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

Adoption of E-procurement and Value Addition: Tanzanian context

E-procurement referred to the use of internet-based (integrated) information and communication technologies (ICTs) to carry out individual or all stages of the procurement process including searching, sourcing, negotiation, ordering, receipt, and post-purchase review. Even though E-procurement is not a new process but in Tanzania is at infant stage. This article aim at analysing the adoption of E-procurement and Value Addition: The Tanzanian Context. A key three factors have been reviewed and critically analysed involve which the Technological factors (T), Organizational factors (O) and Environmental factors (E) (T-O-E). Findings provided ample evidence that Tanzania can adopt e-procurement and enjoy the fruits of this new technology. Keywords: e-procurement, TOE framework.

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

Assessment of Patient Satisfaction with Preoperative Anesthetic Evaluation and Assosated Factors at Menelik Referal Hospital Addis Ababa, Ethiopia

Background: Patient Satisfaction- refers to a state of pleasure or happiness with an action or service especially one that was earlier desired. Patient satisfaction is progressively appreciated measure of outcome for health care procedures and it was a measure of success in this hospitals. It was affected by anesthetist’s patient interaction, in the preoperative anesthetic evaluation. No prior study conducted in our setup. Objective: The purpose of this study was to evaluate inpatients’ satisfaction with preoperative anesthetic evaluation and associated factors at Menelik II Referral Hospital Addis Ababa Ethiopia. Methods- Institutional based cross sectional study was conducted at Menelik II Referral Hospital from Jan 6 to Feb 6, 2016, All patients who remained for elective surgery were included in the study period and interview 24 hours after operation. Data were collected using pretested standard questionnaires. All items in the structured questionnaire were scored on five point Likert scale. Data was entered and analyzed using Statistical Package for Social Sciences (SPSS) version 20. Binary logistic regression was used to measure statistical significance between dependent and each independent variable. P-value 0.05 and 95% CI was used as cut off point. Results: Two hundred and seventy-five patients were operated upon under anesthesia during the study period. Of these, a total of 224 patients were included in this study with a response rate of 81.5 %, with the overall proportion of patients who said they were satisfied with anesthesia services was 72.3 %.the major factors that take patient dissatisfaction were 68.1% of patient explain anesthetist were not introduce him or herself to the patient, information on postoperative analgesia were 99.1% and postoperative nausea vomiting management were accounts 84.8%. Conclusion and recommendation: Patient satisfaction with anesthesia services was low 72.3 % in our setup compared with many previous studies, and females more dissatisfied 42.4 % than males 57.6 %. Factors that affected patient satisfaction negatively may be preventable or enhanced. Further study should be done and patient satisfaction give an emphasis

Effects of General Versus Spinal Anesthesia Over Apgar Score of Newborns Delivered by Cesarean Sections and Factors Associated with Apgar Score at Gandhi Memorial Hospital, Addis Ababa

Introduction: Apgar score is a practical method of systemically assessing newborn baby immediately after birth to identify those requiring resuscitation and to predict survival in neonatal period. It is best parameter to assess the immediate condition of the baby. Objective: To assess the effects of general versus spinal anesthesia over Apgar score of newborns delivered by cesarean sections and factors associated with Apgar score from January to March 2016 at Gandhi Memorial Hospital, Addis Ababa. Method: Institutional based comparative cross sectional study design was conducted. Systematic random sampling technique was used to select study participants. Regular supervision and follow up was made. Data was entered into Epi info version 7 by investigators and was transported to SPSS version 20 for analysis. Bivariate and multivariate analysis was used to identify factors associated with Apgar score. Result: A total of 86 study subjects were included in the study of which majority of new born baby had low Apgar score at one minute. Out of 43 mothers, who received spinal anesthesia, 15 patients (34.88%) gave birth to neonates having Apgar score >7 at one minute. On the other hand, out of 43 mothers who received general anesthesia, 7(16.3%) mothers gave birth to neonate having Apgar score ≥7at one minute. It had been found that neonates who were born under general anesthesia were three folds more likely to have low Apgar score than the other (AOR 2.768 (95% CI ((.876-8.745). Conclusion and recommendation: There was relatively a low Apgar score among newborn babies delivered under general anesthesia.  Hence, practice of spinal anesthesia was recommended

The Role of Family Planning on Economic Development at Health Centers in Halaba Special Woreda, Southern, Ethiopia

Introduction. Family planning is the mechanisms that initiate the economic development by reducing rapid population growth through providing effective use of birth controlling method. When effective family planning occurs in an environment with rapid economic development and major technological advance, it actually contributes to the national development efforts. If population growth can be slow down, each person’s share of countries resource could be greater. Objective: To assess factors influencing clinical outcomes of patients admitted to intensive care units from January 2015 to January 2016 at Nigist Eleni Mohammed Memorial Hospital, hosanna, southern Ethiopia. Method: Institutional based cross sectional study design was conducted. All health professionals working at Nigist Eleni Mohammed Memorial Hosp during the study period were included. Regular supervision and follow up was made. Bivariate analysis was used to identify factors associated with economic development. The result was interpreted using table, graph and narrative. Result: A total of 40 participants were enrolled into the study of 65 %( 26) of respondents were males. Most of respondents 37.5% (15) and 35 %( 14) were in age group of 18-25 and 26-35respectively. Over two fifth and one third of respondents have not used family planning due to lack of knowledge about family planning and lack of having communication with health care provider. Conclusion and recommendation: Family planning has a negative impact on population growth and development therefore, it was recommended that proper use of birth controlling method was strongly were recommended

Surface Runoff Responses to Rainfall Variability over the Bida Basin, Nigeria

Information on annual, seasonal, monthly and daily rainfall variation is desirable for planning operation and management of water resource projects as this gives an insight into river flow regimes.  A surface runoff response to rainfall variation in The Bida River Basin was investigated.  The River Basin has an area extent of about 7,540 km2.  The research utilizes rainfall data for a period of 30 years (1980 – 2009) mean, standard deviation, coefficient of variation and linear regression are used in the analysis. Results indicate that the rainfall pattern is generally in the form of alternating dry and wet years, and characterized by strong seasonality which is reflected in the surface runoff. Declining trend in rainfall over the years has been observed during the study period and is also reflected in the overall decline in runoff leading to variability in annual flow regimes. Therefore, attention should be focused on development of networking of continuous observation and monitoring of hydrometeorological variables and also control of environmental factors that influence the hydrology of the Bida Basin. Keywords: Rainfall, Runoff, Landscape, Streamflow, Seasonalit