K. S. Ravichandran

57 papers B 1C 2Journal 46Unranked 8
YearRankTypeTitle / Venue / Authors
2024 J jnl
IEEE Trans. Engineering Management
Raghunathan Krishankumar, Sundararajan Dhruva, Muhammet Deveci, K. S. Ravichandran, Xin Wen, Bilal Bahaa Zaidan
2024 J jnl
IEEE Trans. Engineering Management
Raghunathan Krishankumar, Fatih Ecer, Arunodaya Raj Mishra, K. S. Ravichandran, Amir H. Gandomi, Samarjit Kar
2024 J jnl
Inf. Sci.
Raghunathan Krishankumar, Sundararajan Dhruva, K. S. Ravichandran, Samarjit Kar
2023 J jnl
IEEE Trans. Engineering Management
Raghunathan Krishankumar, Karthik Arun, Dragan Pamucar, K. S. Ravichandran
2023 J jnl
Appl. Soft Comput.
Raghunathan Krishankumar, Arunodaya Raj Mishra, K. S. Ravichandran, Samarjit Kar, Amir H. Gandomi, Romualdas Bausys
2023 J jnl
Oper. Res. Forum
Manish Aggarwal, Raghunathan Krishankumar, K. S. Ravichandran, Tapan Senapati, Ronald R. Yager
2023 J jnl
IEEE Internet Things J.
Raghunathan Krishankumar, Arunodaya Raj Mishra, Pratibha Rani, Fatih Ecer, K. S. Ravichandran
2023 conf
ISCMI
Mandar Chougule, Praveen K, Amritha P. P, Sangeetha Viswanathan, K. S. Ravichandran, M. Sethumadhavan, Masoumeh Rahimi, Amir H. Gandomi
2022 conf
ISCMI
V. Sangeetha, Raghunathan Krishankumar, K. S. Ravichandran, Amir H. Gandomi
2022 J jnl
IEEE Trans. Engineering Management
Pratibha Rani, Arunodaya Raj Mishra, Raghunathan Krishankumar, K. S. Ravichandran, Amir H. Gandomi
2022 J jnl
Inf. Sci.
Raghunathan Krishankumar, Arunodaya Raj Mishra, Pratibha Rani, Edmundas Kazimieras Zavadskas, K. S. Ravichandran, Samarjit Kar
2022 J jnl
Eng. Appl. Artif. Intell.
Raghunathan Krishankumar, S. Supraja Nimmagadda, Arunodaya Raj Mishra, Dragan Pamucar, K. S. Ravichandran, Amir H. Gandomi
2022 J jnl
Expert Syst. Appl.
Harish Garg, Raghunathan Krishankumar, K. S. Ravichandran
2022 J jnl
Neural Comput. Appl.
R. Krishankumaar, Arunodaya Raj Mishra, Xunjie Gou, K. S. Ravichandran
2021 J jnl
Neural Comput. Appl.
Raghunathan Krishankumar, K. S. Ravichandran, Peide Liu, Samarjit Kar, Amir H. Gandomi
2021 J jnl
Soft Comput.
Xindong Peng, Raghunathan Krishankumar, K. S. Ravichandran
2021 J jnl
Appl. Soft Comput.
Arunodaya Raj Mishra, Pratibha Rani, Raghunathan Krishankumar, K. S. Ravichandran, Samarjit Kar
2021 J jnl
Soft Comput.
Raghunathan Krishankumar, Pratibha Rani, K. S. Ravichandran, Manish Aggarwal, Xindong Peng
2021 J jnl
Int. J. Intell. Syst.
R. Sivagami, Raghunathan Krishankumar, V. Sangeetha, K. S. Ravichandran, Samarjit Kar, Amir H. Gandomi
2021 J jnl
Neural Comput. Appl.
Raghunathan Krishankumar, Karthik Arun, Arun Kumar, Pratibha Rani, K. S. Ravichandran, Amir H. Gandomi
2021 J jnl
Soft Comput.
Raghunathan Krishankumar, K. S. Ravichandran, Samarjit Kar, Pankaj Gupta, Mukesh Kumar Mehlawat
2021 J jnl
Soft Comput.
V. Sangeetha, Raghunathan Krishankumar, K. S. Ravichandran, Samarjit Kar
2021 J jnl
Soft Comput.
Raghunathan Krishankumar, Arunodaya Raj Mishra, K. S. Ravichandran, Samarjit Kar, Pankaj Gupta, Mukesh Kumar Mehlawat
2021 J jnl
Appl. Soft Comput.
Pratibha Rani, Arunodaya Raj Mishra, Raghunathan Krishankumar, K. S. Ravichandran, Samarjit Kar
2020 J jnl
Soft Comput.
Raghunathan Krishankumar, Premaladha Jayaraman, K. S. Ravichandran, K. R. Sekar, Manikandan Ramachandran, X. Z. Gao
2020 J jnl
Multim. Tools Appl.
Ramakrishnan Sundaram, K. S. Ravichandran, Premaladha Jayaraman, Balasubramaniam Venkatraman
2020 C conf
ICIS
Premaladha Jayaraman, Raghunathan Krishankumar, K. S. Ravichandran, Ramakrishnan Sundaram, Samarjit Kar
2020 J jnl
Neural Comput. Appl.
