Information fusion-based cybersecurity threat detection for intelligent transportation system

Intelligent Transportation Systems (ITS) are sophisticated systems that leverage various technologies to increase the safety, efficiency, and sustainability of transportation. By relying on wireless communication and data collected from diverse sensors, ITS is vulnerable to cybersecurity threats. With the increasing number of attacks on ITS worldwide, detecting and addressing cybersecurity threats has become critically important. This need will only intensify with the impending arrival of autonomous vehicles. One of the primary challenges is identifying critical ITS assets that require protection and understanding the vulnerabilities that cyber attackers can exploit. Additionally, creating a standard profile for ITS is challenging due to the dynamic traffic pattern, which exhibits changes in the movement of vehicles over time. To address these challenges, this paper proposes an information fusion-based cybersecurity threat detection method. Specifically, we employ the Kalman filter for noise reduction, Dempster-Shafer decision theory and Shannon’s entropy for assessing the probabilities of traffic conditions being normal, intruded, and uncertain. We utilised Simulation of Urban Mobility (SUMO) to simulate the Melbourne CBD map and historical traffic data from the Victorian transport authority. Our simulation results reveal that information fusion with three sensor data is more effective in detecting normal traffic conditions. On the other hand, for detecting anomalies, information fusion with two sensor data is more efficient

IoT-based emergency vehicle services in intelligent transportation system

Emergency Management System (EMS) is an important component of Intelligent transportation systems, and its primary objective is to send Emergency Vehicles (EVs) to the location of a reported incident. However, the increasing traffic in urban areas, especially during peak hours, results in the delayed arrival of EVs in many cases, which ultimately leads to higher fatality rates, increased property damage, and higher road congestion. Existing literature addressed this issue by giving higher priority to EVs while traveling to an incident place by changing traffic signals (e.g., making the signals green) on their travel path. A few works have also attempted to find the best route for an EV using traffic information (e.g., number of vehicles, flow rate, and clearance time) at the beginning of the journey. However, these works did not consider congestion or disruption faced by other non-emergency vehicles adjacent to the EV travel path. The selected travel paths are also static and do not consider changing traffic parameters while EVs are en route. To address these issues, this article proposes an Unmanned Aerial Vehicle (UAV) guided priority-based incident management system to assist EVs in obtaining a better clearance time in intersections and thus achieve a lower response time. The proposed model also considers disruption faced by other surrounding non-emergency vehicles adjacent to the EVs’ travel path and selects an optimal solution by controlling the traffic signal phase time to ensure that EVs can reach the incident place on time while causing minimal disruption to other on-road vehicles. Simulation results indicate that the proposed model achieves an 8% lower response time for EVs while the clearance time surrounding the incident place is improved by 12%

Performance and cryptographic evaluation of security protocols in distributed networks using applied pi calculus and Markov Chain

The development of cryptographic protocols goes through two stages, namely, security verification and performance analysis. The verification of the protocol’s security properties could be analytically achieved using threat modelling, or formally using formal methods and model checkers. The performance analysis could be mathematical or simulation-based. However, mathematical modelling is complicated and does not reflect the actual deployment environment of the protocol in the current state of the art. Simulation software provides scalability and can simulate complicated scenarios, however, there are times when it is not possible to use simulations due to a lack of support for new technologies or simulation scenarios. Therefore, this paper proposes a formal method and analytical model for evaluating the performance of security protocols using applied pi-calculus and Markov Chain processes. It interprets algebraic processes and associates cryptographic operatives with quantitative measures to estimate and evaluate cryptographic costs. With this approach, the protocols are presented as processes using applied pi-calculus, and their security properties are an approximate abstraction of protocol equivalence based on the verification from ProVerif and evaluated using analytical and simulation models for quantitative measures. The interpretation of the quantities is associated with process transitions, rates, and measures as a cost of using cryptographic primitives. This method supports users’ input in analysing the protocol’s activities and performance. As a proof of concept, we deploy this approach to assess the performance of security protocols designed to protect large-scale, 5G-based Device-to-Device communications. We also conducted a performance evaluation of the protocols based on analytical and network simulator results to compare the effectiveness of the proposed approach

Precision Targeting of Bacterial Pathogen Via Bi-Functional Nanozyme Activated by Biofilm Microenvironment

Human dental caries is an intractable biofilm-associated disease caused by microbial interactions and dietary sugars on the host\u27s teeth. Commensal bacteria help control opportunistic pathogens via bioactive products such as hydrogen peroxide (H2O2). However, high-sugar consumption disrupts homeostasis and promotes pathogen accumulation in acidic biofilms that cause tooth-decay. Here, we exploit the pathological (sugar-rich/acidic) conditions using a nanohybrid system to increase intrinsic H2O2 production and trigger pH-dependent reactive oxygen species (ROS) generation for efficient biofilm virulence targeting. The nanohybrid contains glucose-oxidase that catalyzes glucose present in biofilms to increase intrinsic H2O2, which is converted by iron oxide nanoparticles with peroxidase-like activity into ROS in acidic pH. Notably, it selectively kills Streptococcus mutans (pathogen) without affecting Streptococcus oralis (commensal) via preferential pathogen-binding and in situ ROS generation. Furthermore, nanohybrid treatments potently reduced dental caries in a rodent model. Compared to chlorhexidine (positive-control), which disrupted oral microbiota diversity, the nanohybrid had significant higher efficacy without affecting soft-tissues and the oral-gastrointestinal microbiomes, while modulating dental health-associated microbial activity in vivo. The data reveal therapeutic precision of a bi-functional hybrid nanozyme against a biofilm-related disease in a controlled-manner activated by pathological conditions. © 2020 The Author

