ESPR: Efficient Security Scheme for Position-Based Routing in Vehicular Ad Hoc Networks

Vehicular Ad hoc Network (VANET) is a promising emerging technology that enables road safety, traffic management, and passengers and drivers comfort applications. Many applications require multi-hop routing; position-based routing (PBR) is a well-recognized routing paradigm that performs well in the vehicular context to enable these applications. However, there are many security challenges and various routing attacks which may prevent the deployment of PBR protocols. In this study, we propose a novel security scheme called ESPR to secure PBR protocols in VANETs. ESPR considers both digital signature and keyed Hash Message Authentication Code (HMAC) to meet the unique requirements of PBR. In ESPR, all legitimate members share a secret key. ESPR scheme applies a novel probabilistic key distribution to allow unrevoked members to update the shared secret key. Furthermore, it defines a set of plausibility checks that enables network members to detect and avoid PBR attacks autonomously. By conducting security analysis and performance evaluation, ESPR scheme demonstrated to outperform its counterparts in terms of communication overhead and delay while achieving robust and secure operation

Connectivity-Aware Routing in Vehicular Ad Hoc Networks

Vehicular ad hoc networks (VANETs) is a promising emerging technology that enables a wide range of appealing applications in road safety, traffic management, and passengers and driver comfort. The deployment of VANETs to enable vehicular Internet-based services and mobile data offloading is also envisioned to be a promising solution for the great demand of mobile Internet access. However, developing reliable and efficient routing protocols is one of the key challenges in VANETs due to the high vehicle mobility and frequent network topology changes. In this thesis, we highlight the routing challenges in VANETs with a focus on position-based routing (PBR), as a well-recognized routing paradigm in the vehicular environment. As the current PBR protocols do not support VANET users with connectivity information, our goal is to design an efficient routing protocol for VANETs that dynamically finds long life paths, with reduced delivery delay, and supports vehicles with instant information about connectivity to the infrastructure. The focus of this thesis will be on predicting vehicular mobility to estimate inter-vehicle link duration in order to support routing protocols with proactive connectivity information for a better routing performance. Via three stages to meet our goal, we propose three novel routing protocols to estimate both broad and comprehensive connectivities in VANETs: iCAR, iCAR-II, and D-CAR. iCAR supports VANET users with instant broad connectivity information to surrounding road intersections, iCAR-II uses cellular network channels for comprehensive connectivity awareness to Roadside Units (RSUs), and finally D-CAR supports users with instant comprehensive connectivity information without the assistance of other networks. Detailed analysis and simulation based evaluations of our proposed protocols demonstrate the validity of using VANETs for Internet-based services and mobile data offloading in addition to the significant improvement of VANETs performance in terms of packet delivery ratio and end-to-end delay

Dual functionality of ferrocene-based metallopolymers as radical scavengers and nanoparticle stabilizing agents

The beneficial redox properties of ferrocene-based polymers have been utilized during in situ preparation of metallic nanoparticles, while such redox features also indicate great promise in applications as free radical..

Dual functionality of ferrocene-based metallopolymers as radical scavengers and nanoparticle stabilizing agents

The beneficial redox properties of ferrocene-based polymers have been utilized during in situ preparation of metallic nanoparticles, while such redox features also indicate great promise in applications as free radical scavengers. Here, colloidal dispersions of an antioxidant nanozyme composed of amidine-functionalized polystyrene latex nanoparticles (AL), negatively charged poly(ferrocenylsilane) (PFS(-)) organometallic polyions, and ascorbic acid (AA) were formulated. AL was first functionalized with PFS(-). Increasing the polymer dose resulted in charge neutralization and subsequent charge reversal of the particles. The strength of repulsive interparticle forces of electrostatic origin was significant at low and high doses leading to stable colloids, while attractive forces dominated near the charge neutralization point giving rise to unstable dispersions. The saturated PFS(-) layer adsorbed on the surface of AL (p-AL nanozyme) enhanced the colloidal stability against salt-induced aggregation without affecting the pH-dependent charge and size of the particles. The joint effect of PFS(-) and AA in radical decomposition was observed indicating the antioxidant potential of the system. The immobilization of PFS(-) deteriorated its scavenging activity, yet the combination with AA improved this feature. The results indicate that p-AL-AA is a promising radical scavenger since the high colloidal stability of the particles allows application in heterogeneous systems, such as in industrial manufacturing processes, where antioxidants are required to maintain acceptable product quality

Ping flood attack pattern recognition using a K-Means algorithm in an Internet of Things (IoT) network

Security is the main challenge in Internet of Things (IoT) systems. The devices on the IoT networks are very heterogeneous, many of them have limited resources, and they are connected globally, which makes the IoT much more challenging to secure than other types of networks. Denial of service (DoS) is the most popular method used to attack IoT networks, either by flooding services or crashing services. Intrusion detection system (IDS) is one of countermeasures for DoS attack. Unfortunately, the existing IDSs are still suffering from detection accuracy problem due to difficulty of recognizing features of the DoS attacks. Thus, we need to determine specific features that representing well the traffic attacks, so the IDS will be able to distinguish normal traffic from the attacks. In this work, we investigate ping flood attack pattern recognition on IoT networks. Experiments were conducted using wireless communication with three different scenarios: normal traffic, attack traffic, and combined normal-attack traffic. Each scenario created an associated dataset. The datasets were then grouped into two clusters: normal and attack. The K-Means algorithm was used to produce the clustering results. The average number of packets in the attack cluster was 95 931 packets, and the average in the normal cluster was 4,068 packets. The accuracy level of the clustering results was calculated using a confusion matrix. The accuracy of the clustering using the implemented K-Means algorithm was 99.94%. The rates from the confusion matrix were true negative (98.62%), true positive (100.00%), false negative (0.00%), and false positive (1.38%)

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries