Insider Threat Control: Using Plagiarism Detection Algorithms to Prevent Data Exfiltration in Near Real Time

Lewellen, Todd; Silowash, George J; Costa, Daniel L.

doi:10.21236/ada610372

Cited by 4 publications

(2 citation statements)

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“…e data combining work has the following problems. First, for the sensitive data of enterprises, due to the lack of strict management of the computer network by the managers and their lack of awareness of network security, it is easy for the computer to leak information, which causes a series of subsequent security risks to damage the computer network [12]. Second, most of the understanding of policies, regulations, and standards also relies on manual combining.…”

Section: Introductionmentioning

confidence: 99%

Application Research of Intelligent Classification Technology in Enterprise Data Classification and Gradation System

Wang

Chang

et al. 2020

Complexity

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Classification and gradation system adopts different security protection schemes for different types of data by implementing classification and gradation management of data, which is an important pretechnical means for data security protection and prevention of data leakage. This paper introduces artificial intelligence classification, machine learning, and other means to learn and train enterprise documents according to the characteristics of enterprise sensitive data. The generated training model can intelligently identify and classify file streams, improving work efficiency and accuracy of classification and gradation. At the same time, the differences, advantages, and disadvantages of K-NN (K-Nearest Neighbors), DT (Decision Tree), and LinearSVC algorithms are compared. The experimental data shows that LinearSVC algorithm is applicable to high-dimensional data, with discrete, sparse data features and large number of features, which is more suitable for classification of sensitive data of enterprises.

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Section: Introductionmentioning

confidence: 99%

Application Research of Intelligent Classification Technology in Enterprise Data Classification and Gradation System

Wang

Chang

et al. 2020

Complexity

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“…• WebDLPIndexer, a Java specialists, helps with the execution of the group's information misfortune avoidance (DLP) control • WebDLP Customer advances active web solicitations to the WebDLPIndexer [9] specialists for correlation against a record of licensed innovation.…”

Section: Technical Controlsmentioning

confidence: 99%

User Behaviour Profiling in Cloud using One Class SVM: A Review

Paruchuri¹,

Kumar²,

Sridhar³

et al. 2016

IJSIA

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Distributed computing guarantees to on a very basic level change the way we utilizePCs and get to and store our own specific and business data. With these new registering and correspondences models develop new data security challenges. Existing information security structures, for instance, encryption have fizzled in imagining information theft strikes, particularly those executed by an insider to the cloud supplier. We propose a substitute methodology for securing information in the cloud utilizing adversarial mimic improvement. We screen data access in the cloud and perceive unpredictable data access outlines. Right when unapproved access is suspected and after that confirmed using test questions, we dispatch a disinformation strike by giving back a considerable measure of fake information to the attacker. This secures against the misuse of the customer's real data. Trials coordinated in a neighbor-hood archive setting give confirmation this technique may give unprecedented levels of customer data security in a Cloud space.

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Data Loss Prevention Based on Text Classification in Controlled Environments

Kongsgard

Nordbotten

Mancini

et al. 2016

Information Systems Security

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Insider Threat Control: Using Plagiarism Detection Algorithms to Prevent Data Exfiltration in Near Real Time

Abstract: This material has been approved for public release and unlimited distribution except as restricted below.

Cited by 4 publications

References 0 publications

Application Research of Intelligent Classification Technology in Enterprise Data Classification and Gradation System

Application Research of Intelligent Classification Technology in Enterprise Data Classification and Gradation System

User Behaviour Profiling in Cloud using One Class SVM: A Review

Data Loss Prevention Based on Text Classification in Controlled Environments

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