A Trusted Reputation Management Scheme for Cross-Chain Transactions.

Blockchain has become a well-known, secured, decentralized datastore in many domains, including medical, industrial, and especially the financial field. However, to meet the requirements of different fields, platforms that are built on blockchain technology must provide functions and characteristics with a wide variety of options. Although they may share similar technology at the fundamental level, the differences among them make data or transaction exchange challenging. Cross-chain transactions have become a commonly utilized function, while at the same time, some have pointed out its security loopholes. It is evident that a secure transaction scheme is desperately needed. However, what about those nodes that do not behave? It is clear that not only a secure transaction scheme is necessary, but also a system that can gradually eliminate malicious players is of dire need. At the same time, integrating different blockchain systems can be difficult due to their independent architectures, and cross-chain transactions can be at risk if malicious attackers try to control the nodes in the cross-chain system. In this paper, we propose a dynamic reputation management scheme based on the past transaction behaviors of nodes. These behaviors serve as the basis for evaluating a node's reputation to support the decision on malicious behavior and enable the system to intercept it in a timely manner. Furthermore, to establish a reputation index with high precision and flexibility, we integrate Particle Swarm Optimization (PSO) into our proposed scheme. This allows our system to meet the needs of a wide variety of blockchain platforms. Overall, the article highlights the importance of securing cross-chain transactions and proposes a method to prevent misbehavior by evaluating and managing node reputation.

MiniNet: Dense squeeze with depthwise separable convolutions for image classification in resource-constrained autonomous systems.

In recent years, artificial intelligence (AI) has been developed vigorously, and a great number of AI autonomous applications have been proposed. However, how to decrease computations and shorten training time with high accuracy under the limited hardware resource is a vital issue. In this paper, on the basis of MobileNet architecture, the dense squeeze with depthwise separable convolutions model is proposed, viz. MiniNet. MiniNet utilizes depthwise and pointwise convolutions, and is composed of the dense connection technique and the Squeeze-and-Excitation operations. The proposed MiniNet model is implemented and experimented with Keras. In experimental results, MiniNet is compared with three existing models, i.e., DenseNet, MobileNet, and SE-Inception-Resnet-v1. To validate that the proposed MiniNet model is provided with less computation and shorter training time, two types as well as large and small datasets are used. The experimental results showed that the proposed MiniNet model significantly reduces the number of parameters and shortens training time efficiently. MiniNet is superior to other models in terms of the lowest parameters, shortest training time, and highest accuracy when the dataset is small, especially.

On the Design of Blockchain-Based ECDSA With Fault-Tolerant Batch Verification Protocol for Blockchain-Enabled IoMT.

The blockchain-enabled internet of medical things (IoMT) is an emerging paradigm that could provide strong trust establishment and ensure the traceability of data sharing in the IoMT networks. One of the fundamental building blocks for Blockchain is Elliptic Curve Digital Signature Algorithm (ECDSA). Nevertheless, when processing a large number of transactions, the verification of multiple signatures will incur cumbersome overhead to the nodes in Blockchain. Although batch verification is able to provide a promising approach that verifies multiple signatures simultaneously and efficiently, the upper bound of batch size is limited to small-scale and the efficiency will drop rapidly as the batch size grows in the state-of-the-art ECDSA batch schemes. Meanwhile, most of the existing researches only focus on improving the efficiency of batch verification algorithms in various cryptosystem while ignoring the identification of invalid signatures, which could cause severe performance degradation when the batch verification fails. Motivated by these observations, this paper proposes an efficient and large-scale batch verification scheme with group testing technology based on ECDSA. The application of the presented protocols in Bitcoin and Hyperledger Fabric has been analyzed as supportive and effective. When the batch verification returns a false result, we utilize group testing technology to improve the efficiency of identifying invalid signatures. Comprehensive simulation results demonstrate that our protocol outperforms the related ECDSA batch verification schemes.

Security and Privacy Techniques in IoT Environment.

