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2016 11th International Conference on Malicious and Unwanted Software (MALWARE) / / Institute of Electrical and Electronics Engineers
| 2016 11th International Conference on Malicious and Unwanted Software (MALWARE) / / Institute of Electrical and Electronics Engineers |
| Pubbl/distr/stampa | Piscataway : , : IEEE, , 2016 |
| Descrizione fisica | 1 online resource : illustrations |
| Disciplina | 005.8 |
| Soggetto topico |
Malware (Computer software)
Computer networks - Security measures Computer software |
| ISBN | 1-5090-4542-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | 2016 11th International Conference on Malicious and Unwanted Software |
| Record Nr. | UNISA-996279840203316 |
| Piscataway : , : IEEE, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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2016 11th International Conference on Malicious and Unwanted Software (MALWARE) / / Institute of Electrical and Electronics Engineers
| 2016 11th International Conference on Malicious and Unwanted Software (MALWARE) / / Institute of Electrical and Electronics Engineers |
| Pubbl/distr/stampa | Piscataway : , : IEEE, , 2016 |
| Descrizione fisica | 1 online resource : illustrations |
| Disciplina | 005.8 |
| Soggetto topico |
Malware (Computer software)
Computer networks - Security measures Computer software |
| ISBN | 1-5090-4542-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | 2016 11th International Conference on Malicious and Unwanted Software |
| Record Nr. | UNINA-9910172654803321 |
| Piscataway : , : IEEE, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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2018 13th International Conference on Malicious and Unwanted Software : 22-24 October 2018, Nantucket Island, Massachusetts, USA / / IEEE Computer Society
| 2018 13th International Conference on Malicious and Unwanted Software : 22-24 October 2018, Nantucket Island, Massachusetts, USA / / IEEE Computer Society |
| Pubbl/distr/stampa | Piscataway, New Jersey : , : Institute of Electrical and Electronics Engineers, , 2018 |
| Descrizione fisica | 1 online resource (166 pages) |
| Disciplina | 005.8 |
| Soggetto topico |
Malware (Computer software)
Computer networks - Security measures Computer software |
| ISBN | 1-7281-0155-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910313058303321 |
| Piscataway, New Jersey : , : Institute of Electrical and Electronics Engineers, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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2018 13th International Conference on Malicious and Unwanted Software : 22-24 October 2018, Nantucket Island, Massachusetts, USA / / IEEE Computer Society
| 2018 13th International Conference on Malicious and Unwanted Software : 22-24 October 2018, Nantucket Island, Massachusetts, USA / / IEEE Computer Society |
| Pubbl/distr/stampa | Piscataway, New Jersey : , : Institute of Electrical and Electronics Engineers, , 2018 |
| Descrizione fisica | 1 online resource (166 pages) |
| Disciplina | 005.8 |
| Soggetto topico |
Malware (Computer software)
Computer networks - Security measures Computer software |
| ISBN | 1-7281-0155-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996575287503316 |
| Piscataway, New Jersey : , : Institute of Electrical and Electronics Engineers, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Android malware / / Xuxian Jiang, Yajin Zhou
| Android malware / / Xuxian Jiang, Yajin Zhou |
| Autore | Jiang Xuxian |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | New York, : Springer, c2013 |
| Descrizione fisica | 1 online resource (xi, 44 pages) : illustrations (chiefly color) |
| Disciplina | 005.84 |
| Collana | SpringerBriefs in computer science |
| Soggetto topico |
Malware (Computer software)
Computer science Data protection Data encryption (Computer science) |
