijun Lei, Bao Yang, Xuegang Song, Lei Dong, Xueqin Yan, Cuimei Wei, Chunhua Liang, Xiaohua Xiao, Tianfu Wang, Baiying Lei
2023 J jnl
Neural Comput. Appl.
Haijun Lei, Yukang Lei, Zihao Chen, Shiqi Li, Zhongwei Huang, Feng Zhou, Ee-Leng Tan, Xiaohua Xiao, Yi Lei, Huoyou Hu, Yaohui Huang, Chien-Hung Liu, Baiying Lei
2023 J jnl
IEEE Trans. Medical Imaging
Baiying Lei, Yun Zhu, Enmin Liang, Peng Yang, Shaobin Chen, Huoyou Hu, Haoran Xie, Ziyi Wei, Fei Hao, Xuegang Song, Tianfu Wang, Xiaohua Xiao, Shuqiang Wang, Hongbin Han
2023 J jnl
Pattern Recognit.
Baiying Lei, Yun Zhu, Shuangzhi Yu, Huoyou Hu, Yanwu Xu, Guanghui Yue, Tianfu Wang, Cheng Zhao, Shaobin Chen, Peng Yang, Xuegang Song, Xiaohua Xiao, Shuqiang Wang
2023 J jnl
IEEE Trans. Medical Imaging
Xuegang Song, Feng Zhou, Alejandro F. Frangi, Jiuwen Cao, Xiaohua Xiao, Yi Lei, Tianfu Wang, Baiying Lei
2023 J jnl
Expert Syst. Appl.
Peng Yang, Wei Zheng, Qiong Yang, Xiaohua Xiao, Tianfu Wang, Baiying Lei, Ziwen Peng
2022 J jnl
Medical Image Anal.
Peng Yang, Cheng Zhao, Qiong Yang, Wei Zheng, Xiaohua Xiao, Li Shen, Tianfu Wang, Baiying Lei, Ziwen Peng
2022 J jnl
Comput. Biol. Medicine
Haijun Lei, Yuchen Zhang, Hancong Li, Zhongwei Huang, Chien-Hung Liu, Feng Zhou, Ee-Leng Tan, Xiaohua Xiao, Yi Lei, Huoyou Hu, Yaohui Huang, Baiying Lei
2022 J jnl
Knowl. Based Syst.
Baiying Lei, Yuwen Zhang, Dongdong Liu, Yanwu Xu, Guanghui Yue, Jiuwen Cao, Huoyou Hu, Shuangzhi Yu, Peng Yang, Tianfu Wang, Yali Qiu, Xiaohua Xiao, Shuqiang Wang
2022 J jnl
Expert Syst. Appl.
Baiying Lei, Enmin Liang, Mengya Yang, Peng Yang, Feng Zhou, Ee-Leng Tan, Yi Lei, Chuan-Ming Liu, Tianfu Wang, Xiaohua Xiao, Shuqiang Wang
2021 J jnl
Medical Image Anal.
Xuegang Song, Feng Zhou, Alejandro F. Frangi, Jiuwen Cao, Xiaohua Xiao, Yi Lei, Tianfu Wang, Baiying Lei
2020 J jnl
Pattern Recognit.
Baiying Lei, Mengya Yang, Peng Yang, Feng Zhou, Wen Hou, Wenbin Zou, Xia Li, Tianfu Wang, Xiaohua Xiao, Shuqiang Wang
2020 conf
MICCAI (7)
Xuegang Song, Alejandro F. Frangi, Xiaohua Xiao, Jiuwen Cao, Tianfu Wang, Baiying Lei
2020 B conf
ICPR
Zhongwei Huang, Haijun Lei, Shiqi Li, Xiaohua Xiao, Ee-Leng Tan, Baiying Lei
2020 conf
MICCAI (7)
Shuangzhi Yu, Shuqiang Wang, Xiaohua Xiao, Jiuwen Cao, Guanghui Yue, Dongdong Liu, Tianfu Wang, Yanwu Xu, Baiying Lei
2020 conf
PRIME@MICCAI
Zihao Chen, Haijun Lei, Yujia Zhao, Zhongwei Huang, Xiaohua Xiao, Yi Lei, Ee-Leng Tan, Baiying Lei
2019 J jnl
IEEE Access
Chiyu Feng, Ahmed El-Azab, Peng Yang, Tianfu Wang, Feng Zhou, Huoyou Hu, Xiaohua Xiao, Baiying Lei
2019 J jnl
IEEE J. Biomed. Health Informatics
Baiying Lei, Peng Yang, Yinan Zhuo, Feng Zhou, Dong Ni, Siping Chen, Xiaohua Xiao, Tianfu Wang
2018 conf
PRIME@MICCAI
Chiyu Feng, Ahmed El-Azab, Peng Yang, Tianfu Wang, Baiying Lei, Xiaohua Xiao
redb/extractors/macho_extractors/macho_segments.py
← Index redb/extractors/macho_extractors/macho_segments.py python
import hashlib
import inspect
import base64
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 MachOSegment


class MachOSegmentExtractor(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_segments"
        self.log.debug(inspect.currentframe().f_code.co_name)

    def _is_empty_result(self, extracted_data) -> bool:
        """
        Override: Empty segments is an ERROR, not a valid empty case.
        A valid MachO file must have segments (at minimum __PAGEZERO, __TEXT).
        """
        # Always return False - empty segments should be treated as an error
        return False

