Decentralized identity (DID) is pivotal to Web3 applications as it empowers users to manage their identities and credentials without relying on any central authority. Multi-controller is a new and indispensable scenario outlined by the W3C DID standards, while its privacy and security issues have not yet been fully explored. In this paper, we find two new attacks caused by multiple controllers toward DID management, and propose a privacy-preserving and secure identity management scheme to defend against both attacks. The first proposed controller-correlation attack allows an attacker to infer relationships between different subjects by correlating the public keys uploaded by multiple controllers to the blockchain. To avoid this kind of privacy leakage, we propose a masking scheme based on the Merkle tree, which allows the controllers to prove their ownership over the multi-controller identities without publicizing the plaintext of their public keys. The other identity impersonation attack exploits insecure controller revocation caused by high block synchronization latency. To resist this attack, we propose a lightweight authentication scheme. The holders provide digest freshness proof while the verifiers only need to download block headers. To evaluate the feasibility of our proposed scheme, we implement our system on the Sepolia TestNet. The experimental result demonstrates that our system can prevent these attacks with acceptable gas consumption and time consumption, compared with the state-of-the-art.

The Payment Channel Network (PCN) has emerged as an extensively adopted solution to address the scalability issues of Bitcoin by efficient off-chain updates. However, conflicts arise while existing update protocols are pursuing multiple goals of security, privacy, and expressiveness. In this work, we propose a new off-chain update protocol, Secure and Anonymous Multi-Channel Updates (SAMCU), which is developed on the basis of Unspent Transaction Output (UTXO). SAMCU aims at achieving goals of internal anonymity, balance security, and multi-channel updates simultaneously, which has not been done before. To achieve these goals, we exploit the technique of updating graph splitting (UGS) to make participants aware of only the identities of their neighboring sub-graphs, thereby ensuring internal anonymity in multi-channel updates. Then, to avoid security issues arising from equal sub-graphs, we further propose an Enable Payment Transaction Tree (EPTT) to guarantee balance security for each honest protocol participant. Moreover, we optimize the performance of our solution, reducing transaction fees by splitting transactions and the number of communication connections by hierarchical communication. To evaluate the performance of the SAMCU, we implement a prototype involving up to 100 updating payment channels. Experimental results demonstrate that SAMCU outperforms the state-of-the-art, resulting in approximately 70% savings in communication connections and a 66% reduction in on-chain transaction fees when the number of updating payment channels is 100.

Energy harvesting gives a promising way to deal with the power constrained problem by harvesting energy from the external environment. In this paper, the multi-hop wireless network is considered where the relays with energy storage equipments are random scattered in several discs. The chosen relay nodes are used to decode-and-forward(DF) the received signals to the next terminal. The other active nodes in the discs harvest energy from the received signal. With the aim to achieve the minimum system outage probability, the close-form expressions are proposed about the optimal disc locations and about the optimal number of hops, respectively.

This study considers the effect of channel estimation error (CEE) on the soft‐output bit log‐likelihood ratio (LLR) in a multiple‐input–multiple‐output detection system which the source sends their quadrature amplitude modulation to the detector through Rayleigh fading channels. The new expressions of LLR with maximum‐likelihood CE for deterministic channel model and minimum mean square error (MMSE) CE for random channel model are obtained separately for linear MMSE receiver using known pilot‐symbol‐aided CE. Meanwhile, the optimal power allocation between training and data transmissions for these two different LLR expressions, which attends to get the maximum ratio of signal and interference plus noise ratio, are obtained under the total transmitting power constraints. Numerical results show that the power allocation ratio sets to be ∼0.5 is optimal for two new different LLRs at the same total power and system noise. Moreover, the derived LLR expressions match the simulation result and outperform the conventional system without the consideration of CEE and optimal power allocation. Meanwhile, the system performance is better than the existing research with the consideration of CE.