One of the essential challenges is authentication between service offering Fog servers or nodes and Fog users or Edges. This security confirmation is vital as a large number of users are provided with the services in Fog Computing. The paper proposes an efficient mutual authentication method between Cloud- Fog - Edges. The solution helps for the authentication between edges and newly entering Fog servers as at any instant joining and leaving of the servers to the network happens. The method reduces the overheads and re-registration of the user to the servers. The technique makes the Fog servers to store one secret key peruses and the users to perform the hash calculation with encryptions/decryptions. The sensitive data are encrypted and available at many cloud servers for low latency. Whenever the request is posed from users the Fog nodes search for this encrypted data and made available to the requestor based on authenticated access policy. Another work of the paper is the hybrid of encryption of both index and data file based on fine-grained access policy. The encryption used is ciphertext-policy attribute-based encryption (CP-ABE). The method shares the same key pair thereby reducing the key management cost and improving the efficiency of data used by users. The system is supported by the Blockchain technique to achieve data integrity when confidential data is transferred between edge devices and nodes. The transactions between the nodes are recorded in the blocks which are hashed so that a secured system encircles the whole edge and fog nodes. Whenever any malicious edge enters the network, it is identified based on ledger maintained at the nodes. The security and performance analysis shows the scheme is apt for the Fog computing environment.

Edge computing reduces the overhead of data centers and improves the efficiency of data processing. However, traditional cloud data protection mechanisms are no longer applicable to edge devices. Data leakage and other privacy issues may occur when computation is outsourced to edge nodes. The decentralization raises new privacy challenge for data control, storage and computation. In this work, we present Cerberus, a brand-new framework that preserves data privacy in edge computing by combining blockchain, distributed data storage and trusted execution environment (TEE). Blockchain is used to maintain a global computation state, and also acts as a medium of information interaction. Distributed data storage provides a secure and large-capacity storage. TEE-based off-chain computation guarantees confidentiality and efficiency of data processing. We also implement a prototype of Cerberus using Hyperledger Fabric and Intel SGX. Our evaluation on a sample of data sorting application shows that Cerberus achieves significant speed ups over previous cryptographic schemes. Compared with non-secure computation, Cerberus can preserve data privacy without incurring much performance loss.

Blockchain technology is a new distributed infrastructure and computing mode in recent years, and it provides a distributed data management solution for storage, authentication, transfer and exchange. In order to shorten the confirmation time of block data transaction and improve the processing capacity of blockchain, it is necessary to solve the problem of data communication performance optimization in blockchain transaction validation. This paper proposes a concurrent weighted communication tree algorithm for blockchain transaction (called WFT). This algorithm comprehensively considers the communication weight and the node communication link number. Several small-weight nodes with powerful transmitting capacity are selected to locate in the top or upper part of the communication tree to improve the concurrency and efficiency. The proposed algorithm can provide the routing paths for blockchain transaction, and can improve the communication efficiency on blockchain.

Federated learning (FL) is the collaborative machine learning (ML) technique whereby the devices collectively train and update a shared ML model while preserving their personal datasets. FL systems solve the problems of communication-efficiency, bandwidth-optimization, and privacy-preservation. Despite the potential benefits of FL, one centralized shared ML model across all the devices produce coarse-grained predictions which, in essence, are not required in many application areas involving personalized prediction services. In this paper, we present a novel concept of fine-grained FL to decentralize the shared ML models on the edge servers. We then present a formal extended definition of fine-grained FL process in mobile edge computing systems. In addition, we define the core requirements of fine-grained FL systems including personalization, decentralization, fine-grained FL, incentive mechanisms, trust, activity monitoring, heterogeneity and context-awareness, model synchronization. and communication and bandwidth-efficiency. Moreover, we present the concept of blockchain-based reputation-aware fine-grained FL in order to ensure trustworthy collaborative training in mobile edge computing systems. Finally, we perform the qualitative comparison of proposed approach with state-of-the-art related work and found some promising initial results.

Smart contract helps to broaden the application of blockchain to many fields. In many cases, the non-blockchain systems (NBS) are involved. However, when a smart contract directly interacts with NBS, there is a non-deterministic issue (or a state conflict issue). The reason is that different nodes may obtain different statuses of NBS when the state changes in NBS. If we can solve this issue, a smart contract can be used to interact with current systems without an additional adaptor or bridge required by the existing solutions. In this paper, we regard the states of NBS as a sequence of states instead of a single state and propose to solve the non-deterministic issue by state synchronization. Blockchain nodes synchronize the state of the non-blockchain server via the P2P protocol. The state synchronization has requirements for both blockchain and NBS. For blockchain, it should provide the mechanism to synchronize states obtained from NBS. For NBS, it should sign the query result with a timestamp; the signature prevents the cheat of the observer (the blockchain), and the timestamp ensures the order of a state in the state sequence. At last, we show our verification results with respect to our proposed model and method.

