Malware science: a comprehensive guide to detection, analysis, and compliance
Unlock the secrets of malware data science with cutting-edge techniques, AI-driven analysis, and international compliance standards to stay ahead of the ever-evolving cyber threat landscape Key Features Get introduced to three primary AI tactics used in malware and detection Leverage data science to...
Gespeichert in:
1. Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Birmingham ; Mumbai
Packt Publishing
December 2023
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Schlagworte: | |
Online-Zugang: | FHD01 |
Zusammenfassung: | Unlock the secrets of malware data science with cutting-edge techniques, AI-driven analysis, and international compliance standards to stay ahead of the ever-evolving cyber threat landscape Key Features Get introduced to three primary AI tactics used in malware and detection Leverage data science tools to combat critical cyber threats Understand regulatory requirements for using AI in cyber threat management Purchase of the print or Kindle book includes a free PDF eBook Book Description In today's world full of online threats, the complexity of harmful software presents a significant challenge for detection and analysis. This insightful guide will teach you how to apply the principles of data science to online security, acting as both an educational resource and a practical manual for everyday use. |
Beschreibung: | 1 Online-Ressource (xviii, 211 Seiten) |
ISBN: | 9781804615706 |
Internformat
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505 | 8 | |a Cover -- Title Page -- Copyright and Credits -- Dedication -- Foreword -- What the experts say -- Contributors -- Table of Contents -- Preface -- Part 1- Introduction -- Chapter 1: Malware Science Life Cycle Overview -- Combining malware -- Worms and Trojans combination -- Ransomware and spyware combination -- Macro malware and ransomware -- Managing malware -- Collection -- Analysis -- Detection -- Prevention -- Mitigation -- Reporting -- Summary -- Chapter 2: An Overview of the International History of Cyber Malware Impacts -- The evolution of cyber threats and malware | |
505 | 8 | |a Impacts on international relations and security -- Impacts on the economy and cybercrime -- The future of malware -- Expanded viewpoint on the impacts on international relations and security -- Expansion on cybercrime impacts on the general economy -- Direct financial impacts of malware -- a global overview -- Ransomware's global economic impact -- a continental overview -- Ransomware's economic impact in North America -- a deeper look -- Ransomware's economic impact in Asia -- a detailed examination -- Ransomware's economic impact in Africa -- an in-depth analysis | |
505 | 8 | |a Ransomware's economic impact in South America -- an extensive exploration -- Economic impacts versus socio-economic impacts -- Ransomware attacks and their impact on employment -- an in-depth perspective -- Ransomware attacks and their impact on public services -- an elaborate examination -- Ransomware and inequality -- a closer look at the impact on small businesses -- Policy, regulations, and their downstream impact on smaller businesses and public services -- Regulatory changes due to malware impacts on small and mid-scale businesses -- A deeper dive into the operational challenges | |
505 | 8 | |a Translating operational challenges into increased cost -- Expansion of economic and socio-economic impacts on key industries globally -- Key downstream impacts on key industries globally -- The use of AI systems with malware -- Cybersecurity, malware, and the socio-economic fabric -- Summary -- Part 2 -- The Current State of Key Malware Science AI Technologies -- Chapter 3: Topological Data Analysis for Malware Detection and Analysis -- The mathematics of space and continuous transformations -- A deeper dive into the "shape of the data" -- How TDA creates a multi-dimensional data representation | |
505 | 8 | |a Transforming a malware binary into a topological space -- Homology -- Persistence homology distinguishes meaningful patterns from random data fluctuations -- Improving detection algorithms to predict the behavior of new malware -- TDA -- comparing and contrasting the persistence diagrams of different software -- Using malware persistence diagrams to classify unknown software -- Persistence homology -- filtering noise to find meaningful patterns -- Classifying unknown malware with characteristic persistent features -- Leveraging classification to manage threat response | |
505 | 8 | |a A deeper dive -- employing TDA for threat management | |
520 | |a Unlock the secrets of malware data science with cutting-edge techniques, AI-driven analysis, and international compliance standards to stay ahead of the ever-evolving cyber threat landscape Key Features Get introduced to three primary AI tactics used in malware and detection Leverage data science tools to combat critical cyber threats Understand regulatory requirements for using AI in cyber threat management Purchase of the print or Kindle book includes a free PDF eBook Book Description In today's world full of online threats, the complexity of harmful software presents a significant challenge for detection and analysis. This insightful guide will teach you how to apply the principles of data science to online security, acting as both an educational resource and a practical manual for everyday use. | ||
650 | 4 | |a Malware (Computer software) | |
650 | 4 | |a Computer security | |
650 | 4 | |a Logiciels malveillants | |
650 | 4 | |a Sécurité informatique | |
776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 978-1-80461-864-6 |
912 | |a ZDB-30-PQE | ||
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author | Molinari, Shane |
author_facet | Molinari, Shane |
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bvnumber | BV049521214 |
