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Significant Permission Identification For Android Malware Detection
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Book Synopsis Significant Permission Identification for Android Malware Detection by : Lichao Sun
Download or read book Significant Permission Identification for Android Malware Detection written by Lichao Sun and published by . This book was released on 2016 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt: A recent report indicates that a newly developed malicious app for Android is introduced every 11 seconds. To combat this alarming rate of malware creation, we need a scalable malware detection approach that is effective and efficient. In this thesis, we introduce SigPID, a malware detection system based on permission analysis to cope with the rapid increase in the number of Android malware. Instead of analyzing all 135 Android permissions, our approach applies 3-level pruning by mining the permission data to identify only significant permissions that can be effective in distinguishing benign and malicious apps. Based on the identified significant permissions, SigPID utilizes classification algorithms to classify different families of malware and benign apps. Our evaluation finds that only 25% of permissions (34 out of 135 permissions) are significant. We then compare the performance of our approach, using only 25% of all permissions, against a baseline approach that analyzes all permissions. The results indicate that when Support Vector Machine (SVM) is used as the classifier, we can achieve over 90% of precision, recall, accuracy, and F-measure, which are about the same as those produced by the baseline approach. We also show that SigPID is effective when used with 67 other commonly used supervised learning approaches. We find that 55 out of 67 algorithms can achieve F-measure of at least 85%, while the average running time can be reduced by 85.6\% compared with the baseline approach. When we compare the detection effectiveness of SigPID to those of other approaches, SigPID can detect 96.54% of malware in the data set while other approaches detect 3.99% to 96.41%.
Book Synopsis Malware Detection by : Mihai Christodorescu
Download or read book Malware Detection written by Mihai Christodorescu and published by Springer Science & Business Media. This book was released on 2007-03-06 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Android Malware Detection using Machine Learning by : ElMouatez Billah Karbab
Download or read book Android Malware Detection using Machine Learning written by ElMouatez Billah Karbab and published by Springer Nature. This book was released on 2021-07-10 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Android Malware Detection and Adversarial Methods by : Weina Niu
Download or read book Android Malware Detection and Adversarial Methods written by Weina Niu and published by Springer Nature. This book was released on with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Malware Diagnosis written by Bohyun Suh and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Android mobile phone has rapidly become popular and irreplaceable. The open-source Android platform allows developers to innovate the Android market in various ways, but also raises significant issues with various malicious apps, such as device malfunction, personal information leak, or financial loss. Yet, it is difficult to detect malicious apps by a human or obtain explicit information about suspicious apps. To solve the problem, many studies have come up with some frameworks. However, many frameworks have constraints such as only running on PC and manual data processing. In this thesis, we propose the Malware Diagnosis framework for deep learning-based malware detection using weighted permission. It is designed to be more practical to use with better performance in detecting malware apps. To increase the accuracy of the framework, we apply a ranking-based approach to permissions to generate weights that are derived from the ranking based on the number of permission used from malware and benign apps. As a tool, we develop MD (Malware Diagnosis) Assistant, an Android app that performs automated data extraction from installed apps and provides a prediction rate by running a deep learning model on an Android device. We then present experimental observations that show the effectiveness of our framework on detecting malware apps.
Book Synopsis Android Malware Detection Through Permission and App Component Analysis Using Machine Learning Algorithms by : Keyur Milind Kulkarni
Download or read book Android Malware Detection Through Permission and App Component Analysis Using Machine Learning Algorithms written by Keyur Milind Kulkarni and published by . This book was released on 2018 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: Improvement in technology has inevitably altered the tactic of criminals to thievery. In recent times, information is the real commodity and it is thus subject to theft as any other possessions: cryptocurrency, credit card numbers, and illegal digital material are on the top. If globally available platforms for smartphones are considered, the Android open source platform (AOSP) emerges as a prevailing contributor to the market and its popularity continues to intensify. Whilst it is beneficiary for users, this development simultaneously makes a prolific environment for exploitation by immoral developers who create malware or reuse software illegitimately acquired by reverse engineering. Android malware analysis techniques are broadly categorized into static and dynamic analysis. Many researchers have also used feature-based learning to build and sustain working security solutions. Although Android has its base set of permissions in place to protect the device and resources, it does not provide strong enough security framework to defend against attacks. This thesis presents several contributions in the domain of security of Android applications and the data within these applications. First, a brief survey of threats, vulnerability and security analysis tools for the AOSP is presented. Second, we develop and use a genre extraction algorithm for Android applications to check the availability of those applications in Google Play Store. Third, an algorithm for extracting unclaimed permissions is proposed which will give a set of unnecessary permissions for applications under examination. Finally, machine learning aided approaches for analysis of Android malware were adopted. Features including permissions, APIs, content providers, broadcast receivers, and services are extracted from benign (~2,000) and malware (5,560) applications and examined for evaluation. We create feature vector combinations using these features and feed these vectors to various classifiers. Based on the evaluation metrics of classifiers, we scrutinize classifier performance with respect to specific feature combination. Classifiers such as SVM, Logistic Regression and Random Forests spectacle a good performance whilst the dataset of combination of permissions and APIs records the maximum accuracy for Logistic Regression.
