High Accuracy Phishing Detection Based on Convolutional Neural Networks

The persistent growth in phishing and the rising volume of phishing websites has led to individuals and organizations worldwide becoming increasingly exposed to various cyber-attacks. Consequently, more effective phishing detection is required for improved cyber defence. Hence, in this paper we present a deep learning-based approach to enable high accuracy detection of phishing sites. The proposed approach utilizes convolutional neural networks (CNN) for high accuracy classification to distinguish genuine sites from phishing sites. We evaluate the models using a dataset obtained from 6,157 genuine and 4,898 phishing websites. Based on the results of extensive experiments, our CNN based models proved to be highly effective in detecting unknown phishing sites. Furthermore, the CNN based approach performed better than traditional machine learning classifiers evaluated on the same dataset, reaching 98.2% phishing detection rate with an F1-score of 0.976. The method presented in this pa-per compares favourably to the state-of-the art in deep learning based phishing website detection

DL-Droid: Deep learning based android malware detection using real devices

open access articleThe Android operating system has been the most popular for smartphones and tablets since 2012. This popularity has led to a rapid raise of Android malware in recent years. The sophistication of Android malware obfuscation and detection avoidance methods have significantly improved, making many traditional malware detection methods obsolete. In this paper, we propose DL-Droid, a deep learning system to detect malicious Android applications through dynamic analysis using stateful input generation. Experiments performed with over 30,000 applications (benign and malware) on real devices are presented. Furthermore, experiments were also conducted to compare the detection performance and code coverage of the stateful input generation method with the commonly used stateless approach using the deep learning system. Our study reveals that DL-Droid can achieve up to 97.8% detection rate (with dynamic features only) and 99.6% detection rate (with dynamic + static features) respectively which outperforms traditional machine learning techniques. Furthermore, the results highlight the significance of enhanced input generation for dynamic analysis as DL-Droid with the state-based input generation is shown to outperform the existing state-of-the-art approaches

Multivariate approach to the study of aquatic species diversity of dendrite streams of River Kano, Nigeria

Diversity of macroinvertebrates as well as Physico-chemical parameters were  investigated in six sampling sites of Kano River between June 2014 to May 2015. The pattern of association between measured Physico-chemical parameters were significantly correlated using Pearson Product Moment Correlation and revealed high positive correlation between Total Nitrate and Total Phosphate at site A (.811) and negative correlation between Dissolved Oxygen and pH at site E (-.261). Eigen value of the three variables namely; Temperature, pH and Electrical Conductivity was satisfactory, explaining 73.64% and 70.79% of the total variance in dry season and wet season respectively, other components explained 26.36% and 29.06% noise. Kaiser-Meyer-Olkin in dry season value showed 0.700 degree of common variance is middling bordering meritorious adequacy value while wet season showed miserable degree of common variance value of 0.500. Bartletts' Test of Sphericity showed no difference in wet and dry season with the significant value of p < 0.001. Macroinvertebrates species group frequency distribution of homogeneous set at N 2271 showed Chironomidae subset-7 with the significance of 1.00 highest in harmonic mean value and Planariidae in subset-1 has 0.59 lowest in the value. Generalized Linear Model further revealed the pattern in seasonal variation in the macroinvertebrates data set. The findings were discussed and recommendations made.Key words: Dendrites, Diversity, Eigen value, Macroinvertebrates, Multivariate, River Kano

Biological Assessment of Water Quality: A Study of Challawa River Water Kano, Nigeria

This study was carried out to survey the biotic community of Challawa river water in Kano, Nigeria, using Biological Monitoring Working Party Score (BMWP) and Average Score Per Taxa (ASPT) assessment tools to evaluate the water quality in the field. Using standardized sampling technique insects, insects’ larvae, benthic invertebrates, fresh water vivalve, prosobranch and Pulmonate Gastropods of the river were collected, indentified using identifications keys and BMWP score table. BMWP performances and ASPT values obtained were recorded for each selected site A, B, C and D during sampling period between February to October. The results revealed that Site A, close to water treatment plant, had a total of 63 species count, the total performance of 53 BMWP score; was (high)10 in March but fell sharply to 2(low) in May and the ASPT value obtained was 0.84 as the less sensitive species dominate the sample size and indicating water of B-class quality. Site B, the water intake Station of the Challawa water works had 37 species count, 44 BMWP performances and 1.19 ASPT value assessed A-class. Site C, industrial effluent discharge point, had 51 counts, 28 BMWP performances with 0.55 ASPT value assessed D-class. Site D, the confluent point between River Challawa and River Kano had 67count, 58 BMWP performances and 0.87 ASPT value assessed B-class. The implications of the findings were discussed and recommendations for possible abatement of the situation made.Key words: Macro invertebrates, quality, assessment, Challawa River, ASPT, BMW

The Role of Information and Communications Technology in Socializing Knowledge Management

The globalization of business, the shift from production-based to a knowledge-based economy, the growth of information communications technology (ICT), the strive to become learning organizations and the emergence of the needs for knowledge workers have made knowledge management practice a must today across all types and levels of firms However, because the concept is so new, there exist different views among practitioners and even researchers on how a knowledge management program can be designed and implemented in organizations. This paper posits that knowledge management can be socialized and works in an organization. It also review the related literature on the knowledge management strategy, including the review of the different definition of the knowledge management, types of the knowledge, processes of acquiring knowledge, and the knowledge management strategy according to various empirical studies conducted by scholars. This paper further reviews the technologies and the technology tools to be used in the development of social networks for KM in an organization. A brief description on knowledge processes and technology enabler, the impact of social networking site and socialized KM in today’s organization, the reason for socializing KM and the component of KM are discuss. The strategy for Km implementation and the two main strategies are discussed. The literature are based on the past studies and researches. Keywords: Knowledge Management, Social Networks, I

