Well-being, aging and health is a multidimensional concept covering well-being, aging and health aspects of individuals, communities and ecosystems in the appropriate contexts. Various technology-enabled solutions can contribute to well-being, aging and health goals, and one of key trending technologies enabling digital transformation in healthcare and medicine is Internet of Things. This paper proposes an approach to industrial Internet of Things-based ontology development for well-being, aging and health, in order to structure the knowledge concepts needed for data acquisition and the overall system to contribute to well-being, aging and health. Given its multidisciplinary nature and the need to make use of semantic structures for data processing and usage in Internet of Things-based applications, this scoping review elaborates on usage of ontologies for implementation of Internet of Things solutions, aiming at extending the ontology of choice, reusing parts of existing ontologies and adding new constructs for cross-domain reasoning. In order to enable more efficient use of resources at the application level, an abstract layer of semantic middleware should reason on acquired data and allow for application business logic to trigger actuators while preserving safety and security.

This paper presents results of the signal strength of the BLE v4.0 protocol used by the low-cost bracelet in an indoor environment. Low-cost BLE bracelets can be utilized as a patient monitoring platform, because has the ability to measure the vital parameters of patients. Thus providing the possibility of usage in hospitals and nursing homes for constant monitoring of patients. The application such a bracelets in a real environment has several limitations, and one of them is the signal range of the bracelet tested in this paper. The obtained results are presented together with the simulations for the frequency of 2.4GHz.With a range of up to 18.03m for the low-cost BLE bracelet in an indoor environment with obstacles.

The Internet-of-Things vision of ubiquitous and pervasive computing gives rise to future smart irrigation systems comprising the physical and digital worlds. A smart irrigation ecosystem combined with Machine Learning can provide solutions that successfully solve the soil humidity sensing task in order to ensure optimal water usage. Existing solutions are based on data received from the power hungry/expensive sensors that are transmitting the sensed data over the wireless channel. Over time, the systems become difficult to maintain, especially in remote areas due to the battery replacement issues with a large number of devices. Therefore, a novel solution must provide an alternative, cost- and energy-effective device that has unique advantage over the existing solutions. This work explores the concept of a novel, low-power, LoRa-based, cost-effective system that achieves humidity sensing using Deep Learning techniques that can be employed to sense soil humidity with high accuracy simply by measuring the signal strength of the given underground beacon device.

Finding a free parking lot contributes largely to a total traffic congestion and increases gas emissions in urban and overpopulated cities. Recent advances in smart parking systems adopt Internet of Things (IoT) concepts which tend to improve traffic bottlenecks by providing information about available parking lots. The detection of vehicle presence at the parking lot usually means adopting solutions comprised of power-hungry and battery-operated sensor devices. In this article a hardware-based approach is introduced which aims at building a self-powered and autonomous sensing node equipped with supercapacitors (battery less) to feel the vehicle presence. For purposes of detection, solar-based energy harvester and wake-up trigger prototype is considered along with a Bluetooth low-energy (BLE) radio. The joint use of such technologies is exploited to develop a power autonomous node capable of cost-effectively sensing the car presence and transmitting the parking lot status. The developed triggering system consumes only 150 nA making it suitable as a low-power solution. To initiate the trigger only 6.5 W/m2in light level change is required comparing the two panels, which is more than adequate as the comparison of solar irradiance measured under the vehicle against diffuse horizontal irradiance shows a significant difference. The developed prototype uses a magnetometer to verify the vehicle presence upon trigger generation and BLE 5.0 technology for status change update, while supercapacitor discharge lifetime duration is estimated to be around 13 days in harsh conditions without charging from solar cells.

A plethora of organizations, companies, and foremost universities and educational institutions are using WPA2-Enterprise protocol to allow their end-users to connect to provided Wi-Fi networks. When both the provider’s and the end-user’s devices are configured properly, it is considered one of the safest Wi-Fi connection protocols with the added benefits of having a unique password for every Wi-Fi user. However, a known evil twin attack can be performed to steal users’ Wi-Fi login credentials, if the devices are not configured correctly. Considering the widespread use of Wi-Fi-enabled smartphones and rising concerns regarding users’ privacy, we focus on the privacy aspects of WPA2-Enterprise vulnerabilities mainly on the widespread Eduroam network. We show that device deanonymization is a concerning liability of many Eduroam networks. More than 87% of 1650 devices collected during a two-month test on our university are vulnerable to MAC address deanonymization attack. Furthermore, by analyzing the Eduroam Configuration Assistant Tool of 1066 different institutions around the world, 67% of exported Eduroam profiles having the Wi-Fi device reveal the user’s identity in the clear, thus linking the users with the device’s MAC address. Indeed, the analysis of the configuration profiles has been confirmed by performing the deanonymization attack on a large-scale international music festival in our country, where 70% of the devices have been vulnerable. Additionally, we showcase the psychological aspects of secure Eduroam users, where some are willing to modify secure configuration profiles to gain aspects to certain blocked features. As a result, the attacker is granted with user credentials and IMSI number and provided with access to all Eduroam-related services.

