An Analysis Approach for Context-Aware Energy Feedback Systems

Several energy systems have been developed and studied to help occupants reduce energy usage by providing feedback about their consumption. But recently, a major challenge has emerged about how to enable users to make informed energy efficiency decisions based on consumption feedback. This is because existing systems only present abstract consumption data that are not related to the surrounding energy consumption context. This paper proposes a novel energy data analysis approach which leverages context-awareness to support users to take actions that improve energy efficiency. The approach consists of two stages: multidimensional analysis followed by case-based reasoning. The anticipated output of the analysis approach will be understandable and actionable feedback that helps occupants control their energy consumption

Defining Context for Home Electricity Feedback Systems

Existing electricity feedback systems provide home occupants with real-time consumption data to enable them to control their consumption. However, these systems provide abstract consumption data that is not related to the occupants surrounding. Although there are some attempts to enrich consumption data with some context information, the presented feedback is not enough to inform decisions of how to conserve electricity. Therefore, this paper provides a rich definition of electricity consumption context, which can be used to provide sensible feedback to users. The obtained context elements can be categorized into three context types: User Context, Appliances Context, and Environment Context. Finally, different implications for the application of a context-aware feedback system are presented showing how the obtained context definition could be used to provide understandable feedback

Detection and prediction of insider threats to cyber security: a systematic literature review and meta-analysis

Cyber security is vital to the success of today’s digital economy. The major security threats are coming from within, as opposed to outside forces. Insider threat detection and prediction are important mitigation techniques. This study addresses the following research questions: 1) what are the research trends in insider threat detection and prediction nowadays? 2) What are the challenges associated with insider threat detection and prediction? 3) What are the best-to-date insider threat detection and prediction algorithms? We conduct a systematic review of 37 articles published in peer-reviewed journals, conference proceedings and edited books for the period of 1950–2015 to address the first two questions. Our survey suggests that game theoretic approach (GTA) is a popular source of insider threat data; the insiders’ online activities are the most widely used features in insider threat detection and prediction; most of the papers use single point estimates of threat likelihood; and graph algorithms are the most widely used tools for detecting and predicting insider threats. The key challenges facing the insider threat detection and prediction system include unbounded patterns, uneven time lags between activities, data nonstationarity, individuality, collusion attacks, high false alarm rates, class imbalance problem, undetected insider attacks, uncertainty, and the large number of free parameters in the model. To identify the best-to-date insider threat detection and prediction algorithms, our meta-analysis study excludes theoretical papers proposing conceptual algorithms from the 37 selected papers resulting in the selection of 13 papers. We rank the insider threat detection and prediction algorithms presented in the 13 selected papers based on the theoretical merits and the transparency of information. To determine the significance of rank sums, we perform “the Friedman two-way analysis of variance by ranks” test and “multiple comparisons between groups or conditions” tests

PHYTOCHEMICAL STUDY OF BIOACTIVE CONSTITUENTS FROM SATUREJA MONTANA L. GROWING IN EGYPT AND THEIR ANTIMICROBIAL AND ANTIOXIDANT ACTIVITIES

 Objective: This work aimed to investigate the lipid constituents and flavonoidal compounds of Satureja montana, in addition to evaluation of different extracts and/or isolated compounds as antimicrobials and antioxidants.Methods: The volatile and lipid constituents were extracted with n-hexane by partition from hydroalcoholic extract of S. montana L. aerial parts, after then were fractionated to unsaponifiable matters and fatty acid methyl esters which were identified by gas–liquid chromatography and/or gas chromatography–mass spectrometry. The phenolic constituents were isolated from the ethyl acetate fraction of the aqueous methanolic extract of the aerial parts of the plant. The antimicrobial activity of different extracts and the isolated compounds was evaluated against Gram-positive, Gram-negative bacteria, yeast, and fungus using a modified Kirby-Bauer disc diffusion method.Results: The identified compounds are luteolin-7-rhamnoside-4'-O-β-glucopyranoside (1), quercetin-3-O-α-L-rhamnopyranoside (2), quercetin- 7-O-glucopyranoside (3), luteolin-7-O-glucopyranoside (4), 5-hydroxy-6,7,8,4'-tetramethoxy flavone (5), gallic acid (6), 2,3-hexahydroxydiphenoyl 1-galloyl glucopyranoside (7), and quercetin (8). The structure of all isolated compounds was established using different chromatographic and spectroscopic measurements (PC, thin-layer chromatography, ultraviolet [UV], 1D, 2D-nuclear magnetic resonance, and MS). Compound-2 showed the highest antibacterial activity against all the tested microorganisms. Hydroalcoholic extract exhibited high antioxidant activity (87.7%). On the other hand, hexane fraction showed a low antioxidant activity (46.4%), in addition to the compound-8 showed the highest antioxidant activity (96.27%) in 2,2-diphenyl-1-picrylhydrazyl assay.Conclusion: It can be concluded that the hydroalcoholic extract of S. montana showed significant antimicrobial and antioxidant activity

Growth performance of two lemon [Citrus limon (L.) Osbeck] cultivars budded on three rootstocks, Gezira State, Sudan

