Solutions and Tools for Secure Communication in Wireless Sensor Networks

Secure communication is considered a vital requirement in Wireless Sensor Network (WSN) applications. Such a requirement embraces different aspects, including confidentiality, integrity and authenticity of exchanged information, proper management of security material, and effective prevention and reaction against security threats and attacks. However, WSNs are mainly composed of resource-constrained devices. That is, network nodes feature reduced capabilities, especially in terms of memory storage, computing power, transmission rate, and energy availability. As a consequence, assuring secure communication in WSNs results to be more difficult than in other kinds of network. In fact, trading effectiveness of adopted solutions with their efficiency becomes far more important. In addition, specific device classes or technologies may require to design ad hoc security solutions. Also, it is necessary to efficiently manage security material, and dynamically cope with changes of security requirements. Finally, security threats and countermeasures have to be carefully considered since from the network design phase. This Ph.D. dissertion considers secure communication in WSNs, and provides the following contributions. First, we provide a performance evaluation of IEEE 802.15.4 security services. Then, we focus on the ZigBee technology and its security services, and propose possible solutions to some deficiencies and inefficiencies. Second, we present HISS, a highly scalable and efficient key management scheme, able to contrast collusion attacks while displaying a graceful degradation of performance. Third, we present STaR, a software component for WSNs that secures multiple traffic flows at the same time. It is transparent to the application, and provides runtime reconfigurability, thus coping with dynamic changes of security requirements. Finally, we describe ASF, our attack simulation framework for WSNs. Such a tool helps network designers to quantitatively evaluate effects of security attacks, produce an attack ranking based on their severity, and thus select the most appropriate countermeasures

A Simulation Tool for Evaluating Attack Impact in Cyber Physical Systems

Abstract. Security is getting an ever increasingly important issue in cyber-physical systems comprising autonomous systems. However, it is not possible to defend from all possible attacks for cost and performance reasons. An attack ranking is thus necessary. We propose a simulative framework that makes it possible to rank attacks according to their impact. We also describe a case study to assert its usefulness and effectiveness

Vulnerabilities of the 6P protocol for the Industrial Internet of Things: Impact analysis and mitigation

The 6TiSCH architecture defined by the IETF provides a standard solution for extending the Internet of Things (IoT) paradigm to industrial applications with stringent reliability and timeliness requirements. In this context, communication security is another crucial requirement, which is currently less investigated in the literature. In this article, we present a deep assessment of the security vulnerabilities of 6P, the protocol used for resource negotiation at the core of the 6TiSCH architecture. Specifically, we highlight two possible attacks against 6P, namely the Traffic Dispersion and the Overloading attacks. These two attacks effectively and stealthy alter the communication schedule of victim nodes and severely thwart network basic functionalities and efficiency, by specifically impacting network availability and energy consumption of victim nodes. To assess the impact of the attacks two analytical models have been defined, while, to demonstrate their feasibility, they have been implemented in Contiki-NG. The implementation has been used to quantitatively evaluate the impact of the two attacks by both simulations and measurements in a real testbed. Our results show that the impact of both attacks may be very significant. The impact, however, strongly depends on the position of the victim node(s) in the network and it is highly influenced by the dynamics of the routing protocol. We have investigated mitigation strategies to alleviate this impact and proposed an extended version of the Minimal Scheduling Function (MSF), i.e., the reference scheduling algorithm for 6TiSCH. This allows network nodes to early detect anomalies in their schedules possibly due to an Overloading attack, and thus curb the attack impact by appropriately revising their schedule

On-demand Key Distribution for Cloud Networks

Emerging fine-grained cloud resource billing creates incentives to review the software execution footprint in virtual environments. Operators can use novel virtual execution environments with ever lower overhead: from virtual machines to containers, to unikernels and serverless functions. However, the execution footprint of security mechanisms in virtualized deployments has either remained the same or even increased. In this demo, we present a novel key provisioning mechanism for cloud networks that unlocks scalable use of symmetric keys and significantly reduces the related computational load on network endpoints