| ISBN | 1-4614-7394-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- A Survey of Android Malware -- Case Studies -- Discussion -- Additional Reading -- Summary. |
| Record Nr. | UNINA-9910437959003321 |
Jiang Xuxian
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| New York, : Springer, c2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Android malware detection and adversarial methods / / Weina Niu, Xiaosong Zhang, Ran Yan, and Jiacheng Gong
| Android malware detection and adversarial methods / / Weina Niu, Xiaosong Zhang, Ran Yan, and Jiacheng Gong |
| Autore | Niu Weina |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2024] |
| Descrizione fisica | 1 online resource (xiv, 190 pages) : illustrations |
| Altri autori (Persone) |
ZhangXiaosong <1968->
YanRan GongJiacheng |
| Soggetto topico | Malware (Computer software) |
| ISBN | 981-9714-59-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Foreword -- Preface -- Acknowledgments -- Contents -- Part I The Overview of Android Malware Detection -- 1 Introduction of Android Malware Detection -- 1.1 Android Malware Family -- 1.1.1 Trojan Horse -- 1.1.2 Viruses -- 1.1.3 The Back Door -- 1.1.4 Zombies -- 1.1.5 Espionage -- 1.1.6 Intimidation -- 1.1.7 Extortion -- 1.1.8 Advertising -- 1.1.9 Tracking -- 1.2 History of Android Malware Detection -- 1.3 Android Malware Detection Overview -- 1.4 Challenges and Apps of Android Malware Detection -- 1.5 Domestic and International Android Malware Detection -- 1.5.1 Android Malware Detection Method Based on Static Analysis -- 1.5.2 Android Malware Detection Method Based on Dynamic Analysis -- 1.5.3 Android Malware Detection Method Based on Hybrid Analysis -- 1.6 Chapter Summary -- References -- Part II The General Android Malware Detection Method -- 2 Feature Code Based Android Malware Detection Method -- 2.1 Detection Based on Traditional Feature Codes -- 2.1.1 Introduction -- 2.1.2 DroidAnalyzer: A Case Study in Android Malware Analysis -- 2.1.2.1 Suspicious Android APIs and Keywords 3 -- 2.1.2.2 Main Algorithm of DroidAnalyzer -- 2.2 Detection Based on Semantic Feature Codes -- 2.2.1 Introduction -- 2.2.2 DroidNative: A Case Study in Android Malware Analysis -- 2.2.2.1 Static Analysis in DroidNative -- 2.2.2.2 System Design and Implementation -- 2.3 Chapter Summary -- References -- 3 Behavior-Based Detection Method for Android Malware -- 3.1 Privacy Disclosure -- 3.2 Permission Escalation -- 3.2.1 Permission Escalation Method -- 3.2.2 Authorization Based on Configuration Files -- 3.2.3 Code Analysis -- 3.2.4 Taint Analysis -- 3.3 Machine Learning Technology and Malicious Behavior of Android Software -- 3.4 Chapter Summary -- References -- 4 AI-Based Android Malware Detection Methods.
4.1 Detection Based on Permissions, APIs, and Components -- 4.1.1 Permissions in Android System -- 4.1.1.1 Permissions in Android System -- 4.1.1.2 Overview of Permission-Based Detection Methods -- 4.1.2 Detection Based on API -- 4.1.3 Component-Based Detection -- 4.1.3.1 Components of an Application -- 4.1.3.2 Overview of Component-Based Detection Methods -- 4.1.4 Specific Case: Drebin -- 4.1.4.1 Static Analysis of Applications -- 4.1.4.2 Embedding in Vector Space -- 4.1.4.3 Learning-Based Detection -- 4.1.4.4 Explanation -- 4.2 Detection Anchored in Dynamic Runtime Features -- 4.2.1 Dynamic Analysis and Runtime Features -- 4.2.2 Overview of Detection Methods Based on Dynamic Runtime Features -- 4.2.3 Specific Case: EnDroid -- 4.2.3.1 Training Phase -- 4.2.3.2 Detection Phase -- 4.3 Detection Through Semantic Code Analysis -- 4.3.1 Dalvik Bytecode -- 4.3.2 Overview of Code Semantic-Based Detection Methods -- 4.3.3 Specific Case: MviiDroid -- 4.3.3.1 Static Analysis Phase -- 4.3.3.2 Feature Generation Phase -- 4.3.3.3 Model Training Phase -- 4.4 Detection via Image Analysis -- 4.4.1 Overview of Image-Based Detection Methods -- 4.4.2 Specific Case: R2-D2 -- 4.5 Detection Through Graph Analysis -- 4.5.1 Overview of Homogeneous Graph-Based Detection Methods -- 4.5.2 Overview of Heterogeneous Graph-Based Detection Methods -- 4.5.3 Case Study: HAWK -- 4.5.3.1 Feature Engineering -- 4.5.3.2 Constructing Heterogeneous Information Network (HIN) -- 4.5.3.3 Constructing Application Graph from HIN -- 4.6 Chapter Summary -- References -- Part III The Adversarial Method for Android Malware Detection -- 5 Static Adversarial Method -- 5.1 Static Obfuscation -- 5.1.1 Code Obfuscation -- 5.1.2 Resource Obfuscation -- 5.1.3 Manifest File Obfuscation -- 5.1.4 Control Flow Obfuscation -- 5.2 Common APK Static Obfuscation Tools -- 5.2.1 Obfuscapk -- 5.2.2 ProGuard. 