Proposal of a Token-Based Node Selection Mechanism for Node Distribution of Mobility IoT Blockchain Nodes.

Various elements, such as evolutions in IoT services resulting from sensoring by vehicle parts and advances in small communication technology devices, have significantly impacted the mass spread of mobility services that are provided to users in need of limited resources. In particular, business models are progressing away from one-off costs towards longer-term costs, as represented by shared services utilizing kick-boards or bicycles and subscription services for vehicle software. Advances in shared mobility services, as described, are calling for solutions that can enhance the reliability of data aggregated by users leveraging mobility services in the next-generation mobility areas. However, the mining process to renew status ensures continued network communication, and block creation demands high performance in the public block chain. Therefore, easing the mining process for state updates in public blockchains is a way to alleviate the high-performance process requirements of public blockchains. The proposed mechanism assigns token-based block creation authority instead of the mining method, which provides block creation authority to nodes that provide many resources. Blocks are created only by a group of participants with tokens, and after creation, tokens are updated and delivered to new nodes to form a new token group. Additionally, tokens are updated in each block after their initial creation, making it difficult to disguise the tokens and preventing resource-centered centralization.

De-Identification Mechanism of User Data in Video Systems According to Risk Level for Preventing Leakage of Personal Healthcare Information.

A problem with biometric information is that it is more sensitive to external leakage, because it is information that cannot be changed immediately compared to general authentication methods. Regarding facial information, a case in which authentication was permitted by facial information output by a 3D printer was found. Therefore, a method for minimizing the leakage of biometric information to the outside is required. In this paper, different levels of identification information according to the authority of the user are provided by the de-identification of metadata and face information in stages. For face information and metadata, the level of de-identification is determined and achieved according to the risk level of the de-identified subject. Then, we propose a mechanism to minimize the leakage path by preventing reckless data access by classifying access rights to unidentified data according to four roles. The proposed mechanism provides only differentially de-identified data according to the authority of the accessor, and the required time to perform the de-identification of one image was, on average, 3.6 ms for 300 datapoints, 3.5 ms for 500 datapoints, and 3.47 ms for 1000 datapoints. This confirmed that the required execution time was shortened in proportion to the increase in the size of the dataset. The results for the metadata were similar, and it was confirmed that it took 4.3 ms for 300 cases, 3.78 ms for 500 cases, and 3.5 ms for 1000 cases.

IoT-Blockchain Enabled Optimized Provenance System for Food Industry 4.0 Using Advanced Deep Learning.

Agriculture and livestock play a vital role in social and economic stability. Food safety and transparency in the food supply chain are a significant concern for many people. Internet of Things (IoT) and blockchain are gaining attention due to their success in versatile applications. They generate a large amount of data that can be optimized and used efficiently by advanced deep learning (ADL) techniques. The importance of such innovations from the viewpoint of supply chain management is significant in different processes such as for broadened visibility, provenance, digitalization, disintermediation, and smart contracts. This article takes the secure IoT-blockchain data of Industry 4.0 in the food sector as a research object. Using ADL techniques, we propose a hybrid model based on recurrent neural networks (RNN). Therefore, we used long short-term memory (LSTM) and gated recurrent units (GRU) as a prediction model and genetic algorithm (GA) optimization jointly to optimize the parameters of the hybrid model. We select the optimal training parameters by GA and finally cascade LSTM with GRU. We evaluated the performance of the proposed system for a different number of users. This paper aims to help supply chain practitioners to take advantage of the state-of-the-art technologies; it will also help the industry to make policies according to the predictions of ADL.

An Enhanced Lightweight Anonymous Authentication Scheme for a Scalable Localization Roaming Service in Wireless Sensor Networks.

More security concerns and complicated requirements arise in wireless sensor networks than in wired networks, due to the vulnerability caused by their openness. To address this vulnerability, anonymous authentication is an essential security mechanism for preserving privacy and providing security. Over recent years, various anonymous authentication schemes have been proposed. Most of them reveal both strengths and weaknesses in terms of security and efficiency. Recently, Farash et al. proposed a lightweight anonymous authentication scheme in ubiquitous networks, which remedies the security faults of previous schemes. However, their scheme still suffers from certain weaknesses. In this paper, we prove that Farash et al.'s scheme fails to provide anonymity, authentication, or password replacement. In addition, we propose an enhanced scheme that provides efficiency, as well as anonymity and security. Considering the limited capability of sensor nodes, we utilize only low-cost functions, such as one-way hash functions and bit-wise exclusive-OR operations. The security and lightness of the proposed scheme mean that it can be applied to roaming service in localized domains of wireless sensor networks, to provide anonymous authentication of sensor nodes.

Mutual Authentication Scheme in Secure Internet of Things Technology for Comfortable Lifestyle.

The Internet of Things (IoT), which can be regarded as an enhanced version of machine-to-machine communication technology, was proposed to realize intelligent thing-to-thing communications by utilizing the Internet connectivity. In the IoT, "things" are generally heterogeneous and resource constrained. In addition, such things are connected to each other over low-power and lossy networks. In this paper, we propose an inter-device authentication and session-key distribution system for devices with only encryption modules. In the proposed system, unlike existing sensor-network environments where the key distribution center distributes the key, each sensor node is involved with the generation of session keys. In addition, in the proposed scheme, the performance is improved so that the authenticated device can calculate the session key in advance. The proposed mutual authentication and session-key distribution system can withstand replay attacks, man-in-the-middle attacks, and wiretapped secret-key attacks.