Nowadays, many novel blockchain-based architecture and frameworks are proposed to solve issues in computer science and financial service. Smart contracts with blockchain systems, especially consortium blockchain systems, can help to provide many reliable and efficient functions for existing systems like smart grid payments. The novel concept of smart contract as a service is proposed but the difficulty of developing smart contracts on various kinds of blockchain systems are also significantly increasing which brings the additional cost for both developers and infrastructure builders. In this paper, we present an updated cloud-based smart integrated smart contract development system, ChainIDE 2.0, for the ultra-efficient development of blockchain-based smart contracts on multiple kinds of blockchain systems. Not only we stay as the most popular cloud-based developing Integrated Development Environment (IDE) for the Libra blockchain, but also we introduce the consortium blockchain systems such as Ant Financial Open-Chain (Ant OC) and served as the first cloud-based IDE supporting the Ant Financial OpenChain test net. Today, we have served more than 530k compiled smart contracts which makes us the most popular cloud-based blockchain development IDE in the world.

Random number generators (RNG) play an essential role in blockchains and directed acyclic graphs. The authors formulate the generation task as a Byzantine fault-tolerance problem and provide a relation between RNG and consensus. Taking this correspondence into account, the authors propose a novel protocol for RNG for synchronous systems and test its implementation in the form of a smart contract. The proposed algorithm and code can be used as service in the existing distributed ledger or as a building block of a new one.

Since Bitcoin's seminal work of achieving consensus under the assumption that more than 51% computational power is honest, many researchers have proposed various kinds of consensus protocols. In recent years, there has been a trend in designing proof of stake (PoS) based consensus protocols. Unfortunately, PoS based consensus protocols are inherently not secure and are vulnerable to ``long range attacks''. Thus PoS based blockchains have the potential risk of being forked with a minimal cost for double spending. In this paper, we propose a PoS protocol that is secure against long range attack based double spending. The security is achieved using secure randomness beacons generated by tamper proof hardware modules.

As a very appealing computing standard, cloud computing makes it feasible for resource-constrained clients to experience rate-effective and flexible resources at ease. In the prevailing systems, the conventional cloud storage scheme is bound to operate its primitive functions in centralized mode. This reason possesses problems like data availability, information protection and excessive operational charge. With the improvement of blockchain generation, the decentralized scheme has entered the general public view. Compared to contemporary and cutting- edge cloud storage, they are predicted to be more scalable, securable and comfortable. But, the use of end-to-end encryption in a decentralized scheme limits the search functionality as the existing searchable encryption methods are designed only for the centralized device. Moreover, the existing decentralized cloud storage doesn't restrict any data user to get access to all of the files for any keyword search made purposefully through them. Thus, in this manner, user integrity of files and keyword searches are compromised throughout the network. Therefore, as a manner to solve these complications, we systematically join techniques of encryption and hashing to furnish reliable keyword search over encrypted files in decentralized storage. Consequently using the blockchain system, the architecture remains incorruptible and protects all the confidential files and keywords in a fully controlled file access environment.

We propose a scalable and verifiable transmission recording system based on trusted execution environment (TEE) to support payment system for decentralized services. In the proposed system, consensus of the service is easy to reach based on the service recording chains via mutual recording among participating nodes of the service; A simplified Merkle tree structure is used in the service records for checking the integrity of the transmission content, which facilitates efficient re-transmission of lost packets among neighboring nodes, and tracking of multi-path transmissions. The proposed system enables efficient and trusted incentive mechanisms to support network transmission services via edge devices (mobile devices, moving connected vehicles, base stations, etc.) in dynamic and self-organizing networks.

Blockchain technology is the fundamental technology for digital currency such as Bitcoin. Because blockchain can establish credit between unfamiliar nodes in distributed systems, there are no more centralized credit entities in emerging digital currency systems. It's challenging for financial regulators and state agencies to supervise and manage the participants in the digital money system and the transactions between them. In this paper, a double-chain based regulatable model is proposed to solve this problem. In the aspect of the consensus mechanism, we introduce an agreement protocol based on the Credit Practical Byzantine Fault Tolerance to improve the system efficiency. The experimental results show that the proposed double-chain model works effectively, and the consensus mechanism and overall performance meet the design requirements.

Recent years have witnessed a boom of connected medical devices, which brings security issues in the meantime. Medical imaging devices, an essential part of medical cyber-physical systems, play a vital role in modern hospitals and are often life-critical. However, security and privacy issues in these medical cyber-physical systems are sometimes ignored. In this paper, we perform an empirical study on imaging devices to analyse the security of medical cyber-physical systems. To be precise, we design a threat model and propose prospective attack techniques for medical imaging devices. To tackle potential cyber threats, we introduce protection mechanisms, evaluate the effectiveness and efficiency of protection mechanisms as well as its interplay with attack techniques. To scoring security, we design a hierarchical system that provides actionable suggestions for imaging devices in different scenarios. We investigate 15 devices from 9 manufacturers to demonstrate empirical comprehension and real-world security issues.

The unprecedented growth of smart home industry brings increasing amount of IoT devices into people's home. The transmission of data and execution of commands across connected network were meant to bring security, comfort and accessibility. However, the inter-connectivity and complexity of smart home systems leads to higher vulnerability to cyberattack, network congestion and information leak. In this paper, we first analyze the limitations of existing centralized approaches. Then we propose a blockchain-enabled solution to help build a secure smart home system. We demonstrate the design architecture and implementation methods as a proof of concept. We believe that the proposed blockchain-enabled solution can improve security while offering intelligent control of smart home systems.