Advanced security testing using a cyber-attack forecasting model: A case study of financial institutions

As the number of cyber-attacks on financial institutions has increased over the past few years, an advanced system that is capable of predicting the target of an attack is essential. Such a system needs to be integrated into the existing detection systems of financial institutions as it provides them with proactive controls with which to halt an attack by predicting patterns. Advanced prediction systems also enhance the software design and security testing of new advanced cyber-security measures by providing new testing scenarios supported by attack forecasting. This present study developed a model that forecasts future network-based cyber-attacks on financial institutions using a deep neural network. The dataset that was used to train and test the model consisted of some of the biggest cyber-attacks on banking institutions over the past three years. This provided insight into new patterns that may end with a cyber-crime. These new attacks were also evaluated to determine behavioral similarities with the nearest known attack or a combination of several existing attacks. The performance of the forecasting model was then evaluated in a real banking environment and provided a forecasting accuracy of 90.36%. As such, financial institutions can use the proposed forecasting model to improve their security testing measures.Dado que el número de ciberataques a instituciones financieras ha aumentado en los últimos años, es esencial contar con un sistema avanzado que sea capaz de predecir el objetivo de un ataque. Un sistema de este tipo debe integrarse en los sistemas de detección existentes de las instituciones financieras, ya que les proporciona controles proactivos con los que detener un ataque mediante la predicción de patrones. Los sistemas de predicción avanzados también mejoran el diseño de software y las pruebas de seguridad de nuevas medidas avanzadas de ciberseguridad al proporcionar nuevos escenarios de prueba respaldados por la previsión de ataques. Este presente estudio desarrolló un modelo que pronostica futuros ciberataques basados ​​en redes contra instituciones financieras utilizando una red neuronal profunda. El conjunto de datos que se utilizó para entrenar y probar el modelo consistió en algunos de los mayores ataques cibernéticos a instituciones bancarias en los últimos tres años. Esto proporcionó información sobre nuevos patrones que pueden terminar en un delito cibernético. Estos nuevos ataques también fueron evaluados para determinar similitudes de comportamiento con el ataque conocido más cercano o una combinación de varios ataques existentes. Luego se evaluó el desempeño del modelo de pronóstico en un entorno bancario real y proporcionó una precisión de pronóstico del 90,36%. Como tal, las instituciones financieras pueden utilizar el modelo de pronóstico propuesto para mejorar sus medidas de prueba de seguridad.2022-2

Effect of educational intervention on healthcare providers knowledge and perception towards pharmacovigilance: A tertiary teaching hospital experience

Objective: Based on the theory on planned behavior, perception or attitude is found to be a well-established predictor of healthcare providers’ intentions to perform different behaviors. Also, improving knowledge was proposed to affect their practice as well. In Jordan, many studies have been conducted to evaluate healthcare providers’ knowledge and perception towards pharmacovigilance but no intervention or training was provided. Thus, the aim of this study was to evaluate the impact of an educational workshop on the knowledge and perception of healthcare providers towards pharmacovigilance in a Jordanian tertiary teaching hospital. Methods: An interventional study conducted in Jordan University Hospital on various healthcare providers to assess their pre- and post-knowledge and perception towards pharmacovigilance and adverse drug reactions (ADRs) reporting via questionnaire before and after an educational workshop. Results: Among the 200 invited healthcare providers, 150 attended the educational workshop (response rate 75.0%). Pre-workshop, healthcare providers showed an overall low knowledge score (7.8/19), where only 8.7% could define pharmacovigilance correctly. On the other hand, they showed a favorable perception score (33.6/39).Following educational workshop, knowledge scores significantly improved by 67.9% (P-value <0.05). A similar finding was obtained for perception scores, where perception scores significantly improved by 10.1% following workshop (P-value <0.05). Conclusion: Continuous efforts are needed to implement different strategies including education modules and the provision of appropriate training programs to increase awareness and improve perception towards pharmacovigilance among healthcare providers. Future study is needed to evaluate the impact of improving knowledge and perception on ADRs reporting practice. Keywords: Educational workshop, Pharmacovigilance, Adverse drug reactions, Healthcare providers, Jorda

Medication histories documentation at the community pharmacy setting: A study from Jordan.

OBJECTIVES:The main objective of this study was to evaluate community pharmacists' awareness and perception about medication reconciliation service and to assess the completeness of collecting patients' medication histories in the community pharmacy setting. METHODS:A cross-sectional study was conducted between February to March 2018 in Amman-Jordan. During the study period, 150 community pharmacists were invited to participate in the study. Each pharmacist completed a validated structured questionnaire evaluating their awareness, current practice, perceived attitude and perceived barriers towards the implementation of medication reconciliation and the collection of medication histories at the community pharmacy setting. RESULTS:A total of 121 pharmacists agreed to participate and filled the questionnaire. Our results showed that only 13.2% of the pharmacists were able to define "medication reconciliation" correctly, and around 31% have a misconception that the medication reconciliation process should be performed only at the inpatient setting. Only 19.8% (n = 24) of the participating pharmacists stated that they ask all patients for a complete current medication list of medications when they arrive at the pharmacy site. Medication histories for most patients were lacking information about the dosage, route, frequency, and time of the last refill for each medication listed. "Patients lack of awareness about all the medications they are receiving" was the main barrier discouraging community pharmacists from collecting medication histories and participating in reconciliation service. CONCLUSION:Community pharmacists in Jordan showed a low awareness about the medication reconciliation concept and demonstrated a modest role in obtaining medication histories in community pharmacies. But still, they showed a positive attitude towards their role in implementing the different steps of medication reconciliation. This suggests that educational workshops to increase pharmacists' awareness about their role and responsibilities in collecting a complete and accurate medication history are warrented