Search Results (11)

Attacks on the Internet of Things (IoT) are not highly considered during the design and implementation. The prioritization is making profits and supplying services to clients. Most cryptographic algorithms that are commonly used on the IoT are vulnerable to attacks such as linear, differential, differential–linear cryptanalysis attacks, and many more. In this study, we focus only on linear cryptanalysis attacks. Little has been achieved (by other researchers) to prevent or block linear cryptanalysis attacks on cryptographic algorithms used on the IoT. In this study, we managed to block the linear cryptanalysis attack using a mathematically novel approach called Galois Field of the order (2³²), denoted by GF (2³²), and high irreducible polynomials were used to re-construct weak substitution boxes (S-Box) of mostly cryptographic algorithms used on IoT. It is a novel approach because no one has ever used GF (2³²) and highly irreducible polynomials to block linear cryptanalysis attacks on the most commonly used cryptographic algorithms. The most commonly used cryptographic algorithms on the IoT are Advanced Encryption Standard (AES), BLOWFISH, CAMELLIA, CAST, CLEFIA, Data Encryption Standard (DES), Modular Multiplication-based Block (MMB), RC5, SERPENT, and SKIPJACK. We assume that the reader of this paper has basic knowledge of the above algorithms. Full article

In today’s era of widespread web technology and cloud computing, ensuring data security has become a crucial concern across various industries. Instances of data breaches and vulnerabilities in cloud storage have emphasized the need for robust data protection and communication protocols, particularly in sectors like social media, military, and research. This research proposes a Multi-Level Steganography (MLS) algorithm that employs two encryption algorithms, AES and Blow-Fish, to secure the cover image and embed encryption keys as key images within the stego image. The proposed MLS algorithm incorporates a robust pixel randomization function to enhance the security of the encrypted data. Experimental results demonstrate that the proposed algorithm effectively protects data with high Peak Signal-to-Noise Ratio (PSNR) and low Mean Square Error (MSE) values, ensuring superior image quality, reliable encryption, and decryption of secret messages. The utilization of hybrid encryption with AES and BlowFish algorithms further strengthens the algorithm’s security by augmenting the complexity of the encryption process. Full article

To address a business need, most organizations allow employees to use their own devices to enhance productivity and job satisfaction. For this purpose, the Bring Your Own Device (BYOD) policy provides controllable access for employees to organize data through their personal devices. Although the BYOD practice implies plenty of advantages, this also opens the door to a variety of security risks. This study investigates these security risks and proposes a complementary encryption approach with a digital signature that uses symmetric and asymmetric algorithms, depending on the organization’s digital certificate, to secure sensitive information stored in employees’ devices within the framework of BYOD policies. The method uses Advanced Encryption System (AES), Blowfish, RSA and ElGamal with a digital signature to achieve strong encryption and address critical security considerations such as user authentication, confidentiality and data integrity. The proposed encryption approach offers a robust and effective cryptographic solution for securing sensitive information in organizational settings that involve BYOD policies. The study includes experimental results demonstrating the proposed approach’s efficiency and performance, with reasonable encryption and decryption times for different key and file sizes. The results of the study revealed that AES and Blowfish have the best execution time. AES has a good balance of security and performance. RSA performs better than ElGamal in encryption and signature verification, while RSA is slower than ElGamal in decryption. The study also provides a comparative analysis with previous studies of the four encryption algorithms, highlighting the strengths and weaknesses of each approach. Full article

In a typical Wireless Sensor Network (WSN), thousands of sensor nodes can be distributed in the environment. Then, each sensor node transmits its detected data to the base station with the help of cooperation. In this type of network, data aggregation protocols are used to increase the network’s lifetime and reduce each sensor node’s communication load and energy consumption. With Data Clustering, the density of data circulating in the network is reduced, thus increasing the network’s life. Energy, delay, and efficiency are essential criteria in Data Clustering; however, security is another crucial aspect to be considered. A comprehensive solution for secure data clustering has yet to be seen when the literature is examined. In the solutions developed, data availability, which means that the WSN is resistant to Denial of Service (DOS) attacks, has been neglected too much, even though confidentiality, integrity, and authentication are met with different algorithms. This study developed a comprehensive, secure clustering protocol by considering all security requirements, especially data availability. The developed protocol uses the blowfish encryption algorithm, EAX mode, and RSA algorithm. The proposed protocol was theoretically analyzed, empirically evaluated, and simulated from many perspectives. Comparisons were made with LSDAR, SUCID, and OOP-MDCRP protocols. As a result of the study, a comprehensive security solution is provided and more successful results were obtained according to Energy Efficiency, Network Lifetime, Average Delay, and Packet delivery ratio criteria. Full article

