Academic literature on the topic 'Confidentialité Blowfish'

Over a few years, there is rapid increase of exchange of data over the net has brought data confidentiality and its privacy to the fore front. Data confidentiality can be achieved by implementing cryptography algorithms during transmission of data which confirms that data remains secure and protected over an insecure network channel. In order to ensure data confidentiality and privacy, cryptography service encryption is used which makes data in unreadable form while the reverse process rearranges data in readable form and known as decryption. All encryption algorithms are intended to provide confidentiality to data, but their performance varies depending on many variables such as key size, type, number of rounds, complexity and data size used. In addition, although some encryption algorithms outperform others, they have been found to be prone to particular attacks. This paper reviews and summarizes the various common hybrid cascaded n-tier encryption models. Additionally, this paper compares and analyzes the performance of common hybrid cascaded 2-tier and 3-tier encryption models obtained during simulation based on encryption/decryption time, avalanche effect and throughput. The models compared with AES are 2-tier models (AES-TWOFISH, AES-BLOWFISH, TWOFISH-AES, BLOWFISH-AES, AES-SERPENT and SERPENT-TWOFISH) and 3-tier models (DES-BLOWFISH-AES, AES-TWOFISH-SERPENT and SERPENT-TWOFISH-AES). The hybrid cascaded model like AES-TWOFISH, AES-BLOWFISH and SERPENT-TWOFISH-AES are better hybrid models with respect to throughput and avalanche effect.

Abstract. Security is the study of encryption and decryption, data hiding, potential attacks, and performance evaluation. Many algorithms perform this purpose. Blowfish is a symmetric block cipher that uses the Feistel network. Although several works employed the Blowfish algorithm for the security of the cloud, there is still no article that lists previous studies. Cloud computing is the transmission of computer services such as servers, storage, databases, networking, software, analytics, and intelligence through the Internet ("the cloud") in order to provide faster innovation, more flexible resources, and cost savings. The most common issue with cloud computing is information security, privacy, confidentiality, and how the cloud provider ensures these services. This paper includes a survey of most previous works that were concerned with using the Blowfish algorithm in achieving cloud security

The ease of sending data with the development of internet technology technology is now a concern, especially the problem of data confidentiality, integrity and information security. Cryptography is one of the techniques used to maintain data confidentiality and information security, the application of cryptographic techniques for information security and data integrity is highly dependent on the formation of keys. In this study proposed a frequency analysis approach to measure the level of information security of blowfish encryption results to determine the distribution form of each character used in the text and find out the exact frequency of each character used in the test text data. The encryption algorithm and description of blowfish method against plaintext are proven to be accurate, but the longer the key character used will greatly affect the level of information security that came from encryption process, this is based on the results of the frequency analysis conducted.

Security is the level of confidentiality of data stored using cryptography. There are many ways you can do to improve security. In this study, the writer will use a method by encrypting the database with the Caesar Cipher Algorithm, Hill Cipher and Blowfish. Caesar Cipher, Hill Cipher and Blowfish are part of the symmetric algorithm, which means that the encryption and decryption process have the same key. The encryption and decryption process in Caesar Cipher, Hill Cipher and Blowfish Algorithms each has one key. algorithm encryption techniques using symmetric passwords have 2 types, namely block ciphers and stream ciphers. Caesar Cipher, Hill Cipher and Blowfish and Twofish Algorithms are the encryption of the block cipher that breaks or creates blocks to encrypt and obtain cipher text. Result in this paper In Caesar Cipher, it is carried out like 3 blocks of encryption. Whereas in Hill Cipher a word is divided into several blocks and each block is encrypted. In Blowfish, several iterations are performed to get the text cipher, the input is 64 bits of data that can be done as many as 16 iterations. In Twofish the input is 128 bits, in contrast to Blowfish which is only 64 bits, Twofish can also accept 256 bits long and do 16 iterations to get the cipher text. Twofish has stronger security than the 3 algorithms above, Twofish also takes up more memory and takes longer to encrypt.

