Haiyue Yuan

42 papers A 1B 1C 1Misc 1Journal 25Unranked 11
YearRankTypeTitle / Venue / Authors
2026 J jnl
CoRR
Haiyue Yuan, Shujun Li, Fatima Gillani, Dongmei Cao, Xiao Ma
2026 J jnl
CoRR
Haiyue Yuan, Nikolay Matyunin, Ali Raza, Shujun Li
2025 J jnl
IEEE Trans. Instrum. Meas.
Yuhuan Luo, Xiuqin Chu, Haiyue Yuan, Tao Wei, Yuhao Huang, Jun Wang, Feng Wu, Yushan Li
2025 J jnl
Inf.
Rahime Belen Saglam, Haiyue Yuan, Maria Sophia Heering, Ramsha Ashraf, Shujun Li
2025 J jnl
Appl. Soft Comput.
Xiaowei Gu, Gareth D. Howells, Haiyue Yuan
2025 J jnl
IEEE Trans. Instrum. Meas.
Jun Wang, Tao Wei, Jianmin Lu, Yan Xu, Aobo Li, Haiyue Yuan, Yuhuan Luo, Xiuqin Chu
2025 J jnl
Inf.
Maria Sophia Heering, Haiyue Yuan, Shujun Li
2024 conf
ITSC
Haiyue Yuan, Ali Raza, Nikolay Matyunin, Jibesh Patra, Shujun Li
2024 J jnl
CoRR
Haiyue Yuan, Ali Raza, Nikolay Matyunin, Jibesh Patra, Shujun Li
2024 conf
HCI (55)
David M. Frohlich, Haiyue Yuan, Emily Corrigan-Kavanagh, Elisa Mameli, Caroline Scarles, Radu A. Sporea, George Revill, Alan W. Brown, Miroslaw Bober
2024 J jnl
CoRR
Kai-Fung Chu, Haiyue Yuan, Jinsheng Yuan, Weisi Guo, Nazmiye Balta-Ozkan, Shujun Li
2024 J jnl
IEEE Intell. Transp. Syst. Mag.
Kai-Fung Chu, Haiyue Yuan, Jinsheng Yuan, Weisi Guo, Nazmiye Balta-Ozkan, Shujun Li
2024 J jnl
Inf. Sci.
Xiaowei Gu, Gareth Howells, Haiyue Yuan
2024 J jnl
IEEE Trans. Circuits Syst. I Regul. Pap.
Yuhuan Luo, Jun Wang, Haiyue Yuan, Tao Wei, Yuhao Huang, Feng Wu, Yang Liu, Xiuqin Chu
2024 J jnl
Sensors
Jingling Mei, Haiyue Yuan, Xinxin Guo, Xiuqin Chu, Lei Ding
2023 Misc conf
SAC
Jamie Knott, Haiyue Yuan, Matthew Boakes, Shujun Li
2023 J jnl
CoRR
Sam Parker, Haiyue Yuan, Shujun Li
2023 C conf
VizSec
Sam Parker, Haiyue Yuan, Shujun Li
2023 conf
ITSC
Maria Sophia Heering, Haiyue Yuan, Shujun Li
2023 J jnl
CoRR
Maria Sophia Heering, Haiyue Yuan, Shujun Li
2023 conf
CAiSE Forum
Haiyue Yuan, Matthew Boakes, Xiao Ma, Dongmei Cao, Shujun Li
2023 J jnl
CoRR
Haiyue Yuan, Matthew Boakes, Xiao Ma, Dongmei Cao, Shujun Li
2023 J jnl
CoRR
Enes Altuncu, Jason R. C. Nurse, Meryem Bagriacik, Sophie Kaleba, Haiyue Yuan, Lisa Bonheme, Shujun Li
2022 conf
DSC
Haiyue Yuan, Shujun Li
2022 J jnl
CoRR
Jamie Knott, Haiyue Yuan, Matthew Boakes, Shujun Li
2022 J jnl
CoRR
Haiyue Yuan, Enes Altuncu, Shujun Li, Can Baskent
2021 J jnl
ACM Trans. Comput. Hum. Interact.
Haiyue Yuan, Shujun Li, Patrice Rusconi
2020 book
Haiyue Yuan, Shujun Li, Patrice Rusconi
2020 J jnl
ACM Trans. Priv. Secur.
Benjamin Zi Hao Zhao, Hassan Jameel Asghar, Mohamed Ali Kâafar, Francesca Trevisan, Haiyue Yuan
2020 J jnl
CoRR
Benjamin Zi Hao Zhao, Hassan Jameel Asghar, Mohamed Ali Kâafar, Francesca Trevisan, Haiyue Yuan
2019 J jnl
EAI Endorsed Trans. Security Safety
Saeed Ibrahim Alqahtani, Shujun Li, Haiyue Yuan, Patrice Rusconi
2019 J jnl
J. Electron. Publ.
David M. Frohlich, Emily Corrigan-Kavanagh, Mirek Bober, Haiyue Yuan, Radu A. Sporea, Brice Le Borgne, Caroline Scarles, George Revill, Jan van Duppen, Alan W. Brown, Megan Beynon
2017 conf
HCI (22)
Nouf Aljaffan, Haiyue Yuan, Shujun Li
2017 conf
HCI (22)
Haiyue Yuan, Shujun Li, Patrice Rusconi, Nouf Aljaffan
2014 conf
3DTV-Conference
Haiyue Yuan, Janko Calic, Ahmet M. Kondoz
2014 B conf
ICIP
Haiyue Yuan, Janko Calic, Ahmet M. Kondoz
2013 conf
ICME Workshops
Haiyue Yuan, Janko Calic, Anil Fernando, Ahmet M. Kondoz
2013 A conf
ICME
Haiyue Yuan, Janko Calic, Anil Fernando, Ahmet M. Kondoz
2013
Haiyue Yuan
2012 J jnl
Adv. Hum. Comput. Interact.
Haiyue Yuan, Janko Calic, Ahmet M. Kondoz
2012 conf
3DTV-Conference
Haiyue Yuan, Janko Calic, Ahmet M. Kondoz
2012 conf
ICME Workshops
Haiyue Yuan, Janko Calic, Anil Fernando, Ahmet M. Kondoz
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"