Vasileios Iosifidis

44 papers A* 1A 1B 6Misc 1Journal 24Unranked 9
YearRankTypeTitle / Venue / Authors
2023 J jnl
Knowl. Inf. Syst.
Vasileios Iosifidis, Symeon Papadopoulos, Bodo Rosenhahn, Eirini Ntoutsi
2022 J jnl
WIREs Data Mining Knowl. Discov.
Tai Le Quy, Arjun Roy, Vasileios Iosifidis, Wenbin Zhang, Eirini Ntoutsi
2022 J jnl
CoRR
Vasileios Iosifidis, Symeon Papadopoulos, Bodo Rosenhahn, Eirini Ntoutsi
2022 J jnl
CoRR
Maryam Badar, Marco Fisichella, Vasileios Iosifidis, Wolfgang Nejdl
2022 B conf
DS
Arjun Roy, Vasileios Iosifidis, Eirini Ntoutsi
2022 J jnl
CoRR
Vasileios Iosifidis, Arjun Roy, Eirini Ntoutsi
2022 J jnl
Knowl. Inf. Syst.
Vasileios Iosifidis, Arjun Roy, Eirini Ntoutsi
2021 J jnl
CoRR
Tai Le Quy, Arjun Roy, Vasileios Iosifidis, Eirini Ntoutsi
2021 conf
DASFAA (3)
Xin Huang, Wenbin Zhang, Xuejiao Tang, Mingli Zhang, Jayachander Surbiryala, Vasileios Iosifidis, Zhen Liu, Ji Zhang
2021 J jnl
CoRR
Xin Huang, Wenbin Zhang, Yiyi Huang, Xuejiao Tang, Mingli Zhang, Jayachander Surbiryala, Vasileios Iosifidis, Zhen Liu, Ji Zhang
2021 J jnl
CoRR
Arjun Roy, Vasileios Iosifidis, Eirini Ntoutsi
2021 J jnl
CoRR
Vasileios Iosifidis, Wenbin Zhang, Eirini Ntoutsi
2020 conf
IEEE BigData
Xuejiao Tang, Jiong Qiu, Ruijun Chen, Wenbin Zhang, Vasileios Iosifidis, Zhen Liu, Wei Meng, Mingli Zhang, Ji Zhang
2020 J jnl
CoRR
Xuejiao Tang, Jiong Qiu, Ruijun Chen, Wenbin Zhang, Vasileios Iosifidis, Zhen Liu, Wei Meng, Mingli Zhang, Ji Zhang
2020 J jnl
CoRR
Eirini Ntoutsi, Pavlos Fafalios, Ujwal Gadiraju, Vasileios Iosifidis, Wolfgang Nejdl, Maria-Esther Vidal, Salvatore Ruggieri, Franco Turini, Symeon Papadopoulos, Emmanouil Krasanakis, Ioannis Kompatsiaris, Katharina Kinder-Kurlanda, Claudia Wagner, Fariba Karimi, Miriam Fernández, Harith Alani, Bettina Berendt, Tina Kruegel, Christian Heinze, Klaus Broelemann, Gjergji Kasneci, Thanassis Tiropanis, Steffen Staab
2020 J jnl
WIREs Data Mining Knowl. Discov.
Eirini Ntoutsi, Pavlos Fafalios, Ujwal Gadiraju, Vasileios Iosifidis, Wolfgang Nejdl, Maria-Esther Vidal, Salvatore Ruggieri, Franco Turini, Symeon Papadopoulos, Emmanouil Krasanakis, Ioannis Kompatsiaris, Katharina Kinder-Kurlanda, Claudia Wagner, Fariba Karimi, Miriam Fernández, Harith Alani, Bettina Berendt, Tina Kruegel, Christian Heinze, Klaus Broelemann, Gjergji Kasneci, Thanassis Tiropanis, Steffen Staab
2020 B conf
DS
Vasileios Iosifidis, Eirini Ntoutsi
2020 J jnl
CoRR
Vasileios Iosifidis, Besnik Fetahu, Eirini Ntoutsi
2020 B conf
DS
Tongxin Hu, Vasileios Iosifidis, Wentong Liao, Hang Zhang, Michael Ying Yang, Eirini Ntoutsi, Bodo Rosenhahn
2020 J jnl
CoRR
Tongxin Hu, Vasileios Iosifidis, Wentong Liao, Hang Zhang, Michael Ying Yang, Eirini Ntoutsi, Bodo Rosenhahn
2020
Vasileios Iosifidis
2020 J jnl
Knowl. Inf. Syst.