The limitations of humans to maintain the security and confidentiality of stored data can have a bad impact if it is used by unauthorized parties. One way to secure shipping is to convert data into one that is not understood by encoding and insertion using cryptographic techniques. Cryptography is the study of system security, where the system needs to be secured from interference or threats from irresponsible parties. One of the cryptographic algorithms is the Blowfish Algorithm. The Blowfish algorithm is a modern cryptographic algorithm symmetrical key-shaped block cipher. The Blowfish algorithm is quite simple but strong enough because it has a long keyspace, making it difficult to attack. Encryption is done by using a certain key, so as to produce ciphertext (files that have been encrypted or encoded) that cannot be read or understood. The ciphertext can be restored as if it was decrypted using the same key when encrypting the file. The key length used can affect the security of the algorithm. The decryption flow is almost the same as the Blowfish Algorithm encryption, except in the P-array (P1, P2, ..., P18) done by invading. Information of a system is certainly stored in a database that is always possible to attack but using cryptography then the problem can be overcome. By using the Blowfish algorithm, information security in a MySQL database can be improved.

To improve the security of EoC network traffic, the hybrid encryption scheme was presented. The relevant encryption algorithm was analyzed, and the hybrid encryption scheme was proposed for EOC downlink traffic encryption, in which ECC algorithm is taken to produce and encrypt session key, and Blowfish algorithm is improved to encrypt the broadband-authorized frame and downlink data. The security analysis show the encryption scheme can guarantee the integrity and confidentiality of the data in the EoC transmission process.

A previous study has been conducted integrating modification on secure hash algorithm 1 (SHA-1) to document integrity verification of printed documents using quick response (QR) codes. However, encryption is warranted as data is transmitted in plaintext directly to the server to prevent hacking and ensuring not only data integrity but data security as well. A more secured document integrity verification using QR code was designed and developed by successfully incorporating a better hashing algorithm– modified SHA-1 and integrating a modern encryption algorithm–modified blowfish algorithm. By integrating both, data integrity and data confidentiality is assured as compared to previous research. The developed software was checked against user requirements to check the acceptability of the software. Error rate and accuracy were also checked to see how the software performed. Based on the testing conducted, it has been found that the document integrity verification software using QR code with the integration of modified SHA-1 hash and Modified Blowfish encryption was acceptable, accurate, and more secure.

Services in the cloud environment are distributed between all servers and users. Cloud providers have problems with file protection as security is a major problem when processing and transferring information, as the original data type can be viewed, misused and lost. In the cloud computing world, cloud protection is a major concern. A variety of research projects are planned to safeguard the cloud climate. Cryptography is used to address the security problem and to achieve the CIA (confidentiality, honesty and disponibility). The most effective technique for ensuring high data transfer and storage protection is cryptography. There are certain drawbacks in traditional symmetric and asymmetrics. We will introduce a new technique of hybrid data protection and confidentiality to solve this issue. We use the ECC and Blowfish to build a hybrid algorithm in this article. The hybrid scheme output is compared to the current hybrid technique and demonstrates the high safety and confidentiality of the patient data in the proposed method. The hybrid encryption is used to remove both symmetrical and asymmetrical drawbacks.

