Identification of Cryptographic Vulnerability and Malware Detection in Android

Anjali Kumawat; Anil Kumar Sharma; Sunita Kumawat

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Identification of Cryptographic Vulnerability and Malware Detection in Android

机译：识别Android中的加密漏洞和恶意软件检测

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>Android based Smartphones are nowadays getting more popular. While using Smartphone, user is always concerned about security and malicious attacks, cryptographic vulnerability of the applications. With increase in the number of Android mobiles, Android malwares are also increasing very rapidly. So the authors have proposed the “Identification of cryptographic vulnerability and malware detection in Android” system. They have designed a user friendly android application, through which user and developer can easily test the application whether it is benign or vulnerable. The application will be tested firstly using static analysis and then the dynamic analysis will be carried out. The authors have implemented static and dynamic analysis of android application for vulnerable and malicious app detection. They have also created a web page. User can either use the application or the web page.

机译： >基于Android的智能手机是如今越来越流行。在使用智能手机时，用户始终担心应用程序的安全性和恶意攻击，加密漏洞。随着Android手机数量的增加，Android恶意软件的数量也在迅速增加。因此，作者提出了“ Android中的加密漏洞识别和恶意软件检测”。他们设计了一个用户友好的android应用程序，通过它用户和开发人员可以轻松地测试该应用程序是良性还是脆弱。该应用程序将首先使用静态分析进行测试，然后再进行动态分析。作者已对Android应用程序实施了静态和动态分析，以检测易受攻击和恶意的应用程序。他们还创建了一个网页。用户可以使用应用程序或网页。

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来源
《International journal of information security and privacy》 |2017年第3期|15-28|共14页
作者
Anjali Kumawat; Anil Kumar Sharma; Sunita Kumawat;
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作者单位

Government Women Engineering College, Ajmer, India;

Government Women Engineering College, Ajmer, India;

Government Women Engineering College, Ajmer, India;

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原文格式 PDF
正文语种 eng
中图分类
关键词
Android; Attacks; Intrusions; Malware; Network; Reliable; Security; Vulnerability;

机译：Android;攻击;入侵;恶意软件;网络;可靠;安全性;漏洞;

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2. DeepAMD: Detection and identification of Android malware using high-efficient Deep Artificial Neural Network [J] . Syed Ibrahim Imtiaz, Saif ur Rehman, Abdul Rehman Javed, Future generation computer systems . 2021,第Feba期

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3. Lightweight, Obfuscation-Resilient Detection and Family Identification of Android Malware [J] . JOSHUA GARCIA, MAHMOUD HAMMAD, SAM MALEK ACM transactions on software engineering and methodology . 2017,第3期

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6. Adversarial Samples on Android Malware Detection Systems for IoT Systems [O] . Xiaolei Liu, Xiaojiang Du, Xiaosong Zhang, 2019

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Identification of Cryptographic Vulnerability and Malware Detection in Android

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