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contents | Cover -- Title Page -- Copyright and Credits -- Dedication -- Foreword -- What the experts say -- Contributors -- Table of Contents -- Preface -- Part 1- Introduction -- Chapter 1: Malware Science Life Cycle Overview -- Combining malware -- Worms and Trojans combination -- Ransomware and spyware combination -- Macro malware and ransomware -- Managing malware -- Collection -- Analysis -- Detection -- Prevention -- Mitigation -- Reporting -- Summary -- Chapter 2: An Overview of the International History of Cyber Malware Impacts -- The evolution of cyber threats and malware Impacts on international relations and security -- Impacts on the economy and cybercrime -- The future of malware -- Expanded viewpoint on the impacts on international relations and security -- Expansion on cybercrime impacts on the general economy -- Direct financial impacts of malware -- a global overview -- Ransomware's global economic impact -- a continental overview -- Ransomware's economic impact in North America -- a deeper look -- Ransomware's economic impact in Asia -- a detailed examination -- Ransomware's economic impact in Africa -- an in-depth analysis Ransomware's economic impact in South America -- an extensive exploration -- Economic impacts versus socio-economic impacts -- Ransomware attacks and their impact on employment -- an in-depth perspective -- Ransomware attacks and their impact on public services -- an elaborate examination -- Ransomware and inequality -- a closer look at the impact on small businesses -- Policy, regulations, and their downstream impact on smaller businesses and public services -- Regulatory changes due to malware impacts on small and mid-scale businesses -- A deeper dive into the operational challenges Translating operational challenges into increased cost -- Expansion of economic and socio-economic impacts on key industries globally -- Key downstream impacts on key industries globally -- The use of AI systems with malware -- Cybersecurity, malware, and the socio-economic fabric -- Summary -- Part 2 -- The Current State of Key Malware Science AI Technologies -- Chapter 3: Topological Data Analysis for Malware Detection and Analysis -- The mathematics of space and continuous transformations -- A deeper dive into the "shape of the data" -- How TDA creates a multi-dimensional data representation Transforming a malware binary into a topological space -- Homology -- Persistence homology distinguishes meaningful patterns from random data fluctuations -- Improving detection algorithms to predict the behavior of new malware -- TDA -- comparing and contrasting the persistence diagrams of different software -- Using malware persistence diagrams to classify unknown software -- Persistence homology -- filtering noise to find meaningful patterns -- Classifying unknown malware with characteristic persistent features -- Leveraging classification to manage threat response A deeper dive -- employing TDA for threat management |
ctrlnum | (OCoLC)1422408676 (DE-599)BVBBV049521214 |
format | Electronic eBook |
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id | DE-604.BV049521214 |
illustrated | Not Illustrated |
index_date | 2024-07-03T23:25:02Z |
indexdate | 2024-07-10T10:09:37Z |
institution | BVB |
isbn | 9781804615706 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034867058 |
oclc_num | 1422408676 |
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owner | DE-1050 |
owner_facet | DE-1050 |
physical | 1 Online-Ressource (xviii, 211 Seiten) |
psigel | ZDB-30-PQE ZDB-30-PQE FHD01_PQE_Kauf |
publishDate | 2023 |
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publisher | Packt Publishing |
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spelling | Molinari, Shane Verfasser aut Malware science a comprehensive guide to detection, analysis, and compliance Shane Molinari Birmingham ; Mumbai Packt Publishing December 2023 1 Online-Ressource (xviii, 211 Seiten) txt rdacontent c rdamedia cr rdacarrier Cover -- Title Page -- Copyright and Credits -- Dedication -- Foreword -- What the experts say -- Contributors -- Table of Contents -- Preface -- Part 1- Introduction -- Chapter 1: Malware Science Life Cycle Overview -- Combining malware -- Worms and Trojans combination -- Ransomware and spyware combination -- Macro malware and ransomware -- Managing malware -- Collection -- Analysis -- Detection -- Prevention -- Mitigation -- Reporting -- Summary -- Chapter 2: An Overview of the International History of Cyber Malware Impacts -- The evolution of cyber threats and malware Impacts on international relations and security -- Impacts on the economy and cybercrime -- The future of malware -- Expanded viewpoint on the impacts on international relations and security -- Expansion on cybercrime impacts on the general economy -- Direct financial impacts of malware -- a global overview -- Ransomware's global economic impact -- a continental overview -- Ransomware's economic impact in North America -- a deeper look -- Ransomware's economic impact in Asia -- a detailed examination -- Ransomware's economic impact in Africa -- an in-depth analysis Ransomware's economic impact in South America -- an extensive exploration -- Economic impacts versus socio-economic impacts -- Ransomware attacks and their impact on employment -- an in-depth perspective -- Ransomware attacks and their impact on public services -- an elaborate examination -- Ransomware and inequality -- a closer look at the impact on small businesses -- Policy, regulations, and their downstream impact on smaller businesses and public services -- Regulatory changes due to malware impacts on small and mid-scale businesses -- A deeper dive into the operational challenges Translating operational challenges into increased cost -- Expansion of economic and socio-economic impacts on key industries globally -- Key downstream impacts on key industries globally -- The use of AI systems with malware -- Cybersecurity, malware, and the socio-economic fabric -- Summary -- Part 2 -- The Current State of Key Malware Science AI Technologies -- Chapter 3: Topological Data Analysis for Malware Detection and Analysis -- The mathematics of space and continuous