Data is a very authentic evidence that need to be saved because the data are at risk of data changes by the party who wanted to misuse the data or no effect on the data. Therefore, so that no unauthorized person to change the existing data, stored or can take the data that is very important, we need a method to be able to secure and keep data. The database is used to keep data and information. The whole system stores the data in the database, so that the contents of stored data security and confidentiality must be maintained. To maintain the security of a security that is required cryptography. With the use of databases that are in can be connected to each other, Database is not just a place to store data,Computer security system is needed at this time in line with the increase use of computers in the world. So existing data security has become seriously threatened to be accessed by people who are not responsible. Computer security becomes very important at this time because it is related to the privacy, integrity, authentication and confidentiality. Thus data need to be stored by using the correct storage techniques, so that the confidentiality and security of data is maintained. Cryptographic techniques with engineering data encryption on the database is one solution that can be used to meet the confidentiality and Data Security settings. With the existence of a cryptography that includes the encryption process, the data in the database can be encoded so that unauthorized persons can not read the information, in addition to those who know the key to describing it. Security of data / information document with a cryptographic technique that uses the Blowfish algorithm chosen method for cryptographic key modernmerupakan shaped symmetric block cipher. Blowfish algorithm which can encrypt text built in text form. Encryption is done using a specific key, resulting ciphertext that can not be understood. The ciphertext can be changed back as the beginning if the decryption using the same key in the beginning when the database mengekripsi.

Abstract: The internet has revolutionized advancements, it’s conveniences and uses come at the price of new perils. To be safe from being the victim of fraud, theft and other damage security and vigilance is critical. Cryptography plays an important role in securing information and communications using a set of rules, it ensures the integrity of our data. It maintains confidentiality by protecting the privacy of personal information stored in enterprise systems. Hence Encryption is the only way to ensure that your information remains secure while it is stored and being transmitted. Cryptographic Algorithms mathematically maintain the integrity, confidentiality and authenticity of sensitive information by preventing data disclosure, data tampering and repudiation. The three main types of cryptography are Symmetric Key Cryptography, Asymmetric Key Cryptography and Hash Functions. In this Paper, several important algorithms used for encryption and decryption are defined and analysed, the algorithms are DES, AES, ECC, RSA, MD5 Keywords: Cryptography, Encryption, Decryption, AES, DES, ECC, RSA, Blowfish, MD5

