Wei Chang

43 papers A* 1A 3B 3C 4Misc 1Journal 21Unranked 10
YearRankTypeTitle / Venue / Authors
2026 J jnl
Frontiers Artif. Intell.
Hezhen Gao, Dilraba Mahmut, Fanshu Dai, Haimiao Yu, Wei Chang, Xingya Huang, Biao Zhang
2026 J jnl
CoRR
Jiang Zhang, Yubo Wang, Wei Chang, Lu Han, Xingying Cheng, Feng Zhang, Min Li, Songhao Jiang, Wei Zheng, Harry Tran, Zhen Wang, Lei Chen, Yueming Wang, Benyu Zhang, Xiangjun Fan, Bi Xue, Qifan Wang
2025 conf
VTC2025-Spring
Xuanrong Li, Nan Ma, Xiaoqi Qin, Wei Chang
2025 J jnl
CoRR
Amit Jaspal, Feng Zhang, Wei Chang, Sumit Kumar, Yubo Wang, Roni Mittleman, Qifan Wang, Weize Mao
2025 A conf
ICSME
Taizheng Wang, Yutong Wang, Wei Chang, Chunyang Ye, Hui Zhou
2025 A conf
ICWS
Taizheng Wang, Chunyang Ye, Hui Zhou, Wei Chang, Chaoyi Li
2025 conf
KDD (2)
Jiang Zhang, Sumit Kumar, Wei Chang, Yubo Wang, Feng Zhang, Weize Mao, Hanchao Yu, Aashu Singh, Min Li, Qifan Wang
2025 J jnl
CoRR
Jiang Zhang, Sumit Kumar, Wei Chang, Yubo Wang, Feng Zhang, Weize Mao, Hanchao Yu, Aashu Singh, Min Li, Qifan Wang
2024 J jnl
Soft Comput.
Meijing Hao, Wei Chang, Chonghao Xu
2024 A conf
ISSRE
Wei Chang, Chunyang Ye, Hui Zhou
2024 J jnl
IEEE Access
Xiufeng Wu, Xueli Li, Guangxing Cao, Chao Guo, Wei Chang, Zhao Wang, Shuliang Liu
2024 J jnl
Eng. Appl. Artif. Intell.
Tingrui Jiang, Lei Guo, Guopeng Sun, Wei Chang, Zhigong Yang, Yueqing Wang
2024 J jnl
Soft Comput.
DeChao Qu, Wei Chang
2023 conf
ICSS
Wentao Bai, Jun Fang, Wei Chang
2022 J jnl
Soft Comput.
Wei Chang, Wenzhong Zheng
2021 conf
DFT
Wei Chang, Yu-Guang Chen, Po-Yeh Huang, Jin-Fu Li
2021 J jnl
IEEE Trans. Multim.
Zongyi Xu, Wei Chang, Yindi Zhu, Le Dong, Huiyu Zhou, Qianni Zhang
2021 J jnl
Peer-to-Peer Netw. Appl.
Haoran Hu, Wei Chang
2020 conf
EMBC
Wei Chang, Ching-Chun Hsiao, Yen-Yin Lin, Li-An Chu, A. Lee Swindlehurst, Shi-Wei Chu, Ann-Shyn Chiang, Shun-Chi Wu
2020 B conf
ICCCN
Haoran Hu, Wei Chang
2020 B conf
AIME
Sina Rashidian, Fusheng Wang, Richard A. Moffitt, Victor Garcia, Anurag Dutt, Wei Chang, Vishwam Pandya, Janos G. Hajagos, Mary M. Saltz, Joel H. Saltz
2020 conf
ICIAR (1)
Wei Chang, Chunyang Ye, Hui Zhou
2019 A* conf
AAAI
Rui Wang, Xin Xin, Wei Chang, Kun Ming, Biao Li, Xin Fan
2018 Misc conf
SenSys
Zhou Qin, Zhihan Fang, Yunhuai Liu, Chang Tan, Wei Chang, Desheng Zhang
2018 conf
SPAC
Xiaoshuang Li, Ziyang Chen, Fenghua Zhu, Wei Chang, Chang Tan, Gang Xiong
2017 conf
CyberC
Gang Zhang, Xiaofeng Qiu, Wei Chang
2016 C conf
ICCE
Ya-Wen Cheng, Wei-Chieh Fang, Wei Chang, Li-Chun Lin, Nian-Shing Chen
2015 C conf
IEA/AIE
Wei Chang, Jia-Ling Koh
2015 J jnl
Int. Trans. Oper. Res.
Jonchi Shyu, Pang-Tien Lieu, Wei Chang
2015 J jnl
Microelectron. Reliab.
Wei Chang, Chun-Hsing Shih, Yan-Xiang Luo, Wen-Fa Wu, Chen-Hsin Lien
2014 conf
PACIS
Meihua Wei, Ling Ma, Wei Chang
2013 conf
SERE (Companion)
Wei Chang, Xiaohong Bao, Xuefei Li
2013 C conf
INDIN
Daxing Zeng, Wenjuan Lu, Chao Zhang, Wei Chang, Yulei Hou
2013 B conf
IJCNN
William Koch, Yan Meng, Munish Shah, Wei Chang, Xiaojun Yu
2010 C conf
ISPA
Ying-Kwei Ho, Wei Chang
1999 J jnl
IEEE Trans. Syst. Man Cybern. Part A
Moshe Kam, Chris Rorres, Wei Chang, Xiaoxun Zhu
1991 J jnl
IEEE Trans. Syst. Man Cybern.
Moshe Kam, Wei Chang, Qiang Zhu
1975 J jnl
IBM J. Res. Dev.
Wei Chang
1970 J jnl
IBM Syst. J.
Wei Chang
1968 J jnl
Oper. Res.
Wei Chang
1966 J jnl
IBM Syst. J.
Wei Chang
1965 J jnl
J. ACM
Wei Chang, Donald J. Wong
1965 J jnl
IBM Syst. J.
Wei Chang, Donald J. Wong
redb/extractors/macho_extractors/macho_similarity_hashes.py
← Index redb/extractors/macho_extractors/macho_similarity_hashes.py python
import inspect
from datetime import datetime, timezone
from typing import Any

