Automated Big Text Security Classification

被引:0
|
作者
Alzhrani, Khudran [1 ]
Rudd, Ethan M. [1 ,2 ]
Boult, Terrance E. [1 ,2 ]
Chow, C. Edward [1 ]
机构
[1] Univ Colorado, Dept Comp Sci, Colorado Springs, CO 80907 USA
[2] Univ Colorado, Vis & Secur Technol VAST Lab, Colorado Springs, CO 80907 USA
关键词
Security Classification; Data Leak; Insider Threats; Machine Learning;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In recent years, traditional cybersecurity safeguards have proven ineffective against insider threats. Famous cases of sensitive information leaks caused by insiders, including the WikiLeaks release of diplomatic cables and the Edward Snowden incident, have greatly harmed the U.S. government's relationship with other governments and with its own citizens. Data Leak Prevention (DLP) is a solution for detecting and preventing information leaks from within an organization's network. However, state-of-art DLP detection models are only able to detect very limited types of sensitive information, and research in the field has been hindered due to the lack of available sensitive texts. Many researchers have focused on document-based detection with artificially labeled "confidential documents" for which security labels are assigned to the entire document, when in reality only a portion of the document is sensitive. This type of whole-document based security labeling increases the chances of preventing authorized users from accessing non-sensitive information within sensitive documents. In this paper, we introduce Automated Classification Enabled by Security Similarity ( ACESS), a new and innovative detection model that penetrates the complexity of big text security classification/detection. To analyze the ACESS system, we constructed a novel dataset, containing formerly classified paragraphs from diplomatic cables made public by the WikiLeaks organization. To our knowledge this paper is the first to analyze a dataset that contains actual formerly sensitive information annotated at paragraph granularity.
引用
收藏
页码:103 / 108
页数:6
相关论文
共 50 条
  • [1] Automated Big Security Text Pruning and Classification
    Alzhrani, Khudran
    Rudd, Ethan M.
    Chow, C. Edward
    Boult, Terrance E.
    [J]. 2016 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2016, : 3629 - 3637
  • [2] Improving Text Security Classification Towards an Automated Information Guard
    Heintz, Ilana
    Grothendieck, John
    Bernardin, Fred
    Kuperman, Gregory
    [J]. 2022 IEEE MILITARY COMMUNICATIONS CONFERENCE (MILCOM), 2022,
  • [3] Multidimensional Text Warehousing for Automated Text Classification
    Kim, Jiyun
    Kim, Han-joon
    [J]. JOURNAL OF INFORMATION TECHNOLOGY RESEARCH, 2018, 11 (02) : 168 - 183
  • [4] Automated Classification of Text Sentiment
    Dufourq, Emmanuel
    Bassett, Bruce A.
    [J]. SOUTH AFRICAN INSTITUTE OF COMPUTER SCIENTISTS AND INFORMATION TECHNOLOGISTS (SACSIT 2017), 2017, : 96 - +
  • [5] Automated Classification of Security Requirements
    Jindal, Rajni
    Malhotra, Ruchika
    Jain, Abha
    [J]. 2016 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI), 2016, : 2027 - 2033
  • [6] Comparing automated text classification methods
    Hartmann, Jochen
    Huppertz, Juliana
    Schamp, Christina
    Heitmann, Mark
    [J]. INTERNATIONAL JOURNAL OF RESEARCH IN MARKETING, 2019, 36 (01) : 20 - 38
  • [7] Big Text advantages and challenges: classification perspective
    Sokolova M.
    [J]. Sokolova, Marina (sokolova@uottawa.ca), 2018, Springer Science and Business Media Deutschland GmbH (05) : 1 - 10
  • [8] Automated essay grading via text classification
    Valenti, S
    Cucchiarelli, A
    [J]. INNOVATIONS THROUGH INFORMATION TECHNOLOGY, VOLS 1 AND 2, 2004, : 550 - 552
  • [9] Improving Classification Accuracy of Automated Text Classifiers
    Rastogi, Shivam
    [J]. 2018 7TH INTERNATIONAL CONFERENCE ON RELIABILITY, INFOCOM TECHNOLOGIES AND OPTIMIZATION (TRENDS AND FUTURE DIRECTIONS) (ICRITO) (ICRITO), 2018, : 239 - 245
  • [10] Automated Classification of Variants of Norwegian by Means of Text Mining of Unannotated Text
    Overland, Fartein Th
    [J]. STUDIA UNIVERSITATIS BABES-BOLYAI PHILOLOGIA, 2020, 65 (03): : 107 - 124