A mobile agent is a software application that moves naturally among hosts in a uniform and non-uniform environment; it starts with one host and then moves onto the next in order to divide data between clients. The mobile paradigm is utilized in a wide assortment of medical care applications such as the medical information of a patient, the recovery of clinical information, the incorporation of information pertaining to their wellbeing, dynamic help, telemedicine, obtaining clinical data, patient administration, and so on. The accompanying security issues have grown in tandem with the complexity and improvements in mobile agent technologies. As mobile agents work in an insecure environment, their security is a top priority when communicating and exchanging data and information. Data integrity, data confidentiality and authentication, on-repudiation, denial of service, and access control, are all key security concerns with mobile agent migration. This paper proposes a Verifiable, Secure Mobile Agent Migration model, based on two polynomials (t, n), and an edge secret imparting plan with Blowfish encryption, to enable secure information transmission in clinical medical care. Full article

Background: The technological revolution has allowed users to exchange data and information in various fields, and this is one of the most prevalent uses of computer technologies. However, in a world where third parties are capable of collecting, stealing, and destroying information without authorization, cryptography remains the primary tool that assists users in keeping their information secure using various techniques. Blowfish is an encryption process that is modest, protected, and proficient, with the size of the message and the key size affecting its performance. Aim: the goal of this study is to design a modified Blowfish algorithm by changing the structure of the F function to encrypt and decrypt video data. After which, the performance of the normal and modified Blowfish algorithm will be obtained in terms of time complexity and the avalanche effect. Methods: To compare the encryption time and security, the modified Blowfish algorithm will use only two S-boxes in the F function instead of the four used in Blowfish. Encryption and decryption times were calculated to compare Blowfish to the modified Blowfish algorithm, with the findings indicating that the modified Blowfish algorithm performs better. Results: The Avalanche Effect results reveal that normal Blowfish has a higher security level for all categories of video file size than the modified Blowfish algorithm, with 50.7176% for normal Blowfish and 43.3398% for the modified Blowfish algorithm of 187 kb; hence, it is preferable to secure data and programs that demand a high level of security with Blowfish. Conclusions: From the experimental results, the modified Blowfish algorithm performs faster than normal Blowfish in terms of time complexity with an average execution time of 250.0 ms for normal Blowfish and 248.4 ms for the modified Blowfish algorithm. Therefore, it can be concluded that the modified Blowfish algorithm using the F-structure is time-efficient while normal Blowfish is better in terms of security. Full article

Standard methods used in the encryption and decryption process are implemented to protect confidential data. These methods require many arithmetic and logical operations that negatively affect the performance of the encryption process. In addition, they use private keys of a specific length, in addition to the fixed length of the data block used in encryption, which may provide the possibility of penetration of these methods, thus decreasing the level of security. In this research paper, a new method of digital image cryptography is introduced. This method is based on using a color image as an $image\_key$ to generate a sophisticated matrix private key (MPK) that cannot be hacked. The proposed method uses an initial state to set the required parameters, with secret information needed to generate the private key. The data-block size is variable, and the complicity of the MPK depends on the number of selected rounds and the data-block size. The proposed method is appropriate for publication in Symmetry because it employs a symmetrical complex matrix key to encrypt and decrypt digital images. The proposed method is simple yet very efficient in terms of throughput and scalability. The experiments show that the proposed method meets the quality requirements and can speed up the encryption–decryption process compared with standard methods, including DES, 3DES, AES, and Blowfish. Full article

In this study, we implemented an integrated security solution with Spring Security and Keycloak open-access platform (SSK) to secure data collection and exchange over microservice architecture application programming interfaces (APIs). The adopted solution implemented the following security features: open authorization, multi-factor authentication, identity brokering, and user management to safeguard microservice APIs. Then, we extended the security solution with a virtual private network (VPN), Blowfish and crypt (Bcrypt) hash, encryption method, API key, network firewall, and secure socket layer (SSL) to build up a digital infrastructure. To accomplish and describe the adopted SSK solution, we utilized a web engineering security method. As a case study, we designed and developed an electronic health coaching (eCoach) prototype system and hosted the system in the expanded digital secure infrastructure to collect and exchange personal health data over microservice APIs. We further described our adopted security solution’s procedural, technical, and practical considerations. We validated our SSK solution implementation by theoretical evaluation and experimental testing. We have compared the test outcomes with related studies qualitatively to determine the efficacy of the hybrid security solution in digital infrastructure. The SSK implementation and configuration in the eCoach prototype system has effectively secured its microservice APIs from an attack in all the considered scenarios with 100% accuracy. The developed digital infrastructure with SSK solution efficiently sustained a load of (≈)300 concurrent users. In addition, we have performed a qualitative comparison among the following security solutions: Spring-based security, Keycloak-based security, and their combination (our utilized hybrid security solution), where SSK showed a promising outcome. Full article