from redb.extractors.enum import Tag
from redb.extractors.macho_extractor import MachOExtractor


class MachOSimilarityHashExtractor(MachOExtractor):
    """Extract Mach-O similarity hashes using machofile API.

    Similarity hashes are MD5 fingerprints of sorted, deduplicated binary components:
    - dylib_hash: MD5 of dynamic library names
    - import_hash: MD5 of imported function names
    - export_hash: MD5 of exported symbol names
    - entitlement_hash: MD5 of entitlement names and array values
    - symhash: MD5 of external undefined symbols

    For FAT binaries:
    - Inserts one row per architecture slice with per-slice hashes
    - Inserts one row for the FAT container with combined hashes

    For single-arch binaries:
    - Inserts one row with that architecture's hashes

    Note: parent_sha256 and architecture relationships are tracked in redb_basic_properties,
    not duplicated here. Use JOIN with redb_basic_properties when needed.
    """

    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_hashes"
        self.log.debug(inspect.currentframe().f_code.co_name)

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

    def _extract_similarity_hashes(self, arch_name=None):
        """Extract similarity hashes for a specific architecture."""
        self.log.debug(inspect.currentframe().f_code.co_name)

        if not self.macho:
            return None

        try:
            similarity_hashes = self.macho.get_similarity_hashes(arch=arch_name)
            return similarity_hashes if similarity_hashes else None
        except Exception as e:
            self.log.error(f"Error extracting similarity hashes for arch {arch_name}: {e}")
            return None

    def extract(self):
        self.log.debug(inspect.currentframe().f_code.co_name)
        try:
            if not self.macho:
                return None

            architectures = self.macho.get_architectures()
            if not architectures:
                return None

            if len(architectures) > 1:
                # FAT binary - return combined hashes + per-arch hashes
                results = []

                # First add combined hashes for the FAT container
                all_hashes = self.macho.get_similarity_hashes()
                combined_hashes = all_hashes.get('combined', {}) if all_hashes else {}
                if combined_hashes:
                    combined_hashes['arch_identifier'] = 'fat'
                    results.append(combined_hashes)

                # Then add per-arch hashes
                for arch_name in architectures:
                    hashes = self._extract_similarity_hashes(arch_name)
                    if hashes:
                        hashes['arch_identifier'] = arch_name
                        results.append(hashes)
                return results
            else:
                # Single architecture - return single result
                return self._extract_similarity_hashes(architectures[0])
        except Exception as e:
            self.log.error(f"Error extracting similarity hashes: {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

            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)

            # For FAT binaries, first insert a row for the container with combined hashes
            if is_fat:
                all_hashes = self.macho.get_similarity_hashes()  # Without arch returns all including 'combined'
                combined_hashes = all_hashes.get('combined', {}) if all_hashes else {}
                if combined_hashes:
                    data.append([
                        self.sha256,                                    # sha256 (FAT container)
                        combined_hashes.get('dylib_hash'),              # dylib_hash
                        combined_hashes.get('import_hash'),             # import_hash
                        combined_hashes.get('export_hash'),             # export_hash
                        combined_hashes.get('entitlement_hash'),        # entitlement_hash
                        combined_hashes.get('symhash'),                 # symhash
                        current_time,                                   # analysis_date
                    ])

            # Insert rows for each architecture slice
            for arch_name in architectures:
                # Get architecture-specific sha256
                try:
                    arch_general_info = self.macho.get_general_info(arch=arch_name)
                    arch_sha256 = arch_general_info.get('SHA256', self.sha256)
                except Exception as e:
                    self.log.warning(f"Could not get arch-specific sha256 for {arch_name}: {e}")
                    arch_sha256 = self.sha256

                # Get similarity hashes for this architecture
                similarity_hashes = self._extract_similarity_hashes(arch_name)
                if not similarity_hashes:
                    continue

                data.append([
                    arch_sha256,                                    # sha256 (arch-specific)
                    similarity_hashes.get('dylib_hash'),            # dylib_hash
                    similarity_hashes.get('import_hash'),           # import_hash
                    similarity_hashes.get('export_hash'),           # export_hash
                    similarity_hashes.get('entitlement_hash'),      # entitlement_hash
                    similarity_hashes.get('symhash'),               # symhash
                    current_time,                                   # analysis_date
                ])

            if not data:
                return None

            column_names = [
                'sha256',
                'macho_dylib_hash', 'macho_import_hash', 'macho_export_hash',
                'macho_entitlement_hash', 'macho_symhash',
                'analysis_date'
            ]

            column_type_names = [
                'FixedString(64)',
                'Nullable(FixedString(32))', 'Nullable(FixedString(32))', 'Nullable(FixedString(32))',
                'Nullable(FixedString(32))', 'Nullable(FixedString(32))',
                'DateTime64(3, \'UTC\')'
            ]

            return (data, column_names, column_type_names)

        return None

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