A Survey on The Accuracy of Machine Learning Techniques for Intrusion and Anomaly Detection on Public Data Sets

Adek, Rizal Tjut; Ula, Munirul

doi:10.1109/databia50434.2020.9190436

Cited by 17 publications

(6 citation statements)

References 34 publications

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“…Conventional security systems cannot be directly applied to IoT systems [29]. This is because objects in IoT are dynamic, in the sense that objects (devices) can freely join or separate from the IoT community where these objects join.…”

Section: Security Threats On the Internet Of Thingsmentioning

confidence: 99%

“…RFID tags have a unique PIN, such as a 32-bit PIN. If the attacker enters the correct PIN from the RFID reader, the RFID tag can be instructed to deactivate, so that the tag no longer operates after receiving this command [29]. In addition, there is a sleep command that puts the tag to sleep, for example, by making it inactive for a predetermined amount of time [19].…”

Section: Table 2 the Security Solution For Rfidmentioning

confidence: 99%

See 1 more Smart Citation

Towards The Secure Internet of Things: Threats and Solution

Ula

Adek

Mukhlish

2023

Proceedings of Malikussaleh International Conference on Multidi

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The use of the Internet of Things (IoT) has recently become a worldwide trend, as this technology can connect various types of equipment such as sensors, cameras, and other devices via the internet. The broad adoption of various IoT technologies makes life easier and better for people. Internet of things applications has been widely used in Smart Building, Smart Vehicles, Construction Management, health management and many other applications. However, the IoT technology still has many flaws and weakness especially in its security and defense mechanism. This paper reviews and elaborate type of security vulnerabilities, issue and threats that IoT technology faces from academic research paper in the past 10 years. This review also aims to find the possible solutions proposed by researchers to overcome security weakness, threats and issue in IoT technology and its application. This research goal to provide guidelines for those who want to develop and improve IoT security. A systematic review was used as the methodology in this paper. The purpose of this systematic review is to survey the threats and vulnerabilities of IoT technology as reported in previous studies. This review also proposes a comprehensive countermeasure to the previously mentioned threats and weaknesses. This study's findings include the identification and classification of various threats in IoT, as well as methods for countermeasures against these attacks. It concludes with reviews of research gaps and future research directions to improve IoT security.

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Section: Security Threats On the Internet Of Thingsmentioning

confidence: 99%

Section: Table 2 the Security Solution For Rfidmentioning

confidence: 99%

Towards The Secure Internet of Things: Threats and Solution

Ula

Adek

Mukhlish

2023

Proceedings of Malikussaleh International Conference on Multidi

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“…AI is a term used to build artificial human brains that can learn, plan, perceive, and analyze natural language. It is the study and creation of computer systems capable of performing activities that need human intelligence, such as visual perception, speech recognition, decision-making, and language translation [16]. ML and deep learning are the most often utilized AI technologies.…”

Section: Literature Reviewmentioning

confidence: 99%

A Decision Support System for Benguet’s Upland Vegetable Crop Prediction using Machine Learning Techniques

2023

ecb

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Food security has been a long-standing problem in the Philippines, with the agricultural sector having constant issues with transporting and distributing produce, a huge mismatch between supply and demand, dealing with damages from natural calamities or outbreaks, poor crop planning and management, and other economic and political problems that have negatively affected our farmer folk. In recent times, technologies such as machine learning and decision support systems (DSS) have been helpful in mitigating these problems. This paper presents a DSS for Benguet's upland vegetable crop prediction using machine learning techniques. It will utilize these technologies to help farmers in optimizing their crop yields providing assistance to the farmers of Benguet in decision making on potential crop yield for a particular climatic scenario. Multiple linear regression algorithm was used for the prediction of crop yield and was done on a dataset that contained important commodity information per municipality for the years 2015 to 2020. Data mining techniques such as data pre-processing, data transformation, data aggregation and crop prediction were performed using Microsoft Excel, Python, and WEKA. The accuracy of prediction was evaluated through R-squared and Root Mean Squared Error. We got an accuracy of 97.73% for the prediction algorithm.

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“…Text mining has been defined by many research experts and practitioners. Text mining has the definition of mining data in the form of text [12] where the data source is usually obtained from documents [6], and the goal is to find words that can represent the contents of the document so that analysis of the relationship between documents can be carried out. The text mining system consists of a text preprocessing component, feature selection [13], and a data mining component.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Good clustering should classify or classify objects that have similarities in one group and separate objects that are not similar. Basically, there are two clustering methods [6], but in this final project a hierarchical clustering method will be used. One type of this method is agglomerative clustering, a method that is bottom-up clustering, which is the merging of several objects into a single cluster.…”

Section: Introductionmentioning

confidence: 99%

Online Newspaper Clustering in Aceh using the Agglomerative Hierarchical Clustering Method

Adek

Dinata

Ditha

2021

Int. J. Eng. Scie. and Inform. Technology.

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The rapid progress in the field of information technology, especially the internet, has given birth to a lot of information. The ease of publishing an article on a website causes an explosion of news pages which will certainly confuse readers. The diversity and the increasing number of news articles make it increasingly difficult for internet users to find news and large piles of news data on online newspaper sites in Aceh. The grouping of text documents is needed to classify news in online newspapers in Aceh based on the content contained in news articles. In this study, the process of grouping online news in Aceh was tried using the Agglomerative Hierarchical Clustering method. News is grouped with a Bottom-Up design strategy that starts with placing each object as a cluster then combined into a larger cluster based on the similarity of keywords in each news, then the cluster results are compared and put into each news category. The research design was carried out in a structured manner using data flow diagrams in forming the research framework. The study was conducted by taking online news text data on 10 online news websites in Aceh from July 2016 to March 2017 with 1000 randomly generated documents. The process of crawling news data is done using a php script which will only take text files from the news on the website. News grouping is done based on religion, politics, law, sports, tourism, education, culture, economy and technology. The results of the grouping performance of the Agglomerative Hierarchical Clustering method in this study have an average accuracy of 89.84%.

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A Survey on The Accuracy of Machine Learning Techniques for Intrusion and Anomaly Detection on Public Data Sets

Cited by 17 publications

References 34 publications

Towards The Secure Internet of Things: Threats and Solution

Towards The Secure Internet of Things: Threats and Solution

A Decision Support System for Benguet’s Upland Vegetable Crop Prediction using Machine Learning Techniques

Online Newspaper Clustering in Aceh using the Agglomerative Hierarchical Clustering Method

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