Flowrider: Fast On-Demand Key Provisioning for Cloud Networks

Increasingly fine-grained cloud billing creates incentives to review the software execution footprint in virtual environments. For example, virtual execution environments move towards lower overhead: from virtual machines to containers, unikernels, and serverless cloud computing. However, the execution footprint of security components in virtualized environments has either remained the same or even increased. We present Flowrider, a novel key provisioning mechanism for cloud networks that unlocks scalable use of symmetric keys and significantly reduces the related computational load on network endpoints. We describe the application of Flowrider to common transport security protocols, the results of its formal verification, and its prototype implementation. Our evaluation shows that Florwider uses up to an order of magnitude less CPU to establish a TLS session while preventing by construction some known attacks

Collagen Gene Variants and Anterior Cruciate Ligament Rupture in Italian Athletes: A Preliminary Report

Several studies have investigated the role of genetics in anterior cruciate ligament (ACL) rupture, often returning conflicting results. The present pilot study aimed to analyze the association between six Single Nucleotide Polymorphisms (SNPs) (rs1800012; rs12722; rs13946; rs240736; rs970547; and rs4870723, located on the COL1A1, COL5A1, COL12A1, and COL14A1 genes), and ACL rupture, among Italian athletes. A hypothesis-driven association study was conducted. In total, 181 male and female athletes (n = 86 injured; n = 96 non-injured) were genotyped for the prioritized variants. All polymorphisms were genotyped using PCR RFLP, with the only exception being the rs1800012 on the COL1A1 gene, which was detected using MTPA PCR. The allele frequency distribution fell within the worldwide range. Despite the evident population variability, no selective pressure signals were recorded using PBS analysis. No significant difference was detected between the cases and controls for any of the SNPs (rs1800012; rs13946; rs240736; rs970547, and rs4870723) included in the analyses (p > 0.008, Bonferroni-adjusted for multiple comparisons). Moreover, no significant differences were found when males and females were assessed separately. Further investigations based on a larger sample size are needed, in order to draw solid conclusions for the influence between collagen genes and ACL rupture. © 2023 by the authors

Increasing the agricultural sustainability of closed agrivoltaic systems with the integration of vertical farming: A case study on baby-leaf lettuce

The photovoltaic (PV) greenhouses are closed agrivoltaic (CA) systems that allow the production of energy and food on the same land, but may result in a yield reduction when the shading of the PV panels is excessive. Adopting innovative cropping systems can increase the yield of the CA area, generating a more productive and sustainable agrosystem. In this case study we quantified the increase of land productivity derived from the integration of an experimental vertical farm (VF) for baby leaf lettuce inside a pre-existing commercial CA. The mixed system increased the yield by 13 times compared to the CA and the average LER was 1.31, but only 12 % of the energy consumption was covered by the CA energy. To achieve the energy self-sufficiency and avoid the related CO2 emissions, the VF area should not exceed 7–18 % of the CA area, depending on the PV energy yield and the daily light integral (DLI) of the LED lighting, meaning a land consumption from 5 to 14 times higher than the VF area. The support of the PV energy was essential for the profitability of the VFCA. Design features and solutions were proposed to increase the agronomic and economic sustainability of the VFCA. The VFs can be considered a possible answer for the reconversion of the actual underutilized CAs with high PV cover ratios into productive and efficient cropping systems, but a trade-off between energy production and land consumption should be identified to ensure an acceptable environmental sustainability of the mixed system

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

A cross-ancestry genome-wide association meta-analysis of amyotrophic lateral sclerosis (ALS) including 29,612 patients with ALS and 122,656 controls identifies 15 risk loci with distinct genetic architectures and neuron-specific biology. Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons

Analysis of shared common genetic risk between amyotrophic lateral sclerosis and epilepsy

Because hyper-excitability has been shown to be a shared pathophysiological mechanism, we used the latest and largest genome-wide studies in amyotrophic lateral sclerosis (n = 36,052) and epilepsy (n = 38,349) to determine genetic overlap between these conditions. First, we showed no significant genetic correlation, also when binned on minor allele frequency. Second, we confirmed the absence of polygenic overlap using genomic risk score analysis. Finally, we did not identify pleiotropic variants in meta-analyses of the 2 diseases. Our findings indicate that amyotrophic lateral sclerosis and epilepsy do not share common genetic risk, showing that hyper-excitability in both disorders has distinct origins