Book Synopsis Malware Analysis Using Artificial Intelligence and Deep Learning by : Mark Stamp
Download or read book Malware Analysis Using Artificial Intelligence and Deep Learning written by Mark Stamp and published by Springer Nature. This book was released on 2020-12-20 with total page 651 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis. The individual chapters of the book deal with a wide variety of state-of-the-art AI and DL techniques, which are applied to a number of challenging malware-related problems. DL and AI based approaches to malware detection and analysis are largely data driven and hence minimal expert domain knowledge of malware is needed. This book fills a gap between the emerging fields of DL/AI and malware analysis. It covers a broad range of modern and practical DL and AI techniques, including frameworks and development tools enabling the audience to innovate with cutting-edge research advancements in a multitude of malware (and closely related) use cases.
Book Synopsis Android Malware and Analysis by : Ken Dunham
Download or read book Android Malware and Analysis written by Ken Dunham and published by CRC Press. This book was released on 2014-10-24 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rapid growth and development of Android-based devices has resulted in a wealth of sensitive information on mobile devices that offer minimal malware protection. This has created an immediate need for security professionals that understand how to best approach the subject of Android malware threats and analysis. In Android Malware and Analysis, Ken Dunham, renowned global malware expert and author, teams up with international experts to document the best tools and tactics available for analyzing Android malware. The book covers both methods of malware analysis: dynamic and static. This tactical and practical book shows you how to use to use dynamic malware analysis to check the behavior of an application/malware as it has been executed in the system. It also describes how you can apply static analysis to break apart the application/malware using reverse engineering tools and techniques to recreate the actual code and algorithms used. The book presents the insights of experts in the field, who have already sized up the best tools, tactics, and procedures for recognizing and analyzing Android malware threats quickly and effectively. You also get access to an online library of tools that supplies what you will need to begin your own analysis of Android malware threats. Tools available on the book’s site include updated information, tutorials, code, scripts, and author assistance. This is not a book on Android OS, fuzz testing, or social engineering. Instead, it is about the best ways to analyze and tear apart Android malware threats. After reading the book, you will be able to immediately implement the tools and tactics covered to identify and analyze the latest evolution of Android threats. Updated information, tutorials, a private forum, code, scripts, tools, and author assistance are available at AndroidRisk.com for first-time owners of the book.
Book Synopsis Cyber Security and Digital Forensics by : Kavita Khanna
Download or read book Cyber Security and Digital Forensics written by Kavita Khanna and published by Springer Nature. This book was released on 2021-10-01 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features high-quality research papers presented at the International Conference on Applications and Techniques in Cyber Security and Digital Forensics (ICCSDF 2021), held at The NorthCap University, Gurugram, Haryana, India, during April 3–4, 2021. This book discusses the topics ranging from information security to cryptography, mobile application attacks to digital forensics, and from cyber security to blockchain. The goal of the book is to provide 360-degree view of cybersecurity to the readers which include cyber security issues, threats, vulnerabilities, novel idea, latest technique and technology, and mitigation of threats and attacks along with demonstration of practical applications. This book also highlights the latest development, challenges, methodologies as well as other emerging areas in this field. It brings current understanding of common Web vulnerabilities while maintaining awareness and knowledge of contemporary standards, practices, procedures, and methods of Open Web Application Security Project. It also expounds how to recover information after a cybercrime.
Book Synopsis Advances in Malware and Data-Driven Network Security by : Gupta, Brij B.
Download or read book Advances in Malware and Data-Driven Network Security written by Gupta, Brij B. and published by IGI Global. This book was released on 2021-11-12 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every day approximately three-hundred thousand to four-hundred thousand new malware are registered, many of them being adware and variants of previously known malware. Anti-virus companies and researchers cannot deal with such a deluge of malware – to analyze and build patches. The only way to scale the efforts is to build algorithms to enable machines to analyze malware and classify and cluster them to such a level of granularity that it will enable humans (or machines) to gain critical insights about them and build solutions that are specific enough to detect and thwart existing malware and generic-enough to thwart future variants. Advances in Malware and Data-Driven Network Security comprehensively covers data-driven malware security with an emphasis on using statistical, machine learning, and AI as well as the current trends in ML/statistical approaches to detecting, clustering, and classification of cyber-threats. Providing information on advances in malware and data-driven network security as well as future research directions, it is ideal for graduate students, academicians, faculty members, scientists, software developers, security analysts, computer engineers, programmers, IT specialists, and researchers who are seeking to learn and carry out research in the area of malware and data-driven network security.
