Bayesian Network Trust Model for Certificate Revocation in Adhoc Wireless Networks

An Ad hoc wireless network has no infrastructure. It is formed dynamically by a group of moving nodes. There is no backbone or central point of communication. The media of communication is a shared wireless channel; hence extruders can easily penetrate through such a network. A distributed trust model is therefore employed to authenticate the nodes communicating in the network. Whenever a node observes a malicious activity, it floods an accusation in the network which is recorded in a certificate revocation list maintained in the local environment of each node in the network. The certificates for the nodes in the network are renewed if there is no entry against the node in the list. Hence, malicious nodes are removed from the network. However, this scheme has several drawbacks, the most important one being the removal of innocent nodes due to wrong accusations. This work proposes a Bayesian network trust model for certificate revocation. This will establish trust relations among the nodes to overcome the problems faced by the distributed trust model. The ad hoc network is modeled using the Random waypoint mobility model. The two trust models are analyzed and the performance is compared. The proposed trust model outperformed the distributed trust model in identifying and removing the malicious nodes as well as protecting the innocent nodes form malicious accusations against them. Furthermore, in the proposed approach, the performance was high in terms of availability and quality of service. All these were achieved due to proper trust relations among the nodes in the network. Malicious attacks including Hijacking, DoS, spoofing and Time delay were simulated. The proposed model performed much better than the distributed trust model in revoking the certificates of malicious nodes and hence removing them from the network. The trust relationships lead to better security and performance in the network.Computer Science Departmen

Trust model for certificate revocation in Ad hoc networks

In this paper we propose a distributed trust model for certificate revocation in Adhoc networks. The proposed model allows trust to be built over time as the number of interactions between nodes increase. Furthermore, trust in a node is defined not only in terms of its potential for maliciousness, but also in terms of the quality of the service it provides. Trust in nodes where there is little or no history of interactions is determined by recommendations from other nodes. If the nodes in the network are selfish, trust is obtained by an exchange of portfolios. Bayesian networks form the underlying basis for this model

Geoeconomic variations in epidemiology, ventilation management, and outcomes in invasively ventilated intensive care unit patients without acute respiratory distress syndrome: a pooled analysis of four observational studies

Background: Geoeconomic variations in epidemiology, the practice of ventilation, and outcome in invasively ventilated intensive care unit (ICU) patients without acute respiratory distress syndrome (ARDS) remain unexplored. In this analysis we aim to address these gaps using individual patient data of four large observational studies. Methods: In this pooled analysis we harmonised individual patient data from the ERICC, LUNG SAFE, PRoVENT, and PRoVENT-iMiC prospective observational studies, which were conducted from June, 2011, to December, 2018, in 534 ICUs in 54 countries. We used the 2016 World Bank classification to define two geoeconomic regions: middle-income countries (MICs) and high-income countries (HICs). ARDS was defined according to the Berlin criteria. Descriptive statistics were used to compare patients in MICs versus HICs. The primary outcome was the use of low tidal volume ventilation (LTVV) for the first 3 days of mechanical ventilation. Secondary outcomes were key ventilation parameters (tidal volume size, positive end-expiratory pressure, fraction of inspired oxygen, peak pressure, plateau pressure, driving pressure, and respiratory rate), patient characteristics, the risk for and actual development of acute respiratory distress syndrome after the first day of ventilation, duration of ventilation, ICU length of stay, and ICU mortality. Findings: Of the 7608 patients included in the original studies, this analysis included 3852 patients without ARDS, of whom 2345 were from MICs and 1507 were from HICs. Patients in MICs were younger, shorter and with a slightly lower body-mass index, more often had diabetes and active cancer, but less often chronic obstructive pulmonary disease and heart failure than patients from HICs. Sequential organ failure assessment scores were similar in MICs and HICs. Use of LTVV in MICs and HICs was comparable (42·4% vs 44·2%; absolute difference -1·69 [-9·58 to 6·11] p=0·67; data available in 3174 [82%] of 3852 patients). The median applied positive end expiratory pressure was lower in MICs than in HICs (5 [IQR 5-8] vs 6 [5-8] cm H2O; p=0·0011). ICU mortality was higher in MICs than in HICs (30·5% vs 19·9%; p=0·0004; adjusted effect 16·41% [95% CI 9·52-23·52]; p<0·0001) and was inversely associated with gross domestic product (adjusted odds ratio for a US$10 000 increase per capita 0·80 [95% CI 0·75-0·86]; p<0·0001). Interpretation: Despite similar disease severity and ventilation management, ICU mortality in patients without ARDS is higher in MICs than in HICs, with a strong association with country-level economic status