JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0803", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Computer Software", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": ", Department of Electrical Engineering, Syracuse University, Center for Science and Technology 4-283, 13244, Syracuse, New York, USA", 
          "id": "http://www.grid.ac/institutes/grid.264484.8", 
          "name": [
            ", Department of Electrical Engineering, Syracuse University, Center for Science and Technology 4-283, 13244, Syracuse, New York, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yin", 
        "givenName": "Heng", 
        "id": "sg:person.010023156265.84", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010023156265.84"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": ", Electrical Engineering and, University of California, Berkeley, Soda Hall 387, 94720, Berkeley, California, USA", 
          "id": "http://www.grid.ac/institutes/grid.47840.3f", 
          "name": [
            ", Electrical Engineering and, University of California, Berkeley, Soda Hall 387, 94720, Berkeley, California, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Song", 
        "givenName": "Dawn", 
        "id": "sg:person.01143152610.86", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01143152610.86"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2013", 
    "datePublishedReg": "2013-01-01", 
    "description": "Malicious software (i.e., malware) has become a severe threat to interconnected computer systems for decades and has caused billions of dollars damages each year. A large volume of new malware samples are discovered daily. Even worse, malware is rapidly evolving becoming more sophisticated and evasive to strike against current malware analysis and defense systems.\u00a0 Automatic Malware Analysis presents a virtualized malware analysis framework that addresses common challenges in malware analysis. In regards to this new analysis framework, a series of analysis techniques for automatic malware analysis is developed. These techniques capture intrinsic characteristics of malware, and are well suited for dealing with new malware samples and attack mechanisms.", 
    "genre": "monograph", 
    "id": "sg:pub.10.1007/978-1-4614-5523-3", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isbn": [
      "978-1-4614-5522-6", 
      "978-1-4614-5523-3"
    ], 
    "keywords": [
      "new malware samples", 
      "malware analysis", 
      "malware samples", 
      "malware analysis framework", 
      "interconnected computer systems", 
      "analysis framework", 
      "malicious software", 
      "computer systems", 
      "Based Approach", 
      "new analysis framework", 
      "malware", 
      "attack mechanism", 
      "large volumes", 
      "analysis techniques", 
      "intrinsic characteristics", 
      "framework", 
      "common challenges", 
      "severe threat", 
      "software", 
      "system", 
      "billions", 
      "technique", 
      "challenges", 
      "dollar damage", 
      "threat", 
      "defense system", 
      "analysis", 
      "decades", 
      "characteristics", 
      "regard", 
      "volume", 
      "mechanism", 
      "series", 
      "years", 
      "samples", 
      "damage", 
      "approach"
    ], 
    "name": "Automatic Malware Analysis, An Emulator Based Approach", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1044298304"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-1-4614-5523-3"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-1-4614-5523-3", 
      "https://app.dimensions.ai/details/publication/pub.1044298304"
    ], 
    "sdDataset": "books", 
    "sdDatePublished": "2022-05-10T10:35", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220509/entities/gbq_results/book/book_23.jsonl", 
    "type": "Book", 
    "url": "https://doi.org/10.1007/978-1-4614-5523-3"
  }
]

Download the RDF metadata as:  json-ld nt turtle xml License info

This table displays all metadata directly associated to this object as RDF triples.

101 TRIPLES      21 PREDICATES      63 URIs      55 LITERALS      5 BLANK NODES