OXA-181-like carbapenemases in Klebsiella pneumoniae ST14, ST15, ST23, ST48, and ST231 from septicemic neonates: coexistence with NDM-5, resistome, transmissibility, and genome diversity

Studies on the epidemiology and genomes of isolates harboring OXA-48-like genes in septicemic neonates are rare. Here, isolates producing these carbapenemases which emerged and persisted in an Indian neonatal unit were characterized in terms of their resistome, transmissibility, and genome diversity. Antibiotic susceptibility and whole-genome sequencing were carried out. The sequence types, resistome, virulome, mobile genetic elements, and transmissibility of carbapenem-resistant plasmids were evaluated. Core genome analysis of isolates was shown in a global context with other OXA-48-like carbapenemase-harboring genomes, including those from neonatal studies. Eleven OXA-48-like carbapenemase-producing Klebsiella pneumoniae (blaOXA-181, n = 7 and blaOXA-232, n = 4) isolates belonging to diverse sequence types (ST14, ST15, ST23, ST48, and ST231) were identified. blaOXA-181/OXA-232 and blaNDM-5 were found in a high-risk clone, ST14 (n = 4). blaOXA-181/OXA-232 were in small, nonconjugative ColKP3 plasmids located on truncated Tn2013, whereas blaNDM-5 was in self-transmissible, conjugative IncFII plasmids, within truncated Tn125. Conjugal transfer of blaOXA-181/OXA-232 was observed in the presence of blaNDM-5. The study strains were diverse among themselves and showed various levels of relatedness with non-neonatal strains from different parts of the world and similarity with neonatal strains from Tanzania and Ghana when compared with a representative collection of carbapenemase-positive K. pneumoniae strains. We found that blaOXA-181/OXA-232-harboring isolates from a single neonatal unit had remarkably diverse genomes, ruling out clonal spread and emphasizing the extent of plasmid spreading across different STs. This study is probably the first to report the coexistence of blaOXA-181/232 and blaNDM-5 in neonatal isolates

Topical Ferumoxytol Nanoparticles Disrupt Biofilms and Prevent Tooth Decay in Vivo Via Intrinsic Catalytic Activity

Ferumoxytol is a nanoparticle formulation approved by the U.S. Food and Drug Administration for systemic use to treat iron deficiency. Here, we show that, in addition, ferumoxytol disrupts intractable oral biofilms and prevents tooth decay (dental caries) via intrinsic peroxidase-like activity. Ferumoxytol binds within the biofilm ultrastructure and generates free radicals from hydrogen peroxide (H2O2), causing in situ bacterial death via cell membrane disruption and extracellular polymeric substances matrix degradation. In combination with low concentrations of H2O2, ferumoxytol inhibits biofilm accumulation on natural teeth in a human-derived ex vivo biofilm model, and prevents acid damage of the mineralized tissue. Topical oral treatment with ferumoxytol and H2O2 suppresses the development of dental caries in vivo, preventing the onset of severe tooth decay (cavities) in a rodent model of the disease. Microbiome and histological analyses show no adverse effects on oral microbiota diversity, and gingival and mucosal tissues. Our results reveal a new biomedical application for ferumoxytol as topical treatment of a prevalent and costly biofilm-induced oral disease

The nature of the basement in the Archaean Dharwar craton of southern India and the age of the Peninsular Gneiss

The Archaean Peninsular Gneiss of southern India is considered by a number of workers to be the basement upon which the Dharwar supracrustal rocks were deposited. However, the Peninsular Gneiss in its present state is a composite gneiss formed by synkinematic migmatization during successive episodes of folding (DhF1, DhF1a and DhF2) that affected the Dharwar supracrustal rocks. An even earlier phase of migmatization and deformation (DhF∗ ) is evident from relict fabrics in small enclaves of gneissic tonalites and amphibolites within the Peninsular Gneiss. We consider these enclaves to represent the original basement for the Dharwar supracrustal rocks. Tonalitic pebbles in conglomerates of the Dharwar Supergroup confirm the inference that the supracrustal rocks were deposited on a gneissic basement. Whole rock Rb-Sr ages of gneisses showing only the DhF1 structures fall in the range of 3100-3200 Ma. Where the later deformation (DhF2) has been associated with considerable recrystallization, the Rb-Sr ages are between 2500 Ma and 2700 Ma. Significantly, a new Rb-Sr analysis of tonalitic gneiss pebbles in the Kaldurga conglomerate of the Dharwar sequence is consistent with an age of ~2500 Ma and not that of 3300 Ma reported earlier by Venkatasubramanian and Narayanaswamy (1974). Pb-Pb ages based on direct evaporation of detrital zircon grains from the metasedimentary rocks of the Dharwar sequence fall into two groups, 3300-3100 Ma, and 2800-3000 Ma. Stratigraphic, structural, textural and geochronologic data, therefore, indicate that the Peninsular Gneiss of the Dharwar craton evolved over a protracted period of time ranging from > 3300 Ma to 2500 Ma