Digital legacy: designing with things

This paper explores how theories of things can create new forms of agency for the dead. It considers how meaning is constructed through the use or translation of our diverse collections and environments online. These memorials and rituals offer a plurality of narratives, experiences and aesthetics, which have the potential to give a wider scope for constructing a durable biography after death. The paper draws conceptual links between digital and physical materials and aims to expand interdisciplinary discourse around the way design can create new forms of legacy through rethinking the role of digital things in our lives

Situation aware intrusion recovery policy in WSNs

Wireless Sensor Networks (WSNs) have been gaining tremendous research attention the last few years as they support a broad range of applications in the context of the Internet of Things. WSN-driven applications greatly depend on the sensors’ observations to support decision-making and respond accordingly to reported critical events. In case of compromisation, it is vital to recover compromised WSN services and continue to operate as expected. To achieve an effective restoration of compromised WSN services, sensors should be equipped with the logic to take recovery decisions and self-heal. Self-healing is challenging as sensors should be aware of a variety of aspects in order to take effective decisions and maximize the recovery benefits. So far situation awareness has not been actively investigated in an intrusion recovery context. This research work formulates situation aware intrusion recovery policy design guidelines in order to drive the design of new intrusion recovery solutions that are operated by an adaptable policy. An adaptable intrusion recovery policy is presented taking into consideration the proposed design guidelines. The evaluation results demonstrate that the proposed policy can address advanced attack strategies and aid the sensors to recover the network’s operation under different attack situations and intrusion recovery requirements

WSN operability during persistent attack execution

Wireless Sensor Networks (WSNs) are utilized in a number of critical infrastructures, e.g. healthcare, disaster and relief. In sensitive environments, it is vital to maintain the operability of the network in an effort to support the decision-making process that depends on the sensors’ observations. The network’s operability can be maintained if observations can reach the specified destination and also if the sensors have adequate energy resources. The operability is negatively affected by security attacks, such as the selective forward and the denial of service (DoS), that can be executed against the WSN. The attacks’ impact greatly depends on the attackers’ capabilities such as their knowledge and the number of malicious nodes they hold. Currently, the research community focuses on addressing casual attackers that don’t persist with their attack strategy. However, the proposed solutions cannot address persistent attackers that continue with their attack execution after the network has applied appropriate recovery countermeasures. Designing an adaptive recovery strategy is challenging as a number of issues need to be taken into consideration such as the network’s density, the number of malicious nodes and the persistent attack strategy. This research work formulates a persistent attack strategy and investigates the integration of different recovery countermeasures in WSNs. The evaluation results demonstrate that an adaptive recovery strategy can enhance the network’s recovery benefits, in terms of increased packet delivery and decreased energy consumption, and prolong its operability. Moreover, the observations made are envisioned to encourage new contributions in the area of adaptive intrusion recovery in WSNs

Received Signal Strength for Randomly Distributed Molecular Nanonodes

We consider nanonodes randomly distributed in a circular area and characterize the received signal strength when a pair of these nodes employ molecular communication. Two communication methods are investigated, namely free diffusion and diffusion with drift. Since the nodes are randomly distributed, the distance between them can be represented as a random variable, which results in a stochastic process representation of the received signal strength. We derive the probability density function of this process for both molecular communication methods. Specifically for the case of free diffusion we also derive the cumulative distribution function, which can be used to derive transmission success probabilities. The presented work constitutes a first step towards the characterization of the signal to noise ratio in the considered setting for a number of molecular communication methods.Comment: 6 pages, 6 figures, Nanocom 2017 conferenc