AIDPS:Adaptive Intrusion Detection and Prevention System for Underwater Acoustic Sensor Networks

Underwater Acoustic Sensor Networks (UW-ASNs) are predominantly used for underwater environments and find applications in many areas. However, a lack of security considerations, the unstable and challenging nature of the underwater environment, and the resource-constrained nature of the sensor nodes used for UW-ASNs (which makes them incapable of adopting security primitives) make the UW-ASN prone to vulnerabilities. This paper proposes an Adaptive decentralised Intrusion Detection and Prevention System called AIDPS for UW-ASNs. The proposed AIDPS can improve the security of the UW-ASNs so that they can efficiently detect underwater-related attacks (e.g., blackhole, grayhole and flooding attacks). To determine the most effective configuration of the proposed construction, we conduct a number of experiments using several state-of-the-art machine learning algorithms (e.g., Adaptive Random Forest (ARF), light gradient-boosting machine, and K-nearest neighbours) and concept drift detection algorithms (e.g., ADWIN, kdqTree, and Page-Hinkley). Our experimental results show that incremental ARF using ADWIN provides optimal performance when implemented with One-class support vector machine (SVM) anomaly-based detectors. Furthermore, our extensive evaluation results also show that the proposed scheme outperforms state-of-the-art bench-marking methods while providing a wider range of desirable features such as scalability and complexity.

Customer Empowered Privacy-Preserving Secure Verification using Decentralized Identifier and Verifiable Credentials For Product Delivery Using Robots

In the age of respiratory illnesses like COVID 19, we understand the necessity for a robot based delivery system to ensure safe and contact free courier delivery. A blockchain based Dynamic IDentifier gives people total power over their identities while preserving auditability and anonymity. A human mobile phone and a robot are machines created with a chip, making it simple to deploy a physical unclonable function based verification system between the robot and the customer. This article presents a novel framework and a first customer verification scheme for verified courier delivery utilizing the blockchain enabled DID and PUF enabled robots. We employ DID for customer authentication between a robot (a service provider) and a customer and PUF for robot verification by the customer. We ve also put the proposed work into practice and demonstrated its capabilities in terms of throughput, latency, computing cost, and communication cost. We also show formal security proof for the proposed user verification scheme based on the tamarin prover.