Detection and isolation of black hole attack in mobile ad hoc networks: A review

© 2020 SPIE. Mobile Ad hoc Network or MANET is a wireless network that allows communication between the nodes that are in range of each other and are self-configuring. The distributed administration and dynamic nature of MANET makes it vulnerable to many kind of security attacks. One such attack is Black hole attack which is a well known security threat. A node drops all packets which it should forward, by claiming that it has the shortest path to the destination. Intrusion Detection system identifies the unauthorized users in the system. An IDS collects and analyses audit data to detect unauthorized users of computer systems. This paper aims in identifying Black-Hole attack against AODV with Intrusion Detection System, to analyze the attack and find its countermeasure

Dielectric relaxation dynamics of high-temperature piezoelectric polyimide copolymers

Polyimide co-polymers have been prepared based on different diamines as co-monomers: a diamine without CN groups and a novel synthesized diamine with two CN groups prepared by polycondensation reaction followed by thermal cyclodehydration. Dielectric spectroscopy measurements were performed and the dielectric complex function, ac conductivity and electric modulus of the co-polymers were investigated as a function of CN group content in the frequency range from 0.1 Hz to 107 Hz at temperatures from 25 to 260 °C. For all samples and temperatures above 150ºC, the dielectric constant increases with increasing temperature due to increaseing conductivity. The α-relaxation is just detected for the sample without CN groups, being this relaxation overlapped by the electrical conductivity contributions in the remaining samples. For the copolymer samples and the polymer with CN groups an important Maxwell-Wagner-Sillars contribution is detected. The mechanisms responsible for the dielectric relaxation, conduction process and electric modulus response have been discussed as a function of the CN groups content present in the samples.This work was supported by FEDER through the COMPETE Program and by the Portuguese Foundation for Science and Technology (FCT) in the framework of the Strategic Project PESTC/FIS/UI607/2011 and grants SFRH/BD/ 62507/2009 (A.C.L.) SFRH/BD/68499/2010 (C.M.C.). The authors also thank funding from “Matepro – Optimizing Materials and Processes”, ref. NORTE-07-0124-FEDER-000037”, co-funded by the “Programa Operacional Regional do Norte” (ON.2 – O Novo Norte), under the “Quadro de Referência Estratégico Nacional” (QREN), through the “Fundo Europeu de Desenvolvimento Regional” (FEDER). RSS acknowledge the support of the Spanish Ministry of Economy and Competitiveness through the project MAT2012-38359-C03-01 (including the FEDER financial support). Authors also thank the Basque Country Government for financial support (ACTIMAT project, ETORTEK Program, IE13-380, and Ayudas para Grupos de Investigación del Sistema Universitario Vasco Program, IT718-13)

Securing e-health records using keyless signature infrastructure blockchain technology in the cloud

© 2018, Springer-Verlag London Ltd., part of Springer Nature. Health record maintenance and sharing are one of the essential tasks in the healthcare system. In this system, loss of confidentiality leads to a passive impact on the security of health record whereas loss of integrity leads can have a serious impact such as loss of a patient’s life. Therefore, it is of prime importance to secure electronic health records. Health records are represented by Fast Healthcare Interoperability Resources standards and managed by Health Level Seven International Healthcare Standards Organization. Centralized storage of health data is attractive to cyber-attacks and constant viewing of patient records is challenging. Therefore, it is necessary to design a system using the cloud that helps to ensure authentication and that also provides integrity to health records. The keyless signature infrastructure used in the proposed system for ensuring the secrecy of digital signatures also ensures aspects of authentication. Furthermore, data integrity is managed by the proposed blockchain technology. The performance of the proposed framework is evaluated by comparing the parameters like average time, size, and cost of data storage and retrieval of the blockchain technology with conventional data storage techniques. The results show that the response time of the proposed system with the blockchain technology is almost 50% shorter than the conventional techniques. Also they express the cost of storage is about 20% less for the system with blockchain in comparison with the existing techniques

Ensemble Classification and IoT-Based Pattern Recognition for Crop Disease Monitoring System

Internet of Things (IoT) in the agriculture field provides crops-oriented data sharing and automatic farming solutions under single network coverage. The components of IoT collect the observable data from different plants at different points. The data gathered through IoT components, such as sensors and cameras, can be used to be manipulated for a better farming-oriented decision-making process. This work proposes a system that observes the crops' growth and leaf diseases continuously for advising farmers in need. To provide analytical statistics on plant growth and disease patterns, the proposed framework uses machine learning (ML) techniques, such as support vector machine (SVM) and convolutional neural network (CNN). This framework produces efficient crop condition notifications to terminal IoT components which are assisting in irrigation, nutrition planning, and environmental compliance related to the farming lands. In this regard, this work proposes ensemble classification and pattern recognition for crop monitoring system (ECPRC) to identify plant diseases at the early stages. The proposed ECPRC uses ensemble nonlinear SVM (ENSVM) for detecting leaf and crop diseases. In addition, this work performs comparative analysis between various ML techniques, such as SVM, CNN, naïve Bayes, and K -nearest neighbors. In this experimental section, the results show that the proposed ECPRC system works optimally compared to the other systems

<em>Bacillus </em>spp. for suppression of eggplant bacterial wilt pathogen in Andaman Islands: Isolation and characterization

131-137Bacillus spp. isolated from different soils of Andaman Islands was characterized for antimicrobial potential by different methods. Among 65 strains tested, six Bacillus strains showed best in vitro antagonistic potential against solanaceous bacterial wilt pathogen Ralstonia solanacearum. The identity of the Bacillus strains were confirmed using 16S rRNA gene sequencing and biolog based phenotypic fingerprinting. The functional analysis revealed that most of the strains were positive for the production of IAA, siderophore and phosphate solubilization. In glass house and field studies, Bacillus amyloliquifaceans strain (Bs_Abi) showed significant biocontrol efficacy (92.1 and 73.7%, respectively) against brinjal bacterial wilt disease. The antimicrobial potential of Bs_Abi were further ascertained by presence of nine antimicrobial peptide (AMP) gene biosynthesis in PCR amplifications which confirmed the presence of peptide genes for six antibiotics (iturin, bacillomycin D, mycosubtilin, surfactin, bacilysin and subtilin). Our study revealed that the utilization of such antagonistic Bacillus spp. with multi antimicrobial peptide genes and more functional traits from tropical/ extreme soils would play a vital role in management of eggplant bacterial wilt disease and in formulation of new bioinoculants for improving the cropping system in Andaman and Nicobar Islands