Data Security And Automatic Threat Detection

Teknologian nopeassa kehityksessä turvallisuus ja sääntely kehittyvät jäljessä, erityisesti tieto- sekä dataturvallisuuteen liittyvät ongelmat ovat puhuttaneet teknologia-alalla viimevuosien aikana. Tämä tutkimus on tärkeä teknologisen kehityksen havainnollistamiseksi teknologian hallintaan ja turva...

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Bibliografiset tiedot
Päätekijä: Kelo, Anton
Muut tekijät: Informaatioteknologian tiedekunta, Faculty of Information Technology, Informaatioteknologia, Information Technology, Jyväskylän yliopisto, University of Jyväskylä
Aineistotyyppi: Kandityö
Kieli:eng
Julkaistu: 2024
Aiheet:
Linkit: https://jyx.jyu.fi/handle/123456789/95682
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author Kelo, Anton
author2 Informaatioteknologian tiedekunta Faculty of Information Technology Informaatioteknologia Information Technology Jyväskylän yliopisto University of Jyväskylä
author_facet Kelo, Anton Informaatioteknologian tiedekunta Faculty of Information Technology Informaatioteknologia Information Technology Jyväskylän yliopisto University of Jyväskylä Kelo, Anton Informaatioteknologian tiedekunta Faculty of Information Technology Informaatioteknologia Information Technology Jyväskylän yliopisto University of Jyväskylä
author_sort Kelo, Anton
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description Teknologian nopeassa kehityksessä turvallisuus ja sääntely kehittyvät jäljessä, erityisesti tieto- sekä dataturvallisuuteen liittyvät ongelmat ovat puhuttaneet teknologia-alalla viimevuosien aikana. Tämä tutkimus on tärkeä teknologisen kehityksen havainnollistamiseksi teknologian hallintaan ja turvallisuuteen liittyvien näkökulmien kannalta, jotka ovat tärkeitä alan tutkimuksessa ja kehityksessä. Tutkimus tarkasteli dataturvallisuuden kehitystä erityisesti kybermaailman turvallisuuteen liittyvien elementtien yhteydessä kirjallisuuskatsauksen keinoin, käyttäen lähteinä tutkimuksia, kirjoja, sekä yksittäisiä alan kattotason organisaatioiden internetjulkaisuja. Tutkimus keskittyi kyberturvallisuuden elementeistä erityisesti uhkien havainnointiin liittyvien järjestelmien dataturvallisuuteen, sekä tarkasteli niiden kykyä toteuttaa dataturvallisuuden vaatimuksia. Dataturvallisuutta tarkisteltiin alalla yleisesti käytetyn mallin, CIA-triadin avulla, sen osa-alueita ovat luottamuksellisuus, eheys, ja saavutettavuus. Data- ja kyberturvallisuuden antaminen tekoälysovellusten käsiin on herättänyt keskustelua alalla. Tutkimus keskittyi myös tarkastelemaan, kuinka luotettavana havainnointijärjestelmiä voi pitää koostamalla tietoja järjestelmien suorituskyvyistä. Tutkimus tuo kyberturvallisuutta ja uhkahavainnointia lähemmäs lukijan ymmärrystä, jonka avulla lukijan on helpompi ymmärtää ja nähdä automaattisen uhkahavainnoinnin käyttötapauksia tai turvallisuutta. Tutkimus osoitti sen, että koneoppimisen tarjoamat mahdollisuudet säilyttävät dataturvallisuuden hyvin, tuottaen samalla erinomaisia tuloksia uhkien havainnoinnissa. With the rapid development of technology, security and regulation are lagging, and in particular information and data security issues have been a major concern for the technology sector in recent years. This study is important to illustrate the technological developments in terms of technology governance and security aspects, which are important for research and development in the field. The study examined the evolution of data security, specifically in the context of the security elements of the cyber world, through a literature review, using studies, books, and individual Internet publications of umbrella organizations in the field as sources. Among the elements of cybersecurity, the study focused specifically on the data security of threat detection systems and examined their ability to implement data security requirements. Data security was reviewed using a commonly used model in the industry, the CIA triad, with the components of confidentiality, integrity, and accessibility. Putting data and cybersecurity in the hands of AI applications has sparked debate in the industry. The study also focused on examining how reliable observation systems can be considered by compiling data on system performance. The study brings cybersecurity and threat intelligence closer to the reader's understanding, making it easier for the reader to understand and see the use cases or security of automated threat intelligence. The study showed that the capabilities offered by machine learning preserve data security well while delivering excellent results in threat detection.
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spellingShingle Kelo, Anton Data Security And Automatic Threat Detection CIA-triad Threat detection Tietojärjestelmätiede Information Systems Science 601 kyberturvallisuus koneoppiminen cyber security machine learning
title Data Security And Automatic Threat Detection
title_full Data Security And Automatic Threat Detection
title_fullStr Data Security And Automatic Threat Detection Data Security And Automatic Threat Detection
title_full_unstemmed Data Security And Automatic Threat Detection Data Security And Automatic Threat Detection
title_short Data Security And Automatic Threat Detection
title_sort data security and automatic threat detection
title_txtP Data Security And Automatic Threat Detection
topic CIA-triad Threat detection Tietojärjestelmätiede Information Systems Science 601 kyberturvallisuus koneoppiminen cyber security machine learning
topic_facet 601 CIA-triad Information Systems Science Threat detection Tietojärjestelmätiede cyber security koneoppiminen kyberturvallisuus machine learning
url https://jyx.jyu.fi/handle/123456789/95682 http://www.urn.fi/URN:NBN:fi:jyu-202406104453
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