Medical care has become one of the most indispensable parts of human lives, leading to a dramatic increase in medical big data. To streamline the diagnosis and treatment process, healthcare professionals are now adopting Internet of Things (IoT)-based wearable technology. Recent years have witnessed billions of sensors, devices, and vehicles being connected through the Internet. One such technology—remote patient monitoring—is common nowadays for the treatment and care of patients. However, these technologies also pose grave privacy risks and security concerns about the data transfer and the logging of data transactions. These security and privacy problems of medical data could result from a delay in treatment progress, even endangering the patient’s life. We propose the use of a blockchain to provide secure management and analysis of healthcare big data. However, blockchains are computationally expensive, demand high bandwidth and extra computational power, and are therefore not completely suitable for most resource-constrained IoT devices meant for smart cities. In this work, we try to resolve the above-mentioned issues of using blockchain with IoT devices. We propose a novel framework of modified blockchain models suitable for IoT devices that rely on their distributed nature and other additional privacy and security properties of the network. These additional privacy and security properties in our model are based on advanced cryptographic primitives. The solutions given here make IoT application data and transactions more secure and anonymous over a blockchain-based network.

In this work, we focus on LS-design ciphers Fantomas, Robin, and iSCREAM. LS-designs are a family of bitslice ciphers aimed at efficient masked implementations against side-channel analysis. We have analyzed Fantomas and Robin with a technique that previously has not been applied to both algorithms or linear cryptanalysis. The idea behind linear cryptanalysis is to build a linear characteristic that describes the relation between plaintext and ciphertext bits. Such a relationship should hold with probability 0.5 (bias is zero) for a secure cipher. Therefore, we try to find a linear characteristic between plaintext and ciphertext where bias is not equal to zero. This non-random behavior of cipher could be converted to some key-recovery attack. For Fantomas and Robin, we find 5 and 7-round linear characteristics. Using these characteristics, we attack both the ciphers with reduced rounds and recover the key for the same number of rounds. We also apply linear cryptanalysis to the famous CAESAR candidate iSCREAM and the closely related LS-design Robin. For iScream, we apply linear cryptanalysis to the round-reduced cipher and find a 7-round best linear characteristics. Based on those linear characteristics we extend the path in the related-key scenario for a higher number of rounds.

This article explores how IoT device systems handle multimedia data and presents a secure multimedia framework utilizing blockchain technology. The proposed framework high- lights how blockchain ensures the safety and transparency of multimedia records, document access, and shipping processes between owners and customers. To address these challenges, we introduce a decentralized peer-to-peer multimedia file-sharing platform based on the Inter Planetary File System (IPFS) built on blockchain technology. Additionally, we propose a multimedia file block approval consensus mechanism. Recently, blockchain has been recognized as a potential technology to enforce critical security requirements in IoT devices. It offers protection for IoT networks that require sharing multimedia data, including applications in smart cities, retail, energy, security surveillance, and healthcare.