Bitcoin price forecast via blockchain technology and artificial intelligence algorithms

Sakız, Burcu; Kutlugun, Esra

doi:10.1109/siu.2018.8404719

Cited by 11 publications

(3 citation statements)

References 2 publications

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“…Still, the algorithm designer can obtain the random number state of the system operation through a covert channel and then get the user's system key to achieving concealment to obtain sensitive information. Under the influence of this idea, underground channel utilisation methods for DSA, El Gamal encryption, El-Gamal signature and Schnorr signature have appeared [24]. In 2014, Wang [25] explored such ways in single-key encryption systems.…”

Section: Covert Channels and Covert Information Transmissionmentioning

confidence: 99%

Retracted: Blockchain‐based covert software information transmission for bitcoin

Reis¹,

Barbosa

Albuquerque

et al. 2023

IET Software

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Blockchain-based data transmission will become a new development direction of data concealment transmission, which is of great significance for developing a secure transmission technology for special applications. To meet the needs of efficient, secure, concealed and stable transmission of confidential information, the transaction data structure of Bitcoin and the location and capacity of potential covert channels are analysed. The data transmission model for covert storage channels based on Bitcoin blockchain is also proposed. It cannot destroy the original transaction format, do not increase the particularity of the transaction content, overcome the defects of the concealed channel characteristics in the existing network environment, ensure that the data is not detected, and protect the sender and receiver of the hidden data transmission. | Information hidingInformation hiding methods can be divided into three categories according to the different information hiding carriers:This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Covert Channels and Covert Information Transmissionmentioning

confidence: 99%

Retracted: Blockchain‐based covert software information transmission for bitcoin

Reis¹,

Barbosa

Albuquerque

et al. 2023

IET Software

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“…ANN'in kullanıldığı bir diğer çalışma da Sakız vd. [5] tarafından yapılmıştır. Çalışma sonucunda tahminlemede büyük farklılık ortaya çıkmıştır.…”

Section: Li̇teratür Taramasiunclassified

Bitcoin Price Prediction Using Sentiment Analysis on Twitter

Köksal¹,

Erdem²,

Türkeli³

et al. 2021

Düzce Üniversitesi Bilim Ve Teknoloji Dergisi

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Bütün sektörler dahilinde finans sektöründe de müşterilere ait fikir ve düşüncelerinin belirlenmesi, firma ve kurumların ileriki dönemler için sunacağı hizmetleri etkilemektedir. Kripto para birimlerinin (Bitcoin, Ethereum, Ripple vb.) ekonomik ve sosyal etkileri hızla artmaya devam ettikçe, ilgili haber makalelerinin ve sosyal medya yayınlarının, özellikle de tweetlerin yaygınlığı da artmaktadır. Bu çalışmada, Twitter kullanıcılarının finans sektörü konularından biri olan Bitcoin ile ilgili yorumları derlenerek bir duygu analizi çalışması yapılmıştır. Kullanıcı yorumları, Twitter'ın sunmuş olduğu API hizmeti vasıtasıyla Python Programlama Dili kullanılarak alınmış; yorumlar olumlu, nötr ve olumsuz etiketler ile ayrıştırılmış, etiket bulutunda toplanmıştır. Naïve Bayes ve Lojistik Regresyon algoritmaları kullanılarak oluşturulan modellerde başarı oranları karşılaştırılmıştır. Naïve Bayes uygulamasının tweetlerin duygularını tahmin etmedeki başarı oranı %72,19 olurken, Lojistik Regresyon uygulamasında bu oran %75,53 olmuştur. Çalışmanın ikinci aşamasında ise, duygu analizinden sonra "Bitcoin" anahtar kelimesi içeren günlük pozitif tweet oranı ile Bitcoin günlük açılış değeri beraber kullanılarak Bitcoin kapanış değeri tahminlemesi yapılmıştır. Finans verileri Yahoo Finance web sitesi üzerinden alınmış; Doğrusal Regresyon ve Rastgele Orman Regresyon yöntemleri ile modeller oluşturulmuştur. Doğrusal Regresyon için ² değeri %88,97 çıkarken, Rastgele Orman Regresyonu için ise %94,16 olmuştur.

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“…Different indicators and oscillators have different characteristics, few of them are used for long term prediction like 1 years on the other hand few indictors are used to predict trend for very short time frame like 1 month. As there are many indictors and oscillators are present in analysis, it becomes difficult for traders to select proper indicators (Sakiz and Kutlugun, 2018). In this study clustering is used to find buy, sell or hold decision for traders.…”

Section: Introductionmentioning

confidence: 99%

Crypto-Currency Price Trend Prediction using k-Means Clustering

Rubaie¹

2020

J. Eng. Appl. Sci.

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Crypto-currency is new emerging asset. Many people are trading in crypto currency for money making. To predict the correct trend in crypto coin fluctuation, technical analysis Is used. Many technical factors are present in analysis which help in predicting price trend. Few of this indicator are RSI, Ichimoku clouds, moving average convergence and divergence, different moving averages and Bollinger Band. This indicators are based on mathematical models. With advancement in data mining algorithm it is possible to use this indicators data as input and find out the price trend for different crypto currency. In this paper data pre-processing technique is used to remove noisy data, clustering is used to find cluster based on specified outputs. It is observed that accurate of this model is very good in predicting short term prices and fluctuation.

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Bitcoin price forecast via blockchain technology and artificial intelligence algorithms

Cited by 11 publications

References 2 publications

Retracted: Blockchain‐based covert software information transmission for bitcoin

Retracted: Blockchain‐based covert software information transmission for bitcoin

Bitcoin Price Prediction Using Sentiment Analysis on Twitter

Crypto-Currency Price Trend Prediction using k-Means Clustering

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