Breaking a Caesar Cipher / Vigenère Cipher Encryption for Secure Data Communication
This project had one purpose: creating almost unbreakable encryption by breaking a Caesar – and Vigenère Cipher and getting familiar with how they work. Created a program to encrypt and decrypt messages with a Caesar Cipher and Vigenère Cipher encryption. Breaking these encryptions in these programs will help to identify the factors that contribute to strong and weak encryption systems. A program was created to encrypt messages using Caesar Cipher with a key from 1 to 25 and decrypt messages without knowing the original key by doing different types of “attacks” on the system: a brute force and frequency analysis attack. Created another program to encrypt messages using Vigenère Cipher with a keyword or keyphrase and decrypted messages whilst knowing that original keyword. Tested and compared the two different cyphers when being attacked. This helped identify factors that influenced the strength of encryption and identified the advantages and disadvantages of each Cipher as well as the weaknesses in each attack. Through testing and breaking a Caesar and Vigenère Cipher successfully, multiple factors were identified that influenced the strength of the encryption system. These were used to ensure the new encryption created will be as strong as can be. Comparing the success rate of the different attacks on each Cipher, the similarities, weaknesses and strengths in the Brute Force and Frequency Analysis attacks were found.
HandExo
Stroke is a very common disease, almost a national disease. In terms of stroke frequency, 匈牙利 ranks second in the world. Every year, 40-50 thousand people become paralyzed or permanently injured as a result of cerebrovascular disorders. This number is three to four times higher than in developed countries. Almost every Hungarian family is affected! Of course, saving the life of someone who has a stroke is the most important thing, but rehabilitation is also very important, since only with the help of a physiotherapist will the patient be able to live a full life.
Deciphering The Illusion: A Multi Faceted Algorithm in Deepfake Detection
AI (Artificial Intelligence) technology has developed very rapidly in recent years, to the point where it can make fake videos or photos called "deepfake''. According to Sumsub Identity Fraud Report 2023 just in the past year, in the APAC region the number of deepfakes has grown 1530%, in the philippines an astounding 4500% and in 馬來西亞 a 1000% increase, these numbers will continue to rise without a proper defense against them, With this rapidly developing technology, there are several threats from misuse deepfake, namely making fraud via video calls, fake videos to blame innocent people, and so on. Therefore, in this research project, an algorithm architecture will be created, namely a system and method used to detect "deepfake" images. The architecture of this algorithm involves convolution functions, neural networks, convolutional neural networks, data normalization functions, namely ReLu and SoftMax, and pooling. This architecture will then be trained over and over with 140,000 scrambled images, which then will make the architecture ready to be used. By researching and combining this algorithm architecture, a system is produced without a cost and with a final result of up to 90% accuracy and detection of 32 images faster than a human can blink.
AI時光機-利用照片轉換技術重溫在地歷史
目前網路上流傳許多使用人工智慧修復照片的網站或應用軟體。然而,由於這些訓練資料多數來自國外,導致修復中式建築照片的效果欠佳。此外,許多老舊照片因氧化、潮濕而泛黃,使得修復程序比起修復純黑白相片更加困難。因此,本研究旨在建🖂一個專門修復中式建築物的機器學習模型,主要分為以下三個部分:首先,使用機器學習模型對老舊照片進行修復,包括著色、去模糊化和降噪;其次,分析使用不同比例之有色調照片(模擬泛黃照片)訓練模型的效果;最後,研究不同的修復順序(著色、去模糊化、降噪)和模型執行次數對照片修復效果的影響,發現「著色、去噪、去模糊化」的順序修復效果最佳。此外,許多老舊照片因為受損等原因,只剩下極少的特徵,因此本研究採用機器學習模型,以延伸重建原始照片。透過這種方法,我們能夠重新建構當時建築物周圍可能的場景和情境。