5.2.3 DexGuard -- 5.2.4 Allatori -- 5.2.5 DashO -- 5.2.6 Bangcle -- 5.2.7 Arxan -- 5.2.8 Comparative Analysis -- 5.3 Research on Static Obfuscation -- 5.3.1 Detection Methods Based on New Features -- 5.3.1.1 Static Detection Based on Perceptual Hashing -- 5.3.1.2 Static Detection Based on Semantic Feature Set -- 5.3.1.3 Static Detection Based on Static Data Streams -- 5.3.1.4 Static Detection Based on Grayscale Images -- 5.3.1.5 Static Detection Based on Permission Pairs -- 5.3.1.6 Static Detection Based on Static Sensitive Subgraphs -- 5.3.1.7 Static Detection Based on Malicious URLs -- 5.3.2 Detection Method Based on Binding Method -- 5.3.2.1 Static Detection Combined with Dynamic -- 5.3.2.2 Static Detection Combined with Machine Learning -- 5.3.2.3 Static Detection Combined with Deep Learning -- 5.4 Chapter Summary -- References -- 6 Dynamic Adversarial Method in Android Malware -- 6.1 Automatic Dynamic Analysis Evasion -- 6.1.1 Detection Dependent -- 6.1.1.1 Fingerprint -- 6.1.1.2 Reverse Turing Test -- 6.1.1.3 Target -- 6.1.2 Detection Independent -- 6.1.2.1 Stalling -- 6.1.2.2 Trigger-Based -- 6.1.2.3 Fileless Attack -- 6.2 Manual Dynamic Analysis Evasion -- 6.2.1 Direct Detection -- 6.2.1.1 Read PEB -- 6.2.1.2 Breakpoint Query -- 6.2.1.3 System Artifacts -- 6.2.1.4 Parent Process Detection -- 6.2.2 Deductive Detection -- 6.2.2.1 Trap -- 6.2.2.2 Time-Based Detection -- 6.2.3 Debugger Evasion -- 6.2.3.1 Control Flow Manipulation -- 6.2.3.2 Lockout Evasion -- 6.2.3.3 Debugger Identification -- 6.2.3.4 Fileless Malware -- 6.3 Related Research About Dynamic Analysis Evasion -- 6.3.1 Research About Improving Sandbox -- 6.3.1.1 The Droid is in the Details: Environment-Aware Evasion of Android Sandboxes -- 6.3.1.2 Morpheus: Automatically Generating Heuristics to Detect Android Emulators -- 6.3.2 Research About Detecting Dynamic Evasion. 6.3.2.1 CamoDroid: An Android App Analysis Environment Resilient Against Sandbox Evasion -- 6.3.2.2 Lumus: Dynamically Uncovering Evasive Android apps -- 6.4 Chapter Summary -- References -- 7 AI-Based Adversarial Method in Android -- 7.1 Introduction to Adversarial Examples -- 7.2 Classification of Adversarial Example Generation Methods -- 7.2.1 Gradient-Based Attacks -- 7.2.2 Optimization-Based Attacks -- 7.2.3 GAN-Based Attacks -- 7.2.4 Domain-Specific Attacks (Audio, Images, Text, etc.) -- 7.3 Black-Box Attacks -- 7.3.1 Introduction to Black-Box Attacks -- 7.3.2 Common Black-Box Attack Methods -- 7.3.3 Transfer Learning-Based Black-Box Attacks -- 7.3.4 Meta-Model Based Black-Box Attacks -- 7.3.5 Query-Based Attacks -- 7.3.6 Optimization-Based Attacks -- 7.4 White-Box Attacks -- 7.4.1 Optimization-Based Attacks -- 7.4.1.1 C& -- W Attack -- 7.4.1.2 PGD Attack -- 7.4.2 Gradient-Based Attacks -- 7.4.2.1 FGSM Attack -- 7.4.2.2 BIM Attack -- 7.4.3 App of Adversarial Attacks in Malware Detection -- 7.5 Chapter Summary -- References -- Part IV The Future Trends of Android Malware Detection -- 8 Future Trends in Android Malware Detection -- 8.1 Machine Learning And Deep Learning Techniques -- 8.1.1 Overview of Machine Learning and Deep Learning for Android Malware Detection -- 8.1.2 Challenges Faced -- 8.2 Integrated Solutions -- 8.2.1 Challenges Faced -- 8.3 Blockchain Technology -- 8.3.1 Introduction to Blockchain Technology -- 8.3.2 Examples of Blockchain Technology in the Field of Android Malware Detection -- 8.4 Hardware Technology -- 8.4.1 Advantages of Hardware Technology -- 8.4.2 Challenges to Hardware Technology -- 8.4.3 Examples of Hardware Technologies Applied in the Field of Android Malware Detection -- 8.5 BPF Technology -- 8.5.1 Development of BPF Technology -- 8.5.2 eBPF Technology Overview. 8.5.3 Examples of BPF Techniques in the Field of Android Malware Detection -- 8.6 Chapter Summary -- References. |
