Malware Detection In Android Phones
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| Author | : Sapna Malik |
| Publisher | : diplom.de |
| Total Pages | : 45 |
| Release | : 2017-11-06 |
| Genre | : Computers |
| ISBN | : 3960677049 |
Download Malware Detection in Android Phones Book in PDF, Epub and Kindle
The smartphone has rapidly become an extremely prevalent computing platform, with just over 115 million devices sold in the third quarter of 2011, a 15% increase over the 100 million devices sold in the first quarter of 2011, and a 111% increase over the 54 million devices sold in the first quarter of 2010. Android in particular has seen even more impressive growth, with the devices sold in the third quarter of 2011 (60.5 million) almost triple the devices sold in the third quarter of 2010 (20.5 million), and an associated doubling of market share. This popularity has not gone unnoticed by malware authors. Despite the rapid growth of the Android platform, there are already well-documented cases of Android malware, such as DroidDream, which was discovered in over 50 applications on the official Android market in March 2011. Furthermore, it is found that Android’s built-in security features are largely insufficient, and that even non malicious programs can (unintentionally) expose confidential information. A study of 204,040 Android applications conducted in 2011 found 211 malicious applications on the official Android market and alternative marketplaces. The problem of using a machine learning-based classifier to detect malware presents the challenge: Given an application, we must extract some sort of feature representation of the application. To address this problem, we extract a heterogeneous feature set, and process each feature independently using multiple kernels.We train a One-Class Support Vector Machine using the feature set we get to classify the application as a benign or malware accordingly.
| Author | : Mihai Christodorescu |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 307 |
| Release | : 2007-03-06 |
| Genre | : Computers |
| ISBN | : 0387445994 |
Download Malware Detection Book in PDF, Epub and Kindle
This book captures the state of the art research in the area of malicious code detection, prevention and mitigation. It contains cutting-edge behavior-based techniques to analyze and detect obfuscated malware. The book analyzes current trends in malware activity online, including botnets and malicious code for profit, and it proposes effective models for detection and prevention of attacks using. Furthermore, the book introduces novel techniques for creating services that protect their own integrity and safety, plus the data they manage.
| Author | : Xuxian Jiang |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 50 |
| Release | : 2013-06-13 |
| Genre | : Computers |
| ISBN | : 1461473942 |
Download Android Malware Book in PDF, Epub and Kindle
Mobile devices, such as smart phones, have achieved computing and networking capabilities comparable to traditional personal computers. Their successful consumerization has also become a source of pain for adopting users and organizations. In particular, the widespread presence of information-stealing applications and other types of mobile malware raises substantial security and privacy concerns. Android Malware presents a systematic view on state-of-the-art mobile malware that targets the popular Android mobile platform. Covering key topics like the Android malware history, malware behavior and classification, as well as, possible defense techniques.
| Author | : Weina Niu |
| Publisher | : Springer Nature |
| Total Pages | : 197 |
| Release | : |
| Genre | : |
| ISBN | : 9819714591 |
Download Android Malware Detection and Adversarial Methods Book in PDF, Epub and Kindle
| Author | : ElMouatez Billah Karbab |
| Publisher | : Springer Nature |
| Total Pages | : 212 |
| Release | : 2021-07-10 |
| Genre | : Computers |
| ISBN | : 303074664X |
Download Android Malware Detection using Machine Learning Book in PDF, Epub and Kindle
The authors develop a malware fingerprinting framework to cover accurate android malware detection and family attribution in this book. The authors emphasize the following: (1) the scalability over a large malware corpus; (2) the resiliency to common obfuscation techniques; (3) the portability over different platforms and architectures. First, the authors propose an approximate fingerprinting technique for android packaging that captures the underlying static structure of the android applications in the context of bulk and offline detection at the app-market level. This book proposes a malware clustering framework to perform malware clustering by building and partitioning the similarity network of malicious applications on top of this fingerprinting technique. Second, the authors propose an approximate fingerprinting technique that leverages dynamic analysis and natural language processing techniques to generate Android malware behavior reports. Based on this fingerprinting technique, the authors propose a portable malware detection framework employing machine learning classification. Third, the authors design an automatic framework to produce intelligence about the underlying malicious cyber-infrastructures of Android malware. The authors then leverage graph analysis techniques to generate relevant intelligence to identify the threat effects of malicious Internet activity associated with android malware. The authors elaborate on an effective android malware detection system, in the online detection context at the mobile device level. It is suitable for deployment on mobile devices, using machine learning classification on method call sequences. Also, it is resilient to common code obfuscation techniques and adaptive to operating systems and malware change overtime, using natural language processing and deep learning techniques. Researchers working in mobile and network security, machine learning and pattern recognition will find this book useful as a reference. Advanced-level students studying computer science within these topic areas will purchase this book as well.
