Adaptive Key Generation Research Articles

Privacy preservation of inventory management using adaptive key generation with Hyperledger blockchain technology

ABSTRACT The blockchain is an emerging and essential technology in offering various services to several applications including the financial industry and information technology. Consequently, recent information methodologies cannot satisfy the constraints. The data management issue may rise complexities including tracking operations with information security and unsatisfactory traceability data quality due to the high increase in inventory management data. To address the challenge, this paper aims to focus on developing new hyperledger blockchain-enabled secure inventory management with an adaptive key management process. Here, the inventory management data processed by different distributors is encrypted using the adaptive key generation by Fitness-derived Predator Presence Probability-based Squirrel Search Algorithm (FPPP-SSA) that ensures data control. The optimal key management in encryption solves the multi-objective function based on the “degree of modification information preservation rate and hiding ratio (Euclidean distance).” Once the data are enciphered, they are saved in the hyperledger blockchain, where the smart contract is the chain code application. While restoring or decrypting data, the authorized distributor should use the same adaptive key for maintaining secured inventory management. The performance is evaluated under diverse test cases, and the results are estimated under certain performance metrics.

A Lightweight Security Model using Delta Probabilistic Hashing Technique for Secured Data Transmission in IoT Systems

Secure data transmission is one of the most pressing concerns for resource constrained IoT devices. There is a need for an efficient and lightweight solution for data security in IoT applications. The proposed study is primarily concerned with the creation of a lightweight data security model for an IoT data transmission-based application for data transmission and storage in smart cities. The fundamental contribution of the proposed security model is the creation of a distinct hashing algorithm based on the specific pattern of the previous sequential change in value. The Delta Probabilistic Hashing (DPH) based architecture of key extraction technique for data security will perform this. Based on the hash key signature approach, this kind of safe data handling procedure provides a random key for data encryption, which will simplify the model and speed up the algorithm's operation. Our approach's main features are enhanced efficiency and throughput, lightweight data security, and adaptive key generation.

Neural Attractor-Based Adaptive Key Generator with DNA-Coded Security and Privacy Framework for Multimedia Data in Cloud Environments

Cloud services offer doctors and data scientists access to medical data from multiple locations using different devices (laptops, desktops, tablets, smartphones, etc.). Therefore, cyber threats to medical data at rest, in transit and when used by applications need to be pinpointed and prevented preemptively through a host of proven cryptographical solutions. The presented work integrates adaptive key generation, neural-based confusion and non-XOR, namely DNA diffusion, which offers a more extensive and unique key, adaptive confusion and unpredictable diffusion algorithm. Only authenticated users can store this encrypted image in cloud storage. The proposed security framework uses logistics, tent maps and adaptive key generation modules. The adaptive key is generated using a multilayer and nonlinear neural network from every input plain image. The Hopfield neural network (HNN) is a recurrent temporal network that updates learning with every plain image. We have taken Amazon Web Services (AWS) and Simple Storage Service (S3) to store encrypted images. Using benchmark evolution metrics, the ability of image encryption is validated against brute force and statistical attacks, and encryption quality analysis is also made. Thus, it is proved that the proposed scheme is well suited for hosting cloud storage for secure images.

Adaptive key generation algorithm based on software engineering methodology

Recently, the generation of security keys has been considered for guaranteeing the strongest of them in terms of randomness. In addition, the software engineering methodologies are adopted to ensure the mentioned goal is reached. In this paper, an adaptive key generation algorithm is proposed based on software engineering techniques. The adopted software engineering technique is self-checking process, used for detecting the fault in the underlying systems. This technique checks the generated security keys in terms of validity based on randomness factors. These factors include the results of National Institute of standard Test (NIST) tests. In case the randomness factors are less than the accepted values, the key is regenerated until obtaining the valid one. It is important to note that the security keys are generated using shift register and SIGABA technique. The proposed algorithm is tested over different case studies and the results show the effective performance of it to produce well random generated keys.

Self B - Adaptive Key Generation for Primary Users in Cognitive Radio Networks for Less Prone Primary User Emulation Attacks

Self B - Adaptive Key Generation for Primary Users in Cognitive Radio Networks for Less Prone Primary User Emulation Attacks