As we move into a new decade, the global world of Intelligent Infrastructure (II) services integrated into the Internet of Things (IoT) are at the forefront of technological advancements. With billions of connected devices spanning continents through interconnected networks, security and privacy protection techniques for the emerging II services become a paramount concern. In this paper, an up-to-date privacy method mapping and relevant use cases are surveyed for II services. Particularly, we emphasize on post-quantum cryptography techniques that may (or must when quantum computers become a reality) be used in the future through concrete products, pilots, and projects. The topics presented in this paper are of utmost importance as (1) several recent regulations such as Europe's General Data Protection Regulation (GDPR) have given privacy a significant place in digital society, and (2) the increase of IoT/II applications and digital services with growing data collection capabilities are introducing new threats and risks on citizens' privacy. This in-depth survey begins with an overview of security and privacy threats in IoT/IIs. Next, we summarize some selected Privacy-Enhancing Technologies (PETs) suitable for privacy-concerned II services, and then map recent PET schemes based on post-quantum cryptographic primitives which are capable of withstanding quantum computing attacks. This paper also overviews how PETs can be deployed in practical use cases in the scope of IoT/IIs, and maps some current projects, pilots, and products that deal with PETs. A practical case study on the Internet of Vehicles (IoV) is presented to demonstrate how PETs can be applied in reality. Finally, we discuss the main challenges with respect to current PETs and highlight some future directions for developing their post-quantum counterparts.

The life history of the fruit fly (Drosophila melanogaster) is well understood, but fitness components are rarely measured by following single individuals over their lifetime, thereby limiting insights into lifetime reproductive success, reproductive senescence and post‐reproductive lifespan. Moreover, most studies have examined long‐established laboratory strains rather than freshly caught individuals and may thus be confounded by adaptation to laboratory culture, inbreeding or mutation accumulation. Here, we have followed the life histories of individual females from three recently caught, non‐laboratory‐adapted wild populations ofD. melanogaster. Populations varied in a number of life‐history traits, including ovariole number, fecundity, hatchability and lifespan. To describe individual patterns of age‐specific fecundity, we developed a new model that allowed us to distinguish four phases during a female's life: a phase of reproductive maturation, followed by a period of linear and then exponential decline in fecundity and, finally, a post‐ovipository period. Individual females exhibited clear‐cut fecundity peaks, which contrasts with previous analyses, and post‐peak levels of fecundity declined independently of how long females lived. Notably, females had a pronounced post‐reproductive lifespan, which on average made up 40% of total lifespan. Post‐reproductive lifespan did not differ among populations and was not correlated with reproductive fitness components, supporting the hypothesis that this period is a highly variable, random ‘add‐on’ at the end of reproductive life rather than a correlate of selection on reproductive fitness. Most life‐history traits were positively correlated, a pattern that might be due to genotype by environment interactions when wild flies are brought into a novel laboratory environment but that is unlikely explained by inbreeding or positive mutational covariance caused by mutation accumulation.

In July 2020, the lattice-based CRYSTALS-Dilithium digital signature scheme has been chosen as one of the three third-round finalists in the post-quantum cryptography standardization process by the National Institute of Standards and Technology (NIST). In this work, we present the first Very High Speed Integrated Circuit Hardware Description Language (VHDL) implementation of the CRYSTALS-Dilithium signature scheme for Field-Programmable Gate Arrays (FPGAs). Due to our parallelization-based design requiring only low numbers of cycles, running at high frequency and using reasonable amount of hardware resources on FPGA, our implementation is able to sign 15832 messages per second and verify 10524 signatures per second. In particular, the signing algorithm requires 68461 Look-Up Tables (LUTs), 86295 Flip-Flops (FFs), and the verification algorithm takes 61738 LUTs and 34963 FFs on Virtex 7 UltraScale+ FPGAs. In this article, experimental results for each Dilithium security level are provided and our VHDL-based implementation is compared with related High-Level Synthesis (HLS)-based implementations. Our solution is ca 114 times faster (in the signing algorithm) and requires less hardware resources.

Cybersecurity education and training are essential prerequisites of achieving a secure and privacy-friendly digital environment. Both professionals and the general public widely acknowledge the need for high-quality university education programs and professional training courses. However, guides, recommendations, practical tools, and good examples that could help institutions design appropriate cybersecurity programs are still missing. In particular, a comprehensive method to identify skills needed by cybersecurity work roles offered on the job market is missing. This paper aims to provide practical tools and strategies to help higher education providers design good cybersecurity curricula. First, we analyze the content of 89 existing study programs worldwide, collect recommendations of renowned institutions within and outside the EU, and provide a comprehensive survey accompanied by a dynamic web application called Education Map. Based on the knowledge about the current state in cybersecurity education, we design the SPARTA Cybersecurity Skills Framework that provides the currently missing link between work roles and required expertise and shows how to develop a curriculum that reflects job market requirements. Finally, we provide a practical tool that implements the framework and helps education and training providers design new study programs and analyze existing ones by considering the requirements of cybersecurity work roles.

Before releasing an anonymized data set, the data protector must know how safe the data set is, that is, how much disclosure risk is incurred by the release. If no privacy model is used to select specific privacy guarantees prior to anonymization, posterior disclosure risk assessment must be performed based on the anonymized data set and, if the result is not satisfactory, anonymization must be repeated with stricter privacy parameters. Even if a privacy model is used, it may still be advisable to empirically evaluate disclosure on the anonymized data set, especially if the privacy model parameters have been relaxed to improve data utility. Record linkage is a general methodology to posterior disclosure risk assessment, whereby the data protector attempts to recreate the attacker's re-identification scenario. An important limitation of record linkage is that it usually requires the data protector to make restrictive assumptions on the attacker's background knowledge. To overcome this limitation, we present a maximum-knowledge attacker model and then we specify and compare several record linkage tests for such a worst-case attacker. Our tests are based on comparing the distribution of linkage distances between the original and the anonymized data set with the distribution of distances between one of the two previous data sets and one random data set. The more similar the distributions, the more plausibly deniable are record linkages claimed by an attacker. Because attaining zero disclosure risk for all records is too costly in terms of utility, a less demanding alternative is presented whose goal is to reduce the maximum per-record disclosure risk.