Design and Implementation of a Measurement-Based Policy-Driven Resource Management Framework For Converged Networks

This paper presents the design and implementation of a measurement-based QoS and resource management framework, CNQF (Converged Networks QoS Management Framework). CNQF is designed to provide unified, scalable QoS control and resource management through the use of a policy-based network management paradigm. It achieves this via distributed functional entities that are deployed to co-ordinate the resources of the transport network through centralized policy-driven decisions supported by measurement-based control architecture. We present the CNQF architecture, implementation of the prototype and validation of various inbuilt QoS control mechanisms using real traffic flows on a Linux-based experimental test bed.Comment: in Ictact Journal On Communication Technology: Special Issue On Next Generation Wireless Networks And Applications, June 2011, Volume 2, Issue 2, Issn: 2229-6948(Online

Effects of density and hunger on the spatial distribution and pit construction behaviour of the antlion larvae (Myrmeleon spp.)

The antlion larvae are sessile predaceous larvae, which depend on active prey for their food. They dig conical pit in loose fine sand and remain at the bottom of their pits with their long piercing jaws from where they seize and remove the body fluids of the ant and other arthropods that slide into their trap. The effects of hunger and density on the spatial distribution and pit construction by the larvae were studied for the three instar stages in fine and coarse sand textures of particles size of <540 μm and <1200 μm respectively.Twenty four (24) Iron trays of 25cm2 each filled with sand to the depth of 20cm were used in the study.The result of the findings reveals that with the increase in density, there was an increased in spatial uniformity and the pits became uniformly distributed. The diameters of the pit were not statistically affected by the changes in the larval density. There was difference between the total number of pits constructed between sand textures and not between the larval instars, in addition, nearest neighbor distance decreases with increase in density and with no effect on pit diameter. Pit diameter increases with hunger level and Antlion move pit to reducedisturbances and to improve food supply. The result analysis showed significant differences in the mean number of pits constructed between densities, sand texture and larval instars at P< 0.01 but none between fed and larval instar.Keywords: Antlion, Construction, Density, Distribution, Hunger, Larvae, Pit

Stochastic Analysis and Performance Evaluation of a Complex Thermal Power Plant

This paper present the stochastic analysis and performance evaluation of the thermal power plant which serve as an improvement of Vora 2011, by the use of performance evaluation using probabilistic approach. The research study consists mainly three sub-systems namely boiler, super heater and re-heater connected in series configuration with two type of preventive maintenance ie offline and online. The analysis shows that as failure rate increases, the availability decreases and as repair rate increases, the availability of the system increases and vice-versa. Performance matrices shows that Super heater subsystem is the most critical subsystem among the three subsystems in the power generation plant as far as maintenance is concern, as its availability percentage is the least among the three subsystem and boiler subsystem is having the higher percentage of availability with about 99% level. The results of the analysis are found beneficial to the plant management for the availability analysis of the system. Key words: Reliability, Availability, Maintainability

Effects of Allelochemicals of Some Eucalyptus Species on Germination and Radicle Growth of Arachis Hypogea

A laboratory experiment was conducted to assess the effects of allelochemicals of Eucalyptus camaldulensis, Eucalyptus citriodora and Eucalyptus globules on germination and root elongation using leguminous crop ground nut (Arachis hypogea) as bioassay material. The experiments were conducted in sterilized petridishes. The effect of different concentration of aqueous extracts was compared with distilled water (control). The result revealed that different concentrations of E. globulus and E. camaldulensis extracts caused highly significant (p=0.05) inhibitory effect on germination and root elongation. The bioassays indicated that the inhibitory effect was proportional to the concentrations of the extracts so that higher concentration has a stronger inhibitory effect. The study also revealed that inhibitory effect was much pronounced in root development rather than seed germination. Key words: Allelochemicals, Eucalyptus species, Root length, Germination, Arachis hypoge

Influence of Effective Microorganisms on Qualities of Tomatoes (Lycopersicon esculentum) Grown on Tropical Loam Soil

The use of Effective Microorganism (EM) consortium along with compost may overcome the harmful effects caused by chemical fertilizer while improving the nutritional quality of crops. The study aimed to determining the influence of compost inoculated with EM on the nutritional qualities of tomatoes (Lycopersicon esculentum) grown in tropical loam soil.  Four sets of treated loamy soils was experimented. The treatments were the compost without EM (C); compost containing effective microorganisms (EM); compost containing effective microorganisms with chicken manure (CEM) and urea as mineral fertilizer (M). Tomatoes were harvested randomly after matured and kept in plastic bag and immediately transferred to the laboratory for analysis of beta-carotene, vitamin C and brix contents.  The results shows that tomatoes planted with EM inoculated compost have relatively higher level of β-Carotene (7.76µg/100g), Brix (4.9%), and vitamin C (77.55mg/100g) compared with those from mineral 4.01µg/100g, 4.8%, and 3.83mg/100g respectively. This is likely reflect the efficiency of organic nature decomposition of EM compost over mineral fertilizers. We may therefore conclude that EM compost can be applied to supersede chemical fertilizer to promote sustainable and environmentally friendly tomatoes agriculture. Keywords: Beta-carotene, Brix, Compost, Effective microorganisms, Vitamin C