User’s location privacy concerns have been further raised by today’s Wi‐Fi technology omnipresence. Preferred Network Lists (PNLs) are a particularly interesting source of private location information, as devices are storing a list of previously used hotspots. Privacy implications of a disclosed PNL have been covered by numerous papers, mostly focusing on passive monitoring attacks. Nowadays, however, more and more devices no longer transmit their PNL in clear, thus mitigating passive attacks. Hidden PNLs are still vulnerable against active attacks whereby an attacker mounts a fake SSID hotspot set to one likely contained within targeted PNL. If the targeted device has this SSID in the corresponding PNL, it will automatically initiate a connection with the fake hotspot thus disclosing this information to the attacker. By iterating through different SSIDs (from a predefined dictionary) the attacker can eventually reveal a big part of the hidden PNL. Considering user mobility, executing active attacks usually has to be done within a short opportunity window, while targeting nontrivial SSIDs from user’s PNL. The existing work on active attacks against hidden PNLs often neglects both of these challenges. In this paper we propose a simple mathematical model for analyzing active SSID dictionary attacks, allowing us to optimize the effectiveness of the attack under the above constraints (limited window of opportunity and targeting nontrivial SSIDs). Additionally, we showcase an example method for building an effective SSID dictionary using top‐N recommender algorithm and validate our model through simulations and extensive real‐life tests.

Many applications from the Internet of Things (IoT) domain used in healthcare, smart homes, and cities involve a large number of interconnected wireless devices. To ensure privacy, confidentiality, and integrity of the information, devices should be initialized prior to any communication. In this paper, we present a secure initialization method for constrained IoT devices such as wireless sensors devices and/or actuators. The solution uses visible light communication (VLC) for the initial configuration of the IoT devices. The VLC system consists of a modulated light source such as a smartphone screen and a very simple photodetector. We analyze known coding and modulation techniques used for the VLC and propose BlinkComm, a differential coding technique that achieves threefold increase in transmission speed compared to existing solutions. We showed through experiments with 32 participants that the proposed solution achieves fast completion times and low error rates as well as high user satisfaction levels.

Future healthcare systems, smart homes, and similar will involve a large number of smart inter-connected wireless devices (such as wireless sensor nodes). One of the major challenges to securing these systems presents loading initial cryptographic credentials into a relatively large number of wireless devices. Furthermore, many of these technologies involve low-cost and highly interface constrained devices (lacking usual wired interfaces, displays, keypads, and alike). We propose two novel multichannel key deployment schemes for wireless networks that only require a presence of a light source device, such as a multi-touch screen (tablet or smartphone device). The first key deployment scheme is based on secret key cryptography and is suitable for interface/resource-constrained wireless devices. The second scheme assumes a strong attacker and requires the use of public key cryptography. In both our solutions, we use one-way visible light channel of multi-touch screens (flashing displays) to initialize devices in a secure, usable, and scalable way. From the user's perspective, this boils down to placing the devices on the multitouch screen after which the remaining process is fully automatized. We showed through the experiments with 48 users that our solution is user-friendly and scales linearly with the number of nodes. Copyright © 2015 John Wiley & Sons, Ltd.

Classical password/PIN-based authentication methods have proven to be vulnerable to a broad range of observation attacks (such as key-logging, video-recording or shoulder surfing attacks). In order to mitigate these attacks, a number of solutions have been proposed, most of them being cognitive authentication schemes (challenge-response protocols that require users to perform some kind of cognitive operations). In this paper, we show successful passive side-channel timing attacks on two cognitive authentication schemes, a well-known Hopper-Blum (HB) protocol and a U.S. patent Mod10 method, previously believed to be secure against observation attacks. As we show, the main security weakness of these methods comes from detectable variations in the user's cognitive load that results from cognitive operations during the authentication procedure. We carried out theoretical analysis of both Mod10 and HB methods, as well as an experimental user study of Mod10 method with 58 participants to validate the results of our timing attacks. We also propose security enhancements of these schemes aimed to mitigate the timing side-channel attacks. The proposed enhancements show the existence of a strong tradeoff between security and usability, indicating that the security of cognitive authentication schemes comes at a non-negligible usability cost (e.g., increased overall login time). For this reason, the designers of new cognitive authentication schemes should not ignore possible threats induced by side-channel timing attacks.

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This paper reports two attacks on Undercover, a human authentication scheme against passive observers proposed at CHI 2008. The first attack exploits nonuniform human behavior in responding to authentication challenges and the second one is based on information leaked from authentication challenges or responses visible to the attacker. The second attack can be generalized to break two alternative Undercover designs presented at Pervasive 2009. All the attacks exploit design flaws of the Undercover implementations.