transformations -- A deeper dive into the "shape of the data" -- How TDA creates a multi-dimensional data representation Transforming a malware binary into a topological space -- Homology -- Persistence homology distinguishes meaningful patterns from random data fluctuations -- Improving detection algorithms to predict the behavior of new malware -- TDA -- comparing and contrasting the persistence diagrams of different software -- Using malware persistence diagrams to classify unknown software -- Persistence homology -- filtering noise to find meaningful patterns -- Classifying unknown malware with characteristic persistent features -- Leveraging classification to manage threat response A deeper dive -- employing TDA for threat management Unlock the secrets of malware data science with cutting-edge techniques, AI-driven analysis, and international compliance standards to stay ahead of the ever-evolving cyber threat landscape Key Features Get introduced to three primary AI tactics used in malware and detection Leverage data science tools to combat critical cyber threats Understand regulatory requirements for using AI in cyber threat management Purchase of the print or Kindle book includes a free PDF eBook Book Description In today's world full of online threats, the complexity of harmful software presents a significant challenge for detection and analysis. This insightful guide will teach you how to apply the principles of data science to online security, acting as both an educational resource and a practical manual for everyday use. Malware (Computer software) Computer security Logiciels malveillants Sécurité informatique Erscheint auch als Druck-Ausgabe 978-1-80461-864-6 |
spellingShingle | Molinari, Shane Malware science a comprehensive guide to detection, analysis, and compliance Cover -- Title Page -- Copyright and Credits -- Dedication -- Foreword -- What the experts say -- Contributors -- Table of Contents -- Preface -- Part 1- Introduction -- Chapter 1: Malware Science Life Cycle Overview -- Combining malware -- Worms and Trojans combination -- Ransomware and spyware combination -- Macro malware and ransomware -- Managing malware -- Collection -- Analysis -- Detection -- Prevention -- Mitigation -- Reporting -- Summary -- Chapter 2: An Overview of the International History of Cyber Malware Impacts -- The evolution of cyber threats and malware Impacts on international relations and security -- Impacts on the economy and cybercrime -- The future of malware -- Expanded viewpoint on the impacts on international relations and security -- Expansion on cybercrime impacts on the general economy -- Direct financial impacts of malware -- a global overview -- Ransomware's global economic impact -- a continental overview -- Ransomware's economic impact in North America -- a deeper look -- Ransomware's economic impact in Asia -- a detailed examination -- Ransomware's economic impact in Africa -- an in-depth analysis Ransomware's economic impact in South America -- an extensive exploration -- Economic impacts versus socio-economic impacts -- Ransomware attacks and their impact on employment -- an in-depth perspective -- Ransomware attacks and their impact on public services -- an elaborate examination -- Ransomware and inequality -- a closer look at the impact on small businesses -- Policy, regulations, and their downstream impact on smaller businesses and public services -- Regulatory changes due to malware impacts on small and mid-scale businesses -- A deeper dive into the operational challenges Translating operational challenges into increased cost -- Expansion of economic and socio-economic impacts on key industries globally -- Key downstream impacts on key industries globally -- The use of AI systems with malware -- Cybersecurity, malware, and the socio-economic fabric -- Summary -- Part 2 -- The Current State of Key Malware Science AI Technologies -- Chapter 3: Topological Data Analysis for Malware Detection and Analysis -- The mathematics of space and continuous transformations -- A deeper dive into the "shape of the data" -- How TDA creates a multi-dimensional data representation Transforming a malware binary into a topological space -- Homology -- Persistence homology distinguishes meaningful patterns from random data fluctuations -- Improving detection algorithms to predict the behavior of new malware -- TDA -- comparing and contrasting the persistence diagrams of different software -- Using malware persistence diagrams to classify unknown software -- Persistence homology -- filtering noise to find meaningful patterns -- Classifying unknown malware with characteristic persistent features -- Leveraging classification to manage threat response A deeper dive -- employing TDA for threat management Malware (Computer software) Computer security Logiciels malveillants Sécurité informatique |
title | Malware science a comprehensive guide to detection, analysis, and compliance |
title_auth | Malware science a comprehensive guide to detection, analysis, and compliance |
title_exact_search | Malware science a comprehensive guide to detection, analysis, and compliance |
title_exact_search_txtP | Malware science a comprehensive guide to detection, analysis, and compliance |
title_full | Malware science a comprehensive guide to detection, analysis, and compliance Shane Molinari |
title_fullStr | Malware science a comprehensive guide to detection, analysis, and compliance Shane Molinari |
title_full_unstemmed | Malware science a comprehensive guide to detection, analysis, and compliance Shane Molinari |
title_short | Malware science |
title_sort | malware science a comprehensive guide to detection analysis and compliance |
title_sub | a comprehensive guide to detection, analysis, and compliance |
topic | Malware (Computer software) Computer security Logiciels malveillants Sécurité informatique |
topic_facet | Malware (Computer software) Computer security Logiciels malveillants Sécurité informatique |
work_keys_str_mv | AT molinarishane malwarescienceacomprehensiveguidetodetectionanalysisandcompliance |