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

    def _extract_segments_for_arch(self, arch_name):
        """Extract segment information for a specific architecture."""
        self.log.debug(f"Extracting segments for architecture: {arch_name}")
        segments = []

        try:
            # Get segments using new API with architecture parameter
            segments_data = self.macho.get_segments(arch=arch_name)
            if not segments_data:
                return segments

            # Extract segments for this architecture
            for segment in segments_data:
                try:
                    segment_name = segment.get('segname', 'Unknown')

                    # Calculate segment hash
                    segment_data = self._get_segment_data(segment)
                    if segment_data:
                        seg_sha256 = hashlib.sha256(segment_data).hexdigest()
                    else:
                        seg_sha256 = ""

                    # Use entropy already calculated by machofile module, rounded to 3 decimal places
                    seg_entropy = round(segment.get('entropy', 0.0), 3)

                    # Create segment dataclass with architecture info
                    macho_segment = MachOSegment(
                        segment_name=segment_name,
                        segment_vaddr=segment.get('vaddr', 0),
                        segment_vsize=segment.get('vsize', 0),
                        segment_offset=segment.get('offset', 0),
                        segment_size=segment.get('size', 0),
                        segment_max_vm_protection=segment.get('max_vm_protection', 0),
                        segment_initial_vm_protection=segment.get('initial_vm_protection', 0),
                        segment_nsects=segment.get('nsects', 0),
                        segment_flags=segment.get('flags', 0),
                        segment_entropy=seg_entropy,
                        segment_sha256=seg_sha256,
                    )
                    # Add architecture info to the segment
                    macho_segment.architecture = arch_name
                    segments.append(macho_segment)

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

            return segments

        except Exception as e:
            self.log.error(f"Error extracting MachO segments for architecture {arch_name}: {e}")
            return segments

    def _extract_segments(self):
        """Extract segment information from all architectures in the MachO binary."""
        self.log.debug(inspect.currentframe().f_code.co_name)
        segments = []

        if not self.macho:
            return segments

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

            # Process each architecture
            for arch_name in architectures:
                arch_segments = self._extract_segments_for_arch(arch_name)
                segments.extend(arch_segments)

            return segments

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

    def _get_segment_data(self, segment):
        """Get the raw data for a segment."""
        try:
            offset = segment.get('offset', 0)
            size = segment.get('size', 0)
            
            if size == 0:
                return None
            
            # Read segment data from file
            with open(self.filepath, 'rb') as f:
                f.seek(offset)
                return f.read(size)
                
        except Exception as e:
            self.log.warning(f"Error reading segment data: {e}")
            return None

    def extract(self):
        self.log.debug(inspect.currentframe().f_code.co_name)
        try:
            segments = self._extract_segments()
            return segments
        except Exception as e:
            self.log.error(f"Error extracting MachO segments: {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:
                # Extract segments for this specific architecture
                segments = self._extract_segments_for_arch(arch_name)
                if not segments:
                    continue

                # Get architecture-specific sha256 and header info
                try:
                    arch_general_info = self.macho.get_general_info(arch=arch_name)
                    arch_sha256 = arch_general_info.get('SHA256', self.sha256)

                    # Get raw architecture value
                    arch_header_raw = self.macho.get_macho_header(arch=arch_name)
                    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

                for segment in segments:
                    data.append([
                        arch_sha256,                          # sha256 (architecture-specific)
                        segment.segment_name,                 # segment_name
                        segment.segment_vaddr,                # segment_vaddr
                        segment.segment_vsize,                # segment_vsize
                        segment.segment_offset,               # segment_offset
                        segment.segment_size,                 # segment_size
                        segment.segment_max_vm_protection,    # segment_max_vm_protection
                        segment.segment_initial_vm_protection, # segment_initial_vm_protection
                        segment.segment_nsects,               # segment_nsects
                        segment.segment_flags,                # segment_flags
                        segment.segment_entropy,              # segment_entropy
                        segment.segment_sha256,               # segment_sha256
                        current_time,                         # analysis_date
                    ])

            column_names = [
                'sha256',
                'segment_name', 'segment_vaddr', 'segment_vsize', 'segment_offset',
                'segment_size', 'segment_max_vm_protection', 'segment_initial_vm_protection',
                'segment_nsects', 'segment_flags', 'segment_entropy', 'segment_sha256',
                'analysis_date'
            ]

            if not data:
                return None

            column_type_names = [
                'FixedString(64)',
                'String', 'UInt64', 'UInt64', 'UInt64',
                'UInt64', 'UInt32', 'UInt32',
                'UInt32', 'UInt32', 'Float64', 'FixedString(64)',
                'DateTime64(3, \'UTC\')'
            ]

            return (data, column_names, column_type_names)

        return None

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