A Distributed Consensus Algorithm for Decision Making in Service-Oriented Internet of Things

In a service-oriented Internet of things (IoT) deployment, it is difficult to make consensus decisions for services at different IoT edge nodes where available information might be insufficient or overloaded. Existing statistical methods attempt to resolve the inconsistency, which requires adequate information to make decisions. Distributed consensus decision making (CDM) methods can provide an efficient and reliable means of synthesizing information by using a wider range of information than existing statistical methods. In this paper, we first discuss service composition for the IoT by minimizing the multi-parameter dependent matching value. Subsequently, a cluster-based distributed algorithm is proposed, whereby consensuses are first calculated locally and subsequently combined in an iterative fashion to reach global consensus. The distributed consensus method improves the robustness and trustiness of the decision process

A novel heuristic algorithm for the modeling and risk assessment of the covid-19 pandemic phenomenon

The modeling and risk assessment of a pandemic phenomenon such as COVID-19 is an important and complicated issue in epidemiology, and such an attempt is of great interest for public health decision-making. To this end, in the present study, based on a recent heuristic algorithm proposed by the authors, the time evolution of COVID-19 is investigated for six different countries/states, namely New York, California, USA, Iran, Sweden and UK. The number of COVID-19-related deaths is used to develop the proposed heuristic model as it is believed that the predicted number of daily deaths in each country/state includes information about the quality of the health system in each area, the age distribution of population, geographical and environmental factors as well as other conditions. Based on derived predicted epidemic curves, a new 3D-epidemic surface is proposed to assess the epidemic phenomenon at any time of its evolution. This research highlights the potential of the proposed model as a tool which can assist in the risk assessment of the COVID-19. Mapping its development through 3D-epidemic surface can assist in revealing its dynamic nature as well as differences and similarities among different districts

Design and performance evaluation of a lightweight wireless early warning intrusion detection prototype

The proliferation of wireless networks has been remarkable during the last decade. The license-free nature of the ISM band along with the rapid proliferation of the Wi-Fi-enabled devices, especially the smart phones, has substantially increased the demand for broadband wireless access. However, due to their open nature, wireless networks are susceptible to a number of attacks. In this work, we present anomaly-based intrusion detection algorithms for the detection of three types of attacks: (i) attacks performed on the same channel legitimate clients use for communication, (ii) attacks on neighbouring channels, and (iii) severe attacks that completely block network's operation. Our detection algorithms are based on the cumulative sum change-point technique and they execute on a real lightweight prototype based on a limited resource mini-ITX node. The performance evaluation shows that even with limited hardware resources, the prototype can detect attacks with high detection rates and a few false alarms. © 2012 Fragkiadakis et al

New insights into perinatal testicular torsion

Perinatal testicular torsion is a relatively rare event that remains unrecognized in many patients or is suspected and treated accordingly only after an avoidable loss of time. The authors report their own experience with several patients, some of them quite atypical but instructive. Missed bilateral torsion is an issue, as are partial torsion, possible antenatal signs, and late presentation. These data are discussed together with the existing literature and may help shed new light on the natural course of testicular torsion and its treatment. The most important conclusion is that a much higher index of suspicion based on clinical findings is needed for timely detection of perinatal torsion. It is the authors’ opinion that immediate surgery is mandatory not only in suspected bilateral torsions but also in cases of possible unilateral torsions. There is no place for a more fatalistic “wait-and-see” approach. Whenever possible, even necrotic testes should not be removed during surgery because some endocrine function may be retained

Lightweight steganalysis based on image reconstruction and lead digit distribution analysis

This paper presents a novel method of JPEG image Steganalysis, driven by the need for a quick and accurate identification of stego-carriers from a collection of files, where there is no knowledge of the steganography algorithm used, nor previous database of suspect carrier files created. The suspicious image is analyzed in order to identify the encoding algorithm while various meta-data is retrieved. An image file is then reconstructed in order to be used as a measure of comparison. A generalization of the basic principles of Benford's Law distribution is applied on both the suspicious and the reconstructed image file in order to decide whether the target is a stego-carrier. The authors demonstrate the effectiveness of the technique with a steganalytic tool that can blindly detect the use of JPHide/JPseek/JPHSWin, Camouflage and Invisible Secrets. Experimental results show that the steganalysis scheme is able to efficiently detect the use of different steganography algorithms without the use of a time consuming training step, even if the embedding data rate is very low. The accuracy of the detector is independent of the payload. The method described can be generalized in order to be used for the detection of different type images which act as stego-carriers. Copyright © 2011, IGI Global