Les données numériques jouent un rôle crucial dans notre vie quotidienne en communiquant, en enregistrant des informations, en exprimant nos pensées et nos opinions et en capturant nos moments précieux sous forme d'images et de vidéos numériques. Les données numériques présentent d'énormes avantages dans tous les aspects de la vie moderne, mais constituent également une menace pour notre vie privée. Dans cette thèse, nous considérons trois types de données numériques en ligne générées par les utilisateurs des médias sociaux et les clients du commerce électronique : les graphiques, les transactions et les images. Les graphiques sont des enregistrements des interactions entre les utilisateurs qui aident les entreprises à comprendre qui sont les utilisateurs influents dans leur environnement. Les photos postées sur les réseaux sociaux sont une source importante de données qui nécessitent des efforts d'extraction. Les ensembles de données transactionnelles représentent les opérations qui ont eu lieu sur les services de commerce électronique.Nous nous appuyons sur une technique de préservation de la vie privée appelée Differential Privacy (DP) et sa généralisation Blowfish Privacy (BP) pour proposer plusieurs solutions permettant aux propriétaires de données de bénéficier de leurs ensembles de données sans risque de violation de la vie privée pouvant entraîner des problèmes juridiques. Ces techniques sont basées sur l'idée de récupérer l'existence ou la non-existence de tout élément dans l'ensemble de données (tuple, ligne, bord, nœud, image, vecteur, ...) en ajoutant respectivement un petit bruit sur la sortie pour fournir un bon équilibre entre intimité et utilité.Dans le premier cas d'utilisation, nous nous concentrons sur les graphes en proposant trois mécanismes différents pour protéger les données personnelles des utilisateurs avant d'analyser les jeux de données. Pour le premier mécanisme, nous présentons un scénario pour protéger les connexions entre les utilisateurs avec une nouvelle approche où les utilisateurs ont des privilèges différents : les utilisateurs VIP ont besoin d'un niveau de confidentialité plus élevé que les utilisateurs standard. Le scénario du deuxième mécanisme est centré sur la protection d'un groupe de personnes (sous-graphes) au lieu de nœuds ou d'arêtes dans un type de graphes plus avancé appelé graphes dynamiques où les nœuds et les arêtes peuvent changer à chaque intervalle de temps. Dans le troisième scénario, nous continuons à nous concentrer sur les graphiques dynamiques, mais cette fois, les adversaires sont plus agressifs que les deux derniers scénarios car ils plantent de faux comptes dans les graphiques dynamiques pour se connecter à des utilisateurs honnêtes et essayer de révéler leurs nœuds représentatifs dans le graphique.Dans le deuxième cas d'utilisation, nous contribuons dans le domaine des données transactionnelles en présentant un mécanisme existant appelé Safe Grouping. Il repose sur le regroupement des tuples de manière à masquer les corrélations entre eux que l'adversaire pourrait utiliser pour violer la vie privée des utilisateurs. D'un autre côté, ces corrélations sont importantes pour les propriétaires de données dans l'analyse des données pour comprendre qui pourrait être intéressé par des produits, biens ou services similaires. Pour cette raison, nous proposons un nouveau mécanisme qui expose ces corrélations dans de tels ensembles de données, et nous prouvons que le niveau de confidentialité est similaire au niveau fourni par Safe Grouping.Le troisième cas d'usage concerne les images postées par les utilisateurs sur les réseaux sociaux. Nous proposons un mécanisme de préservation de la confidentialité qui permet aux propriétaires des données de classer les éléments des photos sans révéler d'informations sensibles. Nous présentons un scénario d'extraction des sentiments sur les visages en interdisant aux adversaires de reconnaître l'identité des personnes
Digital data is playing crucial role in our daily life in communicating, saving information, expressing our thoughts and opinions and capturing our precious moments as digital pictures and videos. Digital data has enormous benefits in all the aspects of modern life but forms also a threat to our privacy. In this thesis, we consider three types of online digital data generated by users of social media and e-commerce customers: graphs, transactional, and images. The graphs are records of the interactions between users that help the companies understand who are the influential users in their surroundings. The photos posted on social networks are an important source of data that need efforts to extract. The transactional datasets represent the operations that occurred on e-commerce services.We rely on a privacy-preserving technique called Differential Privacy (DP) and its generalization Blowfish Privacy (BP) to propose several solutions for the data owners to benefit from their datasets without the risk of privacy breach that could lead to legal issues. These techniques are based on the idea of recovering the existence or non-existence of any element in the dataset (tuple, row, edge, node, image, vector, ...) by adding respectively small noise on the output to provide a good balance between privacy and utility.In the first use case, we focus on the graphs by proposing three different mechanisms to protect the users' personal data before analyzing the datasets. For the first mechanism, we present a scenario to protect the connections between users (the edges in the graph) with a new approach where the users have different privileges: the VIP users need a higher level of privacy than standard users. The scenario for the second mechanism is centered on protecting a group of people (subgraphs) instead of nodes or edges in a more advanced type of graphs called dynamic graphs where the nodes and the edges might change in each time interval. In the third scenario, we keep focusing on dynamic graphs, but this time the adversaries are more aggressive than the past two scenarios as they are planting fake accounts in the dynamic graphs to connect to honest users and try to reveal their representative nodes in the graph. In the second use case, we contribute in the domain of transactional data by presenting an existed mechanism called Safe Grouping. It relies on grouping the tuples in such a way that hides the correlations between them that the adversary could use to breach the privacy of the users. On the other side, these correlations are important for the data owners in analyzing the data to understand who might be interested in similar products, goods or services. For this reason, we propose a new mechanism that exposes these correlations in such datasets, and we prove that the level of privacy is similar to the level provided by Safe Grouping.The third use-case concerns the images posted by users on social networks. We propose a privacy-preserving mechanism that allows the data owners to classify the elements in the photos without revealing sensitive information. We present a scenario of extracting the sentiments on the faces with forbidding the adversaries from recognizing the identity of the persons. For each use-case, we present the results of the experiments that prove that our algorithms can provide a good balance between privacy and utility and that they outperform existing solutions at least in one of these two concepts