scholarly journals Spam Filtering Security Evaluation Framework Using SVM, LR and MILR

2016 ◽  
Vol 3 (2/3) ◽  
pp. 19-27
Author(s):  
Kunjali Pawar ◽  
Madhuri Patil
2016 ◽  
Vol 8 (2) ◽  
pp. 51-69 ◽  
Author(s):  
Steve Harrison ◽  
Antonis Tzounis ◽  
Leandros Maglaras ◽  
Francois Siewe ◽  
Richard Smith ◽  
...  

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Haichun Zhang ◽  
Yuqian Pan ◽  
Zhaojun Lu ◽  
Jie Wang ◽  
Zhenglin Liu

Ingenium ◽  
2014 ◽  
Vol 8 (21) ◽  
pp. 11
Author(s):  
Manuel Fernando Fuentes Amaya ◽  
Johan Alberto Gómez Girón

El Android Security Evaluation Framework [ASEF] fue seleccionado por el proyecto Safe Candy como punto de partida para el desarrollo de un aplicativo para control de malware en teléfonos inteligentes con sistema operativo Android, debido a sus características, presentadas en Black-Hat 2012, que lo mostraban como una herramienta poderosa, innovadora y de gran potencial. Como primera actividad, el proyecto realizó una valoración del nivel de avance y la confiabilidad de ASEF, buscando determinar su validez como base de desarrollo e identificar el punto de partida para la generación de la aplicación esperada. Las pruebas de funcionamiento, exactitud y rapidez realizadas, mostraron debilidades y pendientes en el framework, resultado que generó la necesidad de redefinir la metodología prevista, con base en la cual el proyecto desarrolló un sistema para el análisis, la validación y el diagnóstico de aplicaciones Android, que integra –aunque solo de manera complementaria– a la plataforma ASEF. Al producto final se le realizó el mismo set de pruebas, obteniendo una tasa de éxito de 100%


2021 ◽  
pp. 79-92
Author(s):  
Mosabbah Mushir Ahmed ◽  
Youssef Souissi ◽  
Oualid Trabelsi ◽  
Sylvain Guilley ◽  
Antoine Bouvet ◽  
...  

Author(s):  
Syed Rizvi ◽  
Kelsey Karpinski ◽  
Brennen Kelly ◽  
Taryn Walker

2015 ◽  
Vol 16 (2) ◽  
pp. 350
Author(s):  
MD. Hussain Khan ◽  
G. Pradeepini

<p>Phone is a device which provides communication between the people through voice, text, video etc. Now a day’s people may leave without food but not without using phones. No of operating systems are working with various versions and various security issues are working. Security is very important task in Mobiles and mobile apps. To improve the security status of mobiles, existing methodology is using cloud computing and data mining. Out traditional method is named as MobSafe to identify the mobile apps antagonism or graciousness. In the proposed system, we adopt Android Security Evaluation Framework (ASEF) and Static Android Analysis Framework (SAAF).In this paper, our proposed system works on machine learning to conduct automotive forensic analysis of mobile apps based on the generated multifaceted data in this stage.</p>


2017 ◽  
Vol 74 (11) ◽  
pp. 5774-5796 ◽  
Author(s):  
Syed Rizvi ◽  
Jungwoo Ryoo ◽  
John Kissell ◽  
William Aiken ◽  
Yuhong Liu

2015 ◽  
Vol 737 ◽  
pp. 210-213
Author(s):  
Liang Chen ◽  
Xiao Jun Zuo ◽  
Yu Fei Wang

Analyzing the characters and abstracting the system model of the distribution automation system, information security test-bed of distribution automation is designed. Meanwhile, information security test and evaluation framework is proposed based on the lifecycle of distribution automation system. The evaluation activities and the testing methods are analyzed and key problems and solutions of information security evaluation and reinforcement requirements for distribution automation system are introduced. The work in this paper can effectively support the information security protection of distribution automation system, and can provide reference for other power industrial control systems.


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