| Author | : Sapna Malik |
| Publisher | : Anchor Academic Publishing |
| Total Pages | : 49 |
| Release | : 2017-12 |
| Genre | : Computers |
| ISBN | : 3960672047 |
Download Malware Detection in Android Phones Book in PDF, Epub and Kindle
The smartphone has rapidly become an extremely prevalent computing platform, with just over 115 million devices sold in the third quarter of 2011, a 15% increase over the 100 million devices sold in the first quarter of 2011, and a 111% increase over the 54 million devices sold in the first quarter of 2010. Android in particular has seen even more impressive growth, with the devices sold in the third quarter of 2011 (60.5 million) almost triple the devices sold in the third quarter of 2010 (20.5 million), and an associated doubling of market share. This popularity has not gone unnoticed by malware authors. Despite the rapid growth of the Android platform, there are already well-documented cases of Android malware, such as DroidDream, which was discovered in over 50 applications on the official Android market in March 2011. Furthermore, it is found that Android’s built-in security features are largely insufficient, and that even non malicious programs can (unintentionally) expose confidential information. A study of 204,040 Android applications conducted in 2011 found 211 malicious applications on the official Android market and alternative marketplaces. The problem of using a machine learning-based classifier to detect malware presents the challenge: Given an application, we must extract some sort of feature representation of the application. To address this problem, we extract a heterogeneous feature set, and process each feature independently using multiple kernels.We train a One-Class Support Vector Machine using the feature set we get to classify the application as a benign or malware accordingly.
| Author | : Qian Han |
| Publisher | : No Starch Press |
| Total Pages | : 330 |
| Release | : 2023-11-07 |
| Genre | : Computers |
| ISBN | : 1718503318 |
Download The Android Malware Handbook Book in PDF, Epub and Kindle
Written by machine-learning researchers and members of the Android Security team, this all-star guide tackles the analysis and detection of malware that targets the Android operating system. This groundbreaking guide to Android malware distills years of research by machine learning experts in academia and members of Meta and Google’s Android Security teams into a comprehensive introduction to detecting common threats facing the Android eco-system today. Explore the history of Android malware in the wild since the operating system first launched and then practice static and dynamic approaches to analyzing real malware specimens. Next, examine machine learning techniques that can be used to detect malicious apps, the types of classification models that defenders can implement to achieve these detections, and the various malware features that can be used as input to these models. Adapt these machine learning strategies to the identifica-tion of malware categories like banking trojans, ransomware, and SMS fraud. You’ll: Dive deep into the source code of real malware Explore the static, dynamic, and complex features you can extract from malware for analysis Master the machine learning algorithms useful for malware detection Survey the efficacy of machine learning techniques at detecting common Android malware categories The Android Malware Handbook’s team of expert authors will guide you through the Android threat landscape and prepare you for the next wave of malware to come.
| Author | : Erol Gelenbe |
| Publisher | : Springer |
| Total Pages | : 169 |
| Release | : 2018-07-13 |
| Genre | : Computers |
| ISBN | : 3319951890 |
Download Security in Computer and Information Sciences Book in PDF, Epub and Kindle
This open access book constitutes the thoroughly refereed proceedings of the First International ISCIS Security Workshop 2018, Euro-CYBERSEC 2018, held in London, UK, in February 2018. The 12 full papers presented together with an overview paper were carefully reviewed and selected from 31 submissions. Security of distributed interconnected systems, software systems, and the Internet of Things has become a crucial aspect of the performance of computer systems. The papers deal with these issues, with a specific focus on societally critical systems such as health informatics systems, the Internet of Things, energy systems, digital cities, digital economy, mobile networks, and the underlying physical and network infrastructures.
| Author | : Zarni Aung |
| Publisher | : LAP Lambert Academic Publishing |
| Total Pages | : 132 |
| Release | : 2015-02-11 |
| Genre | : |
| ISBN | : 9783659673986 |
Download Machine Learning Based Android Malware Detection Book in PDF, Epub and Kindle
Mobile phones have become central computing and communication devices since they offer almost the same functionalities as personal computers. They are also becoming ubiquitous and it has been an increase in the number of mobile users who are relying on them to store and handle personal information. Among them, Android-based mobile phones had appeared lately and were widely used so that they became an ideal target for malware developers. Android phone users can get free applications by downloading from the websites of Android Application Markets. Unfortunately, this phenomenon draws attention to malicious applications developers to upload their malicious applications. Because the free downloaded applications are not certified by legitimate organizations, they contain malware applications that can steal users' private information.
| Author | : Hector Florez |
| Publisher | : Springer |
| Total Pages | : 380 |
| Release | : 2018-10-24 |
| Genre | : Computers |
| ISBN | : 3030015351 |
Download Applied Informatics Book in PDF, Epub and Kindle
This book constitutes the thoroughly refereed papers of the First International Conference on Applied Informatics, ICAI 2018, held in Bogotá, Colombia, in November 2018. The 27 full papers were carefully reviewed and selected from 81 submissions. The papers are organized in topical sections on data analysis; decision systems; health care information systems; IT architectures; learning management systems; mobile information processing systems; robotic autonomy; software design engineering.