Due to rapid technical advancements, many devices in the Internet of Things (IoT) environment, such as embedded systems, mobile devices, actuators, and sensors (all of which can be referred to as smart things), can receive huge amounts of information through data exchanging and interconnection [...].

Robust IoT-based nursing-care support system with smart bio-objects.

BACKGROUND: The significant advancement in the mobile sensing technologies has brought great interests on application development for the Internet-of-Things (IoT). With the advantages of contactlessness data retrieval and efficient data processing of intelligent IoT-based objects, versatile innovative types of on-demand medical relevant services have promptly been developed and deployed. Critical characteristics involved within the data processing and operation must thoroughly be considered. To achieve the efficiency of data retrieval and the robustness of communications among IoT-based objects, sturdy security primitives are required to preserve data confidentiality and entity authentication. METHODS: A robust nursing-care support system is developed for efficient and secure communication among mobile bio-sensors, active intelligent objects, the IoT gateway and the backend nursing-care server in which further data analysis can be performed to provide high-quality and on-demand nursing-care service. RESULTS: We realize the system implementation with an IoT-based testbed, i.e. the Raspberry PI II platform, to present the practicability of the proposed IoT-oriented nursing-care support system in which a user-friendly computation cost, i.e. 6.33 ms, is required for a normal session of our proposed system. Based on the protocol analysis we conducted, the security robustness of the proposed nursing-care support system is guaranteed. CONCLUSIONS: According to the protocol analysis and performance evaluation, the practicability of the proposed method is demonstrated. In brief, we can claim that our proposed system is very suitable for IoT-based environments and will be a highly competitive candidate for the next generation of nursing-care service systems.

Toward a Robust Security Paradigm for Bluetooth Low Energy-Based Smart Objects in the Internet-of-Things.

Bluetooth Low Energy (BLE) has emerged as one of the most promising technologies to enable the Internet-of-Things (IoT) paradigm. In BLE-based IoT applications, e.g., wearables-oriented service applications, the Bluetooth MAC addresses of devices will be swapped for device pairings. The random address technique is adopted to prevent malicious users from tracking the victim's devices with stationary Bluetooth MAC addresses and accordingly the device privacy can be preserved. However, there exists a tradeoff between privacy and security in the random address technique. That is, when device pairing is launched and one device cannot actually identify another one with addresses, it provides an opportunity for malicious users to break the system security via impersonation attacks. Hence, using random addresses may lead to higher security risks. In this study, we point out the potential risk of using random address technique and then present critical security requirements for BLE-based IoT applications. To fulfill the claimed requirements, we present a privacy-aware mechanism, which is based on elliptic curve cryptography, for secure communication and access-control among BLE-based IoT objects. Moreover, to ensure the security of smartphone application associated with BLE-based IoT objects, we construct a Smart Contract-based Investigation Report Management framework (SCIRM) which enables smartphone application users to obtain security inspection reports of BLE-based applications of interest with smart contracts.

A Novel Certificateless Signature Scheme for Smart Objects in the Internet-of-Things.

Rapid advances in wireless communications and pervasive computing technologies have resulted in increasing interest and popularity of Internet-of-Things (IoT) architecture, ubiquitously providing intelligence and convenience to our daily life. In IoT-based network environments, smart objects are embedded everywhere as ubiquitous things connected in a pervasive manner. Ensuring security for interactions between these smart things is significantly more important, and a topic of ongoing interest. In this paper, we present a certificateless signature scheme for smart objects in IoT-based pervasive computing environments. We evaluate the utility of the proposed scheme in IoT-oriented testbeds, i.e., Arduino Uno and Raspberry PI 2. Experiment results present the practicability of the proposed scheme. Moreover, we revisit the scheme of Wang et al. (2015) and revealed that a malicious super type I adversary can easily forge a legitimate signature to cheat any receiver as he/she wishes in the scheme. The superiority of the proposed certificateless signature scheme over relevant studies is demonstrated in terms of the summarized security and performance comparisons.