Book Synopsis Machine Intelligence and Soft Computing by : Debnath Bhattacharyya
Download or read book Machine Intelligence and Soft Computing written by Debnath Bhattacharyya and published by Springer Nature. This book was released on 2021-01-20 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected papers presented at the International Conference on Machine Intelligence and Soft Computing (ICMISC 2020), held jointly by Vignan’s Institute of Information Technology, Visakhapatnam, India and VFSTR Deemed to be University, Guntur, AP, India during 03-04 September 2020. Topics covered in the book include the artificial neural networks and fuzzy logic, cloud computing, evolutionary algorithms and computation, machine learning, metaheuristics and swarm intelligence, neuro-fuzzy system, soft computing and decision support systems, soft computing applications in actuarial science, soft computing for database deadlock resolution, soft computing methods in engineering, and support vector machine.
Book Synopsis Implementing Enterprise Cybersecurity with Opensource Software and Standard Architecture by : Anand Handa
Download or read book Implementing Enterprise Cybersecurity with Opensource Software and Standard Architecture written by Anand Handa and published by CRC Press. This book was released on 2022-09-01 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many small and medium scale businesses cannot afford to procure expensive cybersecurity tools. In many cases, even after procurement, lack of a workforce with knowledge of the standard architecture of enterprise security, tools are often used ineffectively. The Editors have developed multiple projects which can help in developing cybersecurity solution architectures and the use of the right tools from the opensource software domain. This book has 8 chapters describing these projects in detail with recipes on how to use opensource tooling to obtain standard cyber defense and the ability to do self-penetration testing and vulnerability assessment. This book also demonstrates work related to malware analysis using machine learning and implementation of honeypots, network Intrusion Detection Systems in a security operation center environment. It is essential reading for cybersecurity professionals and advanced students.
Book Synopsis Advances in Information Communication Technology and Computing by : Vishal Goar
Download or read book Advances in Information Communication Technology and Computing written by Vishal Goar and published by Springer Nature. This book was released on 2022-05-09 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a collection of best selected research papers presented at the International Conference on Advances in Information Communication Technology and Computing (AICTC 2021), held in Government Engineering College Bikaner, Bikaner, India, during 20–21 December 2021. The book covers ICT-based approaches in the areas of ICT for energy efficiency, life cycle assessment of ICT, green IT, green information systems, environmental informatics, energy informatics, sustainable HCI or Artificial intelli computational sustainability.
Book Synopsis Advanced Data Mining and Applications by : Weitong Chen
Download or read book Advanced Data Mining and Applications written by Weitong Chen and published by Springer Nature. This book was released on 2022-11-23 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 13725 and 13726 constitutes the proceedings of the 18th International Conference on Advanced Data Mining and Applications, ADMA 2022, which took place in Brisbane, Queensland, Australia, in November 2022. The 72 papers presented in the proceedings were carefully reviewed and selected from 198 submissions. The contributions were organized in topical sections as follows: Finance and Healthcare; Web and IoT Applications; On-device Application; Other Applications; Pattern Mining; Graph Mining; Text Mining; Image, Multimedia and Time Series Data Mining; Classification, Clustering and Recommendation; Multi-objective, Optimization, Augmentation, and Database; and Others.
Book Synopsis Machine Learning for Cyber Security by : Preeti Malik
Download or read book Machine Learning for Cyber Security written by Preeti Malik and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-12-05 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows how machine learning (ML) methods can be used to enhance cyber security operations, including detection, modeling, monitoring as well as defense against threats to sensitive data and security systems. Filling an important gap between ML and cyber security communities, it discusses topics covering a wide range of modern and practical ML techniques, frameworks and tools.
Book Synopsis Handbook of Research on Machine Learning Techniques for Pattern Recognition and Information Security by : Dua, Mohit
Download or read book Handbook of Research on Machine Learning Techniques for Pattern Recognition and Information Security written by Dua, Mohit and published by IGI Global. This book was released on 2021-05-14 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: The artificial intelligence subset machine learning has become a popular technique in professional fields as many are finding new ways to apply this trending technology into their everyday practices. Two fields that have majorly benefited from this are pattern recognition and information security. The ability of these intelligent algorithms to learn complex patterns from data and attain new performance techniques has created a wide variety of uses and applications within the data security industry. There is a need for research on the specific uses machine learning methods have within these fields, along with future perspectives. The Handbook of Research on Machine Learning Techniques for Pattern Recognition and Information Security is a collection of innovative research on the current impact of machine learning methods within data security as well as its various applications and newfound challenges. While highlighting topics including anomaly detection systems, biometrics, and intrusion management, this book is ideally designed for industrial experts, researchers, IT professionals, network developers, policymakers, computer scientists, educators, and students seeking current research on implementing machine learning tactics to enhance the performance of information security.
Book Synopsis Information Security by : Willy Susilo
Download or read book Information Security written by Willy Susilo and published by Springer Nature. This book was released on 2020-11-24 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 23rd International Conference on Information Security, ISC 2020, held in Bali, Indonesia, in December 2020. The 23 full papers presented in this volume were carefully reviewed and selected from 87 submissions. The papers cover topics of research in theory and applications of information security, such as Security and privacy and Network security as well.
