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Wireless Sensor Networks (WSNs) are susceptible to a wide range of attacks due to their distributed nature, limited sensor resources, and lack of tamper resistance. Once a sensor is corrupted, the adversary learns all secrets. Thereafter, most security measures become ineffective. Recovering secrecy after compromise requires either help from a trusted third party or access to a source of high-quality cryptographic randomness. Neither is available in Unattended Wireless Sensor Networks (UWSNs), where the sink visits the network periodically. Prior results have shown that sensor collaboration is an effective but expensive means of obtaining probabilistic intrusion resilience in static UWSNs. In this paper, we focus on intrusion resilience in Mobile Unattended Wireless Sensor Networks (μUWSNs), where sensors move according to some mobility models. Note that such a mobility feature could be independent from security (e.g., sensors move to improve area coverage). We define novel security metrics to evaluate intrusion resilience protocols for sensor networks. We also propose a cooperative protocol that - by leveraging sensor mobility - allows compromised sensors to recover secure state after compromise. This is obtained with very low overhead and in a fully distributed fashion. Thorough analysis and extensive simulations support our findings.

In this paper, we present a novel probabilistic protocol (COKE) to allow two wireless communicating parties to commit over-the-air (OTA) on a shared secret, even in the presence of a globally eavesdropping adversary. The proposed solution leverages no crypto but just plaintext messages exchange. Indeed, the security of the solution relies on the difficulty for the adversary to correctly identify, for each one-bit transmission, the sender of that bit-not its value, which is indeed exchanged in cleartext. Due to the low requirements of COKE (essentially, the capability to send a few wireless messages), it is particularly suited for resource constrained wireless devices (e.g., WNSs, wireless embedded systems), as well as for those scenarios where just energy saving is at premium, such as smartphones.

This paper offers a new role engineering approach to Role-Based Access Control (RBAC), referred to as visual role mining. The key idea is to graphically represent user-permission assignments to enable quick analysis and elicitation of meaningful roles. First, we formally define the problem by introducing a metric for the quality of the visualization. Then, we prove that finding the best representation according to the defined metric is a NP-hard problem. In turn, we propose two algorithms: ADVISER and EXTRACT. The former is a heuristic used to best represent the user-permission assignments of a given set of roles. The latter is a fast probabilistic algorithm that, when used in conjunction with ADVISER, allows for a visual elicitation of roles even in absence of predefined roles. Besides being rooted in sound theory, our proposal is supported by extensive simulations run over real data. Results confirm the quality of the proposal and demonstrate its viability in supporting role engineering decisions.