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Found 4 from your keywords: subject="Spyware"
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KLASIFIKASI SERANGAN SPYWARE DENGAN MENGGUNAKAN METODE DECISION TREE
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Dipotara, A. Haikal

Spyware is a type of malicious software that can collect information about a person or organization without permission. Typically, spyware is installed accidentally through malware or downloaded from the internet without the user's knowledge. Spyware is particularly dangerous because it targets computers and gadgets, posing serious risks to privacy and data integrity. Spyware can collect sensit…

Edition
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ISBN/ISSN
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Collation
xv, 82 hlm.; ilus.; tab.; 29 cm.
Series Title
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Call Number
T1859732025
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VISUALISASI SERANGAN MALWARE SPYWARE MENGGUNAKAN METODE K-MEANS CLUSTERING.
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Saifullah, Muhammad Arief

K-means clustering is a tool for determining the cluster structure of a data set identified by its strong similarity to other clusters or its strong differences from other clusters. Another article says that the working method of the K-Means algorithm requires using centroids as cluster prototypes and previous cluster results as output. The dataset comes from CIC-MalMem2022 provided by UNB CIC.…

Edition
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ISBN/ISSN
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Collation
xiii, 48 hlm.; ilus.; 29 cm
Series Title
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Call Number
T1308832023
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VISUALISASI SERANGAN MALWARE SPYWARE DENGAN MENGGUNAKAN METODE RANDOM FOREST.
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Pramudita, Amelia 

Spyware is a type of malware that aims to collect important information and data such as financial information and passwords without permission and send them to the attacker. Visualization techniques are needed to make it easier to analyze attack patterns and characteristics of spyware. This study used the Random Forest algorithm. The dataset is from CIC-MalMem2022 with benign data types and Sp…

Edition
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ISBN/ISSN
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Collation
xiii, 71 hlm.; ilus.; 29 cm
Series Title
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Call Number
T1120832023
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VISUALISASI SERANGAN MALWARE SPYWARE DENGAN MENGGUNAKAN METODE SUPPORT VECTOR…
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Fitriani, Zarah 

Spyware malware attacks are a significant threat to computer hardware and user privacy. To analyze and make it easier to recognize such attacks effectively, visualization techniques can provide valuable insights into their patterns and characteristics. This research using a machine learning algorithm, Support Vector Machine (SVM). The dataset used in this study is from the CIC MalMem 2022 which…

Edition
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ISBN/ISSN
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Collation
xiv, 71 hlm.; Ilus.; 29 cm
Series Title
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Call Number
T1120822023