Authentication systems based on biometrics characteristics and data represents one of the most important trend in the evolution of the society, e.g., Smart City, Internet-of-Things (IoT), Cloud Computing, Big Data. In the near future, biometrics systems will be everywhere in the society, such as government, education, smart cities, banks etc. Due to its uniqueness, characteristic, biometrics systems will become more and more vulnerable, privacy being one of the most important challenges. The classic cryptographic primitives are not sufficient to assure a strong level of secureness for privacy. The current paper has several objectives. The main objective consists in creating a framework based on cryptographic modules which can be applied in systems with biometric authentication methods. The technologies used in creating the framework are: C#, Java, C++, Python, and Haskell. The wide range of technologies for developing the algorithms give the readers the possibility and not only, to choose the proper modules for their own research or business direction. The cryptographic modules contain algorithms based on machine learning and modern cryptographic algorithms: AES (Advanced Encryption System), SHA-256, RC4, RC5, RC6, MARS, BLOWFISH, TWOFISH, THREEFISH, RSA (Rivest-Shamir-Adleman), Elliptic Curve, and Diffie Hellman. As methods for implementing with success the cryptographic modules, we will propose a methodology which can be used as a how-to guide. The article will focus only on the first category, machine learning, and data clustering, algorithms with applicability in the cloud computing environment. For tests we have used a virtual machine (Virtual Box) with Apache Hadoop and a Biometric Analysis Tool. The weakness of the algorithms and methods implemented within the framework will be evaluated and presented in order for the reader to acknowledge the latest status of the security analysis and the vulnerabilities founded in the mentioned algorithms. Another important result of the authors consists in creating a scheme for biometric enrollment (in Results). The purpose of the scheme is to give a big overview on how to use it, step by step, in real life, and how to use the algorithms. In the end, as a conclusion, the current work paper gives a comprehensive background on the most important and challenging aspects on how to design and implement an authentication system based on biometrics characteristics. Full article

Cryptovirological augmentations present an immediate, incomparable threat. Over the last decade, the substantial proliferation of crypto-ransomware has had widespread consequences for consumers and organisations alike. Established preventive measures perform well, however, the problem has not ceased. Reverse engineering potentially malicious software is a cumbersome task due to platform eccentricities and obfuscated transmutation mechanisms, hence requiring smarter, more efficient detection strategies. The following manuscript presents a novel approach for the classification of cryptographic primitives in compiled binary executables using deep learning. The model blueprint, a Dynamic Convolutional Neural Network (DCNN), is fittingly configured to learn from variable-length control flow diagnostics output from a dynamic trace. To rival the size and variability of equivalent datasets, and to adequately train our model without risking adverse exposure, a methodology for the procedural generation of synthetic cryptographic binaries is defined, using core primitives from OpenSSL with multivariate obfuscation, to draw a vastly scalable distribution. The library, CryptoKnight, rendered an algorithmic pool of AES, RC4, Blowfish, MD5 and RSA to synthesise combinable variants which automatically fed into its core model. Converging at 96% accuracy, CryptoKnight was successfully able to classify the sample pool with minimal loss and correctly identified the algorithm in a real-world crypto-ransomware application. Full article

Cloud computing plays a major role in sharing data and resources to other devices through data outsourcing. During sharing resources, it is a challenging task to provide access control and secure write operations. The main issue is to provide secure read and write operations collaboratively and to reduce computational overload by effective key management. In this paper, a secure and an efficient data collaboration scheme blowfish hybridized weighted attribute-based Encryption (BH-WABE ) for secure data writing and proficient access control has been proposed. Here, weight is assigned to each attribute based on its importance and data are encrypted using access control policies. The cloud service provider stores the outsourced data and an attribute authority revokes or updates the attributes by assigning different attributes based on the weight. The receiver can access the data file corresponding to its weight in order to reduce the computational overload. The proposed BH-WABE provides collusion resistance, multiauthority security and fine-grained access control in terms of security, reliability, and efficiency. The performance is compared with the conventional hybrid attribute-based encryption (HABE) scheme in terms of data confidentiality, flexible access control, data collaboration, full delegation, partial decryption, verification, and partial signing. Full article