Vasileios Iosifidis, Eirini Ntoutsi
2020 J jnl
Int. J. Digit. Libr.
Pavlos Fafalios, Vasileios Iosifidis, Kostas Stefanidis, Eirini Ntoutsi
2020 conf
BIBM
Xuejiao Tang, Liuhua Zhang, Wenbin Zhang, Xin Huang, Vasileios Iosifidis, Zhen Liu, Mingli Zhang, Enza Messina, Ji Zhang
2020 J jnl
CoRR
Xuejiao Tang, Liuhua Zhang, Wenbin Zhang, Xin Huang, Vasileios Iosifidis, Zhen Liu, Mingli Zhang, Enza Messina, Ji Zhang
2020 ch.
Ausgezeichnete Informatikdissertationen
Vasileios Iosifidis
2019 A conf
CIKM
Vasileios Iosifidis, Eirini Ntoutsi
2019 J jnl
CoRR
Vasileios Iosifidis, Eirini Ntoutsi
2019 conf
IEEE BigData
Vasileios Iosifidis, Besnik Fetahu, Eirini Ntoutsi
2019 conf
DEXA (1)
Vasileios Iosifidis, Thi Ngoc Han Tran, Eirini Ntoutsi
2019 J jnl
CoRR
Vasileios Iosifidis, Thi Ngoc Han Tran, Eirini Ntoutsi
2019 Misc conf
SEMANTiCS
Simon Gottschalk, Nicolas Tempelmeier, Günter Kniesel, Vasileios Iosifidis, Besnik Fetahu, Elena Demidova
2019 J jnl
CoRR
Simon Gottschalk, Nicolas Tempelmeier, Günter Kniesel, Vasileios Iosifidis, Besnik Fetahu, Elena Demidova
2018 conf
WIMS
Damianos P. Melidis, Alvaro Veizaga Campero, Vasileios Iosifidis, Eirini Ntoutsi, Myra Spiliopoulou
2018 conf
DL4KGS@ESWC
Nilamadhaba Mohapatra, Vasileios Iosifidis, Asif Ekbal, Stefan Dietze, Pavlos Fafalios
2018 J jnl
CoRR
Nilamadhaba Mohapatra, Vasileios Iosifidis, Asif Ekbal, Stefan Dietze, Pavlos Fafalios
2018 J jnl
CoRR
Pavlos Fafalios, Vasileios Iosifidis, Kostas Stefanidis, Eirini Ntoutsi
2018 B conf
ESWC
Pavlos Fafalios, Vasileios Iosifidis, Eirini Ntoutsi, Stefan Dietze
2018 J jnl
CoRR
Pavlos Fafalios, Vasileios Iosifidis, Eirini Ntoutsi, Stefan Dietze
2017 A* conf
KDD
Vasileios Iosifidis, Eirini Ntoutsi
2017 B conf
TPDL
Pavlos Fafalios, Vasileios Iosifidis, Kostas Stefanidis, Eirini Ntoutsi
2017 B conf
TPDL
Vasileios Iosifidis, Annina Oelschlager, Eirini Ntoutsi
2016 conf
WEBIST (1)
Vasileios Iosifidis, Christos Makris
2015 conf
DEXA (2)
Kyriakos Ispoglou, Christos Makris, Yannis C. Stamatiou, Elias C. Stavropoulos, Athanasios K. Tsakalidis, Vasileios Iosifidis
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"