Manu Goyal

41 papers B 3Journal 29Unranked 9
YearRankTypeTitle / Venue / Authors
2024 conf
ISBI
Yuyang Hu, Satya V. V. N. Kothapalli, Weijie Gan, Alexander L. Sukstanskii, Gregory F. Wu, Manu Goyal, Dmitriy A. Yablonskiy, Ulugbek S. Kamilov
2024 J jnl
CoRR
Manu Goyal, Jonathan D. Marotti, Adrienne A. Workman, Elaine P. Kuhn, Graham M. Tooker, Seth K. Ramin, Mary D. Chamberlin, Roberta M. diFlorio-Alexander, Saeed Hassanpour
2023 J jnl
CoRR
Manu Goyal, Laura J. Tafe, James X. Feng, Kristen E. Muller, Liesbeth Hondelink, Jessica L. Bentz, Saeed Hassanpour
2022 conf
Computer-Aided Diagnosis
Manu Goyal, Junyu Guo, Lauren Hinojosa, Keith Hulsey, Ivan Pedrosa
2022 conf
MIUA
Manu Goyal, Neil D. Reeves, Satyan Rajbhandari, Moi Hoon Yap
2022 J jnl
CoRR
Moi Hoon Yap, Connah Kendrick, Neil D. Reeves, Manu Goyal, Joseph M. Pappachan, Bill Cassidy
2021 J jnl
CoRR
Manu Goyal, Junyu Guo, Lauren Hinojosa, Keith Hulsey, Ivan Pedrosa
2021 J jnl
Comput. Biol. Medicine
Moi Hoon Yap, Ryo Hachiuma, Azadeh Alavi, Raphael Brüngel, Bill Cassidy, Manu Goyal, Hongtao Zhu, Johannes Rückert, Moshe Olshansky, Xiao Huang, Hideo Saito, Saeed Hassanpour, Christoph M. Friedrich, David B. Ascher, Anping Song, Hiroki Kajita, David Gillespie, Neil D. Reeves, Joseph M. Pappachan, Claire O'Shea, Eibe Frank
2021 conf
DFUC@MICCAI
Moi Hoon Yap, Connah Kendrick, Neil D. Reeves, Manu Goyal, Joseph M. Pappachan, Bill Cassidy
2021 B conf
AIME
Manu Goyal, Judith Austin-Strohbehn, Sean J. Sun, Karen Rodriguez, Jessica M. Sin, Yvonne Y. Cheung, Saeed Hassanpour
2020 J jnl
CoRR
Manu Goyal, Saeed Hassanpour
2020 J jnl
Comput. Biol. Medicine
Manu Goyal, Thomas Knackstedt, Shaofeng Yan, Saeed Hassanpour
2020 J jnl
Artif. Intell. Medicine
Moi Hoon Yap, Manu Goyal, Fatima Osman, Robert Martí, Erika R. E. Denton, Arne Juette, Reyer Zwiggelaar
2020 J jnl
IEEE Trans. Emerg. Top. Comput. Intell.
Manu Goyal, Neil D. Reeves, Adrian K. Davison, Satyan Rajbhandari, Jennifer Spragg, Moi Hoon Yap
2020 J jnl
CoRR
Moi Hoon Yap, Ryo Hachiuma, Azadeh Alavi, Raphael Brüngel, Manu Goyal, Hongtao Zhu, Bill Cassidy, Johannes Rückert, Moshe Olshansky, Xiao Huang, Hideo Saito, Saeed Hassanpour, Christoph M. Friedrich, David B. Ascher, Anping Song, Hiroki Kajita, David Gillespie, Neil D. Reeves, Joseph Pappachan, Claire O'Shea, Eibe Frank
2020 conf
BIOINFORMATICS
Manu Goyal, Moi Hoon Yap, Saeed Hassanpour
2020 J jnl
Comput. Biol. Medicine
Manu Goyal, Neil D. Reeves, Satyan Rajbhandari, Naseer Ahmad, Chuan Wang, Moi Hoon Yap
2020 J jnl
CoRR
Manu Goyal, Judith Austin-Strohbehn, Sean J. Sun, Karen Rodriguez, Jessica M. Sin, Yvonne Y. Cheung, Saeed Hassanpour
2020 J jnl
IEEE Access
Manu Goyal, Amanda Oakley, Priyanka Bansal, Darren Dancey, Moi Hoon Yap
2019 J jnl
CoRR
Manu Goyal, Thomas Knackstedt, Shaofeng Yan, Amanda Oakley, Saeed Hassanpour
2019 J jnl
CoRR
Manu Goyal, Moi Hoon Yap
2019 J jnl
Manag. Sci.
Krishnan S. Anand, Manu Goyal
2019 J jnl
CoRR
Manu Goyal, Neil D. Reeves, Satyan Rajbhandari, Naseer Ahmad, Chuan Wang, Moi Hoon Yap
2019 J jnl
IEEE J. Biomed. Health Informatics
Manu Goyal, Neil D. Reeves, Satyan Rajbhandari, Moi Hoon Yap
2019 conf
Biomedical Applications in Molecular, Structural, and Functional Imaging
Manu Goyal, Jiahua Ng, Amanda Oakley, Moi Hoon Yap
2019 conf
Biomedical Applications in Molecular, Structural, and Functional Imaging
Jiahua Ng, Manu Goyal, Brett Hewitt, Moi Hoon Yap
2018 conf
Biomedical Applications in Molecular, Structural, and Functional Imaging
Moi Hoon Yap, Manu Goyal, Fatima Osman, Ezak Ahmad, Robert Martí, Erika R. E. Denton, Arne Juette, Reyer Zwiggelaar
2018 J jnl
CoRR
Manu Goyal, Jiahua Ng, Moi Hoon Yap
2018 J jnl
CoRR
Manu Goyal, Moi Hoon Yap
2018 J jnl
CoRR
Ezak Ahmad, Manu Goyal, Jamie S. McPhee, Hans Degens, Moi Hoon Yap
2017 J jnl
CoRR
Omaima FathElrahman Osman, Remah Mutasim Ibrahim Elbashir, Imad Eldain Abbass, Connah Kendrick, Manu Goyal, Moi Hoon Yap
2017 B conf
SMC
Omaima FathElrahman Osman, Remah Mutasim Ibrahim Elbashir, Imad Eldain Abbass, Connah Kendrick, Manu Goyal, Moi Hoon Yap
2017 J jnl
CoRR
Manu Goyal, Neil D. Reeves, Adrian K. Davison, Satyan Rajbhandari, Jennifer Spragg, Moi Hoon Yap
2017 conf
ICIAR
Jhan S. Alarifi, Manu Goyal, Adrian K. Davison, Darren Dancey, Rabia Khan, Moi Hoon Yap
2017 J jnl
CoRR
Manu Goyal, Neil D. Reeves, Satyan Rajbhandari, Jennifer Spragg, Moi Hoon Yap
2017 B conf
SMC
Manu Goyal, Moi Hoon Yap, Neil D. Reeves, Satyan Rajbhandari, Jennifer Spragg
2017 J jnl
CoRR
Manu Goyal, Moi Hoon Yap
2013 J jnl
Manag. Sci.
Anandasivam Gopal, Manu Goyal, Serguei Netessine, Matthew J. Reindorp
2011 J jnl
Manuf. Serv. Oper. Manag.
Manu Goyal, Serguei Netessine
2009 J jnl
Manag. Sci.
Krishnan S. Anand, Manu Goyal
2007 J jnl
Manag. Sci.
Manu Goyal, Serguei Netessine
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"