No abstract

ABSTRACT

Wireless sensor networks (WSNs) are susceptible to many security threats and are specifically prone to physical node capture in which the adversary can easily launch the so-called insider attacks such as node compromise, bypassing the traditional security mechanisms based on cryptography primitives. So, the compromised nodes can be modified to misbehave and disrupt the entire network and can successfully perform the authentication process with their neighbors, which have no way to distinguish fraudulent nodes from trustworthy ones. Trust and reputation systems have been recently suggested as a powerful tools and an attractive complement to cryptography-based schemes in securing WSNs. They provide ability to detect and isolate both faulty and malicious nodes. Considerable research has been done on modeling and managing trust and reputation. However, trust topic issue in WSNs remains an open and challenging field. In this paper, we propose a Risk-aware Reputation-based Trust (RaRTrust) model for WSNs. Our novel framework uses both reputation and risk to evaluate trustworthiness of a sensor node. Risk evaluation is used to deal with the dramatic spoiling of nodes, which makes RaRTrust robust to on-off attack and differ from other trust models based only on reputation. This paper contributes to model the risk as opinion of short-term trustworthiness combining with traditional reputation evaluation to derive trustworthiness in WSNs.

In recent years, the interest in using wireless communication technologies and mobile devices in the healthcare environment has increased. However, despite increased attention to the security of electronic health records, patient privacy is still at risk for data breaches. Thus, it is quite a challenge to involve an access control system especially if the patients' medical data are accessible by users who have diverse privileges in different situations. Blockchain is a new technology that can be adopted for decentralized access control management issues. Nevertheless, different scalability, security, and privacy challenges affect this technology. To address these issues, we suggest a novel Decentralized Self-Management of data Access Control (DSMAC) system using a blockchain-based Self-Sovereign Identity (SSI) model for privacy-preserving medical data, empowering patients with mechanisms to preserve control over their personal information and allowing them to self-grant access rights to their medical data. DSMAC leverages smart contracts to conduct Role-based Access Control policies and adopts the implementation of decentralized identifiers and verifiable credentials to describe advanced access control techniques for emergency cases. Finally, by evaluating performance and comparing analyses with other schemes, DSMAC can satisfy the privacy requirements of medical systems in terms of privacy, scalability, and sustainability, and offers a new approach for emergency cases.INDEX TERMS Blockchain, data privacy, decentralized access control, decentralized IDentifier (DID), IoMT sensors, Self Sovereign Identity (SSI), smart contract, verifiable credential (VC).

Localization is an important topic in mobile wireless ad hoc and sensor networks, which has received considerable attention from the research community during the past few decades. In many sensor networks applications, location awareness is useful or even necessary. However, because of their key role in wireless sensor networks, localization systems can be the target of an attack that could compromise the entire functioning of a wireless sensor network. In this paper, we present a novel defense mechanism against wormhole attacks in DV‐Hop localization algorithm. The main idea of our approach is to plug in a proactive countermeasure to the basic DV‐Hop scheme called Infection prevention. We choose the wormhole attack as our defending target because it is a particularly challenging attack that can be successfully launched without compromising any nodes or having access to any cryptographic keys. Using analysis and simulation, we show that our solution is effective in detecting and defending against wormhole attacks with a high detection rate. Copyright © 2011 John Wiley & Sons, Ltd.