Payment Channel Networks (PCNs) have successfully replaced slow global consensus mechanisms with local cryptographic agreements between nodes. As PCN payments heavily depend on network topology for payment routing, strategic node positioning is critical to building cost-effective channels for users and enhancing network robustness against topological attacks. Nevertheless, existing node attachment strategies in the Lightning Network (LN), the most popular PCN, ignore crucial topology issues, such as network centralization and the scarcity of cycles for cheap off-chain rebalancing. In this paper, we first investigate the current state of the LN topology and show that the availability of topology cycles is highly unequal in the network, which exposes the network to several vulnerabilities. Then, we design ProfitPilot, a node positioning strategy that encourages cycle creation in PCNs to reverse the trend in centralization and enable cheap off-chain rebalancing. We compare our proposed algorithm with heuristics available in the Lightning Network and verify that even by focusing on creating cycles, ProfitPilot successfully increases the user’s probability of collecting fees by over 2× while reducing average paying fees. Furthermore, out of all the evaluated heuristics, ProfitPilot presents the fastest increase in network transitivity and mitigates the impact of targeted topological attacks by over 17% compared with the regular Lightning Network operation.

Flow classification employs machine learning techniques to identify attacks on computer networks. This classification relies on quantitative features that synthesize the information of packets from the same flow. Conventional features, however, such as packet size and the number of bytes, generate redundancies and do not capture the temporal correlations between the packets in a flow. Automated network attacks generate periodic patterns observable through spectral decomposition, which facilitates classification. This paper proposes FENED (Feature Extraction by Network spEctrum Decomposition), a method to extract features from network data. We consider the packet-arrived order within the same flow using the fast Fourier transform for binary classification. The proposed feature vector contains the module of the spectral components of the flow. Experimental results show that FENED outperforms conventional proposals because it extracts features that consider intra-flow packet-arrival order.

Service provisioning in next-generation networks, such as 5G and 6G, relies on virtualization to carry out multi-domain and multi-tenant connections. In these scenarios, virtual network functions (VNF) orchestration becomes susceptible to security threats once trust between peers cannot be assumed. This paper1proposes a blockchain-based system for an agile, secure, and distributed provisioning of virtual network functions in scenarios with multiple administrative domains. Our proposal employs smart contracts to deliver all stages of a service-level-agreement management life cycle automatically. We develop, implement, and evaluate a prototype of the proposed system using smart contracts running on Hyperledger Fabric. The performance evaluation results show that the system guarantees high-rate VNF provisioning, reaching hundreds of slice requests per second in a trustful way.

Blockchain and Smart Contracts ensure security and automation in trustless scenarios, leading to innovative solutions in various industry branches. The Hyperledger open-source project adopts these technologies in the corporate business, providing platforms for developing distributed applications. This paper analyses and compares two widely used platforms to develop applications based on permissioned blockchains: Hyper-ledger Sawtooth and Hyperledger Fabric. We implement two prototypes based on the same smart contract to evaluate the performance of each tool. The results show that: i) Sawtooth parallel transaction execution performs up to 30% better than serial execution only if the number of conflicting transactions remains low, and ii) Fabric has a much faster consensus protocol, but presents a low performance if the transactions are conflicting.

The trust centralization in current data sharing systems restricts the owner's control over their data. Furthermore, the owner's intervention to authorize his/hers data access for each request makes frequent access to popular data tiresome. In this paper, we propose AutAvailChain, an architecture based on software defined networking (SDN) and blockchain to provide secure, automatic, and distributed sharing of IoT data. We develop a prototype using the Hyperledger Fabric platform to implement the blockchain and a smart contract. The results show a quick, secure, and excellent performance of dozens of transactions per second.

Network slicing, network function virtualization (NFV), and software defined network (SDN) technologies provide agile on-demand end-to-end services. The identification of a faulty virtual function becomes mandatory because services allocate resources across a distributed and trustless environment composed by multi-tenant competing service providers. In this paper, we propose and develop a blockchain-based architecture to provide auditability to orchestration operations of network slices and to provide secure VNF configuration updates while ensuring isolation and privacy between network slices. A proof of concept prototype using the Hyperledger Fabric platform was developed in which network slice runs on an isolated channel. The results show that we can secure a network slice creation, but that the consensus and the number of transaction required by the slices are a great challenge.