Raghunathan Krishankumar, K. S. Ravichandran, Manish Aggarwal, Sanjay Kumar Tyagi
2020 J jnl
Neural Comput. Appl.
Raghunathan Krishankumar, K. S. Ravichandran, V. Shyam, S. V. Sneha, Samarjit Kar, Harish Garg
2020 C conf
ICIS
Rajsekhar Reddy Manyam, R. Sivagami, Raghunathan Krishankumar, V. Sangeetha, K. S. Ravichandran, Samarjit Kar
2020 conf
SSCI
Raghunathan Krishankumar, V. Sangeetha, Pratibha Rani, K. S. Ravichandran, Amir H. Gandomi
2020 J jnl
Appl. Soft Comput.
Raghunathan Krishankumar, Y. Gowtham, M. Ifjaz Ahmed, K. S. Ravichandran, Samarjit Kar
2019 J jnl
Int. J. Fuzzy Syst.
Raghunathan Krishankumar, L. S. Subrajaa, K. S. Ravichandran, Samarjit Kar, Arsham Borumand Saeid
2019 J jnl
Symmetry
R. Sivagami, K. S. Ravichandran, Raghunathan Krishankumar, V. Sangeetha, Samarjit Kar, Xiao-Zhi Gao, Dragan Pamucar
2019 J jnl
J. Intell. Fuzzy Syst.
Raghunathan Krishankumar, R. Saranya, R. P. Nethra, K. S. Ravichandran, Samarjit Kar
2019 J jnl
J. Intell. Fuzzy Syst.
Ramakrishnan Sundaram, K. S. Ravichandran
2019 J jnl
J. Medical Imaging Health Informatics
Ramakrishnan Sundaram, Premaladha Jayaraman, R. Rangarajan, R. Rengasri, C. Rajeshwari, K. S. Ravichandran
2019 J jnl
Clust. Comput.
Rajasekhar Reddy Manyam, K. S. Ravichandran, Balasubramaniam Venkatraman, K. R. Sekar, Manikandan Ramachandran
2019 J jnl
Soft Comput.
Raghunathan Krishankumar, K. S. Ravichandran, Samarjit Kar, Pankaj Gupta, Mukesh Kumar Mehlawat
2019 J jnl
Symmetry
A. D. Shrivathsan, K. S. Ravichandran, Raghunathan Krishankumar, V. Sangeetha, Samarjit Kar, Pawel Ziemba, Jaroslaw Jankowski
2019 J jnl
Symmetry
Raghunathan Krishankumar, K. S. Ravichandran, M. Ifjaz Ahmed, Samarjit Kar, Sanjay Kumar Tyagi
2019 J jnl
J. Intell. Fuzzy Syst.
S. Arunkumar, Subramaniyaswamy Vairavasundaram, K. S. Ravichandran, Logesh Ravi
2019 J jnl
Wirel. Pers. Commun.
Logesh Ravi, V. Subramaniyaswamy, Malathi Devarajan, K. S. Ravichandran, S. Arunkumar, V. Indragandhi, Vijayakumar Varadharajan
2018 conf
ISDA (2)
V. Sangeetha, R. Sivagami, K. S. Ravichandran
2018 J jnl
Soft Comput.
Raghunathan Krishankumar, K. S. Ravichandran, K. K. Murthy, Arsham Borumand Saeid
2018 conf
ISDA (2)
R. Sivagami, J. Srihari, K. S. Ravichandran
2018 conf
ISDA (1)
Raghunathan Krishankumar, S. Shyam, R. P. Nethra, S. Srivatsa, K. S. Ravichandran
2018 J jnl
Comput. Math. Organ. Theory
Raghunathan Krishankumar, K. S. Ravichandran
2017 J jnl
Appl. Soft Comput.
Raghunathan Krishankumar, K. S. Ravichandran, Arsham Borumand Saeid
2016 J jnl
Artif. Intell. Rev.
Badrinath Narayanamurthy, G. Gopinath, K. S. Ravichandran, R. Girish Soundhar
2016 J jnl
Int. J. Adv. Intell. Paradigms
R. Seethalakshmi, K. S. Ravichandran, P. Swaminathan, A. N. Alagappan
2016 J jnl
J. Medical Syst.
Premaladha Jayaraman, K. S. Ravichandran
2014 J jnl
Neural Comput. Appl.
K. S. Ravichandran, Badrinath Narayanamurthy, Gopinath Ganapathy, Sri Ravalli, Jaladhanki Sindhura
2013 J jnl
Int. J. Softw. Eng. Knowl. Eng.
K. S. Ravichandran, K. R. Sekar, P. Suresh
2011 conf
FSKD
K. S. Ravichandran, Salem Saleh Saeed Alsheyuhi
2007 B conf
IEEE Congress on Evolutionary Computation
M. V. Judy, K. S. Ravichandran
2004 conf
International Conference on Computational Intelligence
S. Subasree, K. S. Ravichandran
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"