| Record Nr. | UNINA-9910864193603321 |
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Niu Weina
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| Singapore : , : Springer, , [2024] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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The art of memory forensics : detecting malware and threats in Windows, Linux, and Mac Memory / / Michael Hale Ligh [and four others]
| The art of memory forensics : detecting malware and threats in Windows, Linux, and Mac Memory / / Michael Hale Ligh [and four others] |
| Pubbl/distr/stampa | Indianapolis, Indiana : , : Wiley, , 2014 |
| Descrizione fisica | xxiii, 886p. ; : ill |
| Disciplina | 005.84 |
| Soggetto topico |
Malware (Computer software)
Computer security |
| ISBN | 9781118825044 : (ebk : EbookCentral) |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910786622903321 |
| Indianapolis, Indiana : , : Wiley, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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The art of memory forensics : detecting malware and threats in Windows, Linux, and Mac Memory / / Michael Hale Ligh [and four others]
| The art of memory forensics : detecting malware and threats in Windows, Linux, and Mac Memory / / Michael Hale Ligh [and four others] |
| Pubbl/distr/stampa | Indianapolis, Indiana : , : Wiley, , 2014 |
| Descrizione fisica | xxiii, 886p. ; : ill |
| Disciplina | 005.84 |
| Soggetto topico |
Malware (Computer software)
Computer security |
| ISBN | 9781118825044 : (ebk : EbookCentral) |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910824452103321 |
| Indianapolis, Indiana : , : Wiley, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Automatic malware analysis : an emulator based approach / / Heng Yin, Dawn Song
| Automatic malware analysis : an emulator based approach / / Heng Yin, Dawn Song |
| Autore | Yin Heng |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | New York, : Springer, 2013 |
| Descrizione fisica | 1 online resource (82 p.) |
| Disciplina | 005.8 |
| Altri autori (Persone) | SongDawn |
| Collana | SpringerBriefs in computer science |
| Soggetto topico | Malware (Computer software) |
| ISBN |
1-283-62478-8
9786613937230 1-4614-5523-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Dynamic Binary Analysis Platform -- Hidden Code Extraction -- Privacy-breaching Behavior Analysis -- Hooking Behavior Analysis -- Analysis of Trigger Conditions and Hidden Behaviors -- Concluding Remarks. |
| Record Nr. | UNINA-9910437578803321 |
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Yin Heng
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| New York, : Springer, 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Best practices for continuity of operations (handling destructive malware) / / by National Protection and Programs Directorate, Department of Homeland Security
| Best practices for continuity of operations (handling destructive malware) / / by National Protection and Programs Directorate, Department of Homeland Security |
| Pubbl/distr/stampa | [Washington, D.C.] : , : Homeland Security, , 2018 |
| Descrizione fisica | 1 online resource (6 unnumbered pages) |
| Soggetto topico |
Malware (Computer software)
Computer networks - Security measures Hacking - Prevention |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Best practices for continuity of operations |
| Record Nr. | UNINA-9910715044903321 |
| [Washington, D.C.] : , : Homeland Security, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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