     Lemon [Citrus limon (L.) Osbeck ], family Rutaceae, is one of the world's major fruit crops with global popularity contributing to human diets. Lemon rootstocks and scion cultivars play an important role in the rapid development of citrus in the world. This study was conducted to evaluate the growth performance of two lemon cultivars budded on three rootstocks under Gezira State conditions, Sudan. The experiment was conducted in the nursery of the Department of Horticultural Sciences, Faculty of Agricultural Sciences, University of Gezira, Wad Medani, Sudan, in 2017.Volcamariana, Rough Lemon and Macrophylla rootstocks were grafted with buds of Eureka and Teresa cultivars. The T- budding technique was used in this study. Treatments were arranged in a randomized complete block design with three replicates. Parameters measured were rootstock height and thickness, height of scion, number of branches, length of branches and stem circumference of the scion. The parameters were recorded for 10 months.  Rootstocks were significantly different in their vegetative growth.  Rough Lemon rootstock resulted in the best vegetative growth.  However, there were no significant differences in growth parameters between Volkameriana and Macrophylla rootstocks. Lemon cultivars were highly significantly different in their vegetative performance. Teresa lemon cultivar resulted in the largest plant height (73.9 cm), number of branches (27), length of branches (68 cm) and stem circumference (11.8 cm). The interaction effects of rootstocks and cultivars on vegetative performance of lemon were significant. The largest plant height (84.33 cm), number of branches (31.7), length of branches (75.7 cm) and stem circumference (12.3 cm) were obtained by Teresa cultivar budded on Rough Lemon rootstock and the smallest parameters were obtained by Eureka cultivar budded on Volkameriana, whereas the smallest length of branches (55.3) and stem circumference (9.5 cm) were obtained by Eureka cultivar budded on Macrophylla. Depending on the results of this study, it is recommended to bud the lemon cultivar Teresa on Rough Lemon rootstock under Gezira State Conditions, to obtain the best growth performance

A Trust Management Framework for Network Applications within an SDN Environment

Software Defined Networking (SDN) is an emerging paradigm that changes the way networks are managed by separating the control plane from data plane and making networks programmable. The separation brings about flexibility, automation, orchestration and offers savings in both capital and operational expenditure. Despite all the advantages offered by SDN it introduces new threats that did not exist before or were harder to exploit in traditional networks, making network penetration potentially easier. One of the key threat to SDN is the authentication and authorisation of network applications that control network behaviour (unlike the traditional network where network devices like routers and switches are autonomous and run proprietary software and protocols to control the network). This paper proposes a mechanism that helps the control layer authenticate network applications and set authorisation permissions that constrict manipulation of network resources

Performance Implication and Analysis of the OpenFlow SDN Protocol

Software Defined Networks provide the ability to manage networks from a centralised point through separating control plane from the data plane. This brings opportunities in terms of manageability, flexibility and cost savings in network operations. This centralisation, however, also brings about a potentially serious performance bottleneck and poses a scalability issue in high performance networks. This paper investigates performance of Software Defined Networks in general, and the OpenFlow protocol, to provide insight into the components of control path delay incurred by packets and ways to optimise flow forwarding. Two Openflow controllers (Floodlight and Pox) were used to validate performance measurements in relation to their theoretical composition. Secondly, the packet processing dynamics of switches, in particular OpenVSwitch are examined, looking at the control packet forwarding behaviour in the kernel module to meet high performance network and traffic engineering demand

Securing Microservices

Microservices has drawn significant interest in recent years and is now successfully finding its way into different areas, from Enterprise IT to Internet-of-Things to even Critical Applications. This article discusses how Microservices can be secured at different levels and stages considering a common software development lifecycle

Experimental demonstration of 72% reach enhancement of 3.6Tbps optical transmission system using mid-link Optical Phase Conjugation

We experimentally demonstrate nonlinear noise compensation in optical phase conjugation assisted 1st order Raman amplified 30x30Gbaud DP-QPSK transmission system with a spectral efficiency of 3.6b/s/Hz. We show that by optimizing the link symmetry, even with only 1st order Raman amplification a single, mid-link, optical phase conjugation compensates for 90% off the signal-signal nonlinear interference resulting in a 2.3dB performance enhancement. We show that increasing the number of optical phase conjugation s in the presence of 10% residual nonlinearity results in a reduction in the performance enhancement owing to an enhancement in the nonlinear noise generation efficiency of the system. We achieve a record 72% optical phase conjugation enabled reach enhancement of the 30x30Gbaud DP-QPSK signals

A Novel Trust Taxonomy for Shared Cyber Threat Intelligence

Cyber threat intelligence sharing has become a focal point for many organizations to improve resilience against cyber attacks. The objective lies on sharing relevant information achieved through automating as many processes as possible without losing control or compromising security. The intelligence may be crowdsourced from decentralized stakeholders to collect and enrich existing information. Trust is an attribute of actionable cyber threat intelligence that has to be established between stakeholders. Sharing information about vulnerabilities requires a high level of trust because of the sensitive information. Some threat intelligence platforms/providers support trust establishment through internal vetting processes, others rely on stakeholders to manually build up trust. The latter may reduce the amount of intelligence sources. This work presents a novel trust taxonomy to establish a trusted threat sharing environment. 30 popular threat intelligence platforms/providers were analyzed and compared regarding trust functionalities. Trust taxonomies were analyzed and compared. Illustrative case studies were developed and analyzed applying our trust taxonomy