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AI and Cyber Attacks: The Growing Threat of AI-Enhanced Hacking

AI and Cyber Attacks: The Growing Threat of AI-Enhanced Hacking PDF Author: AQEEL AHMED
Publisher: AQEEL AHMED
ISBN: 199881050X
Category : Computers
Languages : en
Pages : 100

Book Description
AI and Cyber Attacks: The Growing Threat of AI-Enhanced Hacking Introduction Artificial intelligence (AI) has transformed many industries, including cybersecurity. Rapid breakthroughs in artificial intelligence technology have created both opportunities and difficulties in the field of cybersecurity. While AI has enormous potential to improve security defenses and fight against cyber threats, it also poses major hazards when misused. Because of the confluence of AI and cyberattacks, a new breed of threats known as AI-enhanced hacking has emerged, which mixes AI algorithms and tactics with malicious intent. AI-enhanced hacking refers to hostile actors' use of AI and machine learning (ML) tools to increase the effectiveness, sophistication, and scope of cyberattacks. AI algorithms are being used by hackers to automate processes, boost attack success rates, elude detection, and circumvent security restrictions. Cybercriminals can substantially increase the effect and speed of their attacks by leveraging the capabilities of AI. For hackers, one of the most important benefits of AI is the capacity to launch more sophisticated and targeted attacks. AI systems can find vulnerabilities, build specialized attack methods, and adapt to changing protection mechanisms by analyzing massive volumes of data. Because of this sophistication, traditional security systems are finding it increasingly difficult to identify and resist AI-enhanced threats. AI algorithms can be used by hackers to undertake extensive reconnaissance, uncover system weaknesses, and launch precise and well-coordinated attacks. As a result, attack sophistication has increased, posing substantial problems for cybersecurity professionals. Furthermore, artificial intelligence enables hackers to automate many stages of an attack, from reconnaissance to exploitation and even post-exploitation activities. This automation enables attackers to undertake large-scale attacks, targeting several systems at the same time and improving their chances of success. Automated attacks present a big challenge to cybersecurity specialists, who must devise equally sophisticated protection systems to counter them. Hackers can save time and resources by automating their attacks while increasing their impact. Another significant benefit of AI for hackers is its ability to circumvent standard security measures and avoid discovery. In real-time, AI algorithms can evaluate trends, learn from previous attacks, and change defensive methods. Because of this adaptive behavior, attackers might go unnoticed for long periods of time, making it difficult for security analysts to identify and respond to threats quickly. AI-powered assaults can imitate legitimate user behavior, making it difficult to discern between legitimate and malicious activity. Hackers can extend their access to networks and collect critical information without alerting security measures by escaping detection. Another troubling element of AI-enhanced hacking is the weaponization of AI. As AI technology becomes more widely available, thieves can use them to develop stronger hacking tools. AI algorithms can be trained to generate convincing phishing emails, deepfake movies, and even replicate human behavior in order to circumvent multi-factor authentication systems. The weaponization of AI increases the potency of attacks and poses major hazards to individuals, organizations, and even governments. In the cybersecurity landscape, the potential for AI-powered assaults to deceive and manipulate users is becoming a significant worry. The growing threat of AI-enhanced hacking has necessitated the implementation of preventative measures to limit the hazards. To confront the shifting threat landscape, organizations and cybersecurity experts must adjust their protection measures. Advanced protection systems that use AI and machine learning can assist detect and respond to AI-enhanced threats more quickly, lessening the effect of possible breaches. AI-powered security systems can improve threat detection and response capabilities by monitoring network traffic, evaluating patterns, and recognizing anomalies in real-time. Collaboration between human expertise and AI technologies is also critical. AI can help cybersecurity professionals handle and analyze massive amounts of data, detect trends, and provide insights. Human specialists contribute critical thinking skills, contextual knowledge, and the capacity to make sound decisions in difficult situations. Organizations can develop a more effective security posture by combining human intuition and knowledge with AI's computational capabilities. In the development and deployment of Certainly! Ethical considerations are critical. There are various other factors to consider when it comes to AI and cyber-attacks, in addition to the ones described above. One critical issue is the continued need for AI-powered cybersecurity tool research and development. As AI-enhanced hacking techniques evolve, cybersecurity experts must stay on the cutting edge of technology. Continued research and development efforts can result in the development of creative technologies capable of detecting, preventing, and responding to AI-driven cyber-attacks. Collaboration and information sharing among cybersecurity specialists and companies are also critical. The cybersecurity community can collectively improve its ability to prevent AI-enhanced hacking by sharing knowledge, insights, and best practices. Collaborative initiatives such as information sharing platforms, industry conferences, and public-private partnerships can help to facilitate information flow and develop a collective defense against cyber threats. Furthermore, incorporating AI into threat intelligence can boost the ability to anticipate and respond to cyber-attacks dramatically. To identify prospective risks and deliver actionable insight, AI systems can scan enormous amounts of data, including previous attack patterns, new threats, and indicators of compromise. Organizations can proactively discover vulnerabilities, prioritize mitigation efforts, and improve incident response capabilities by employing AI in threat intelligence. End-user education and awareness are also critical in limiting the hazards of AI-enhanced hacking. Individuals must be educated on the risks posed by AI-driven cyber-attacks, such as phishing schemes, social engineering, and malware. Promoting cyber hygiene measures such as using strong passwords, being skeptical of questionable emails or links, and keeping software up to date can reduce the likelihood of falling victim to AI-powered assaults dramatically. Furthermore, legal frameworks and standards to control the development and deployment of AI technologies should be established. Governments and regulatory agencies can play an important role in establishing rules, verifying compliance, and encouraging the ethical use of AI in cybersecurity. These policies can address issues such as data privacy, algorithmic transparency, accountability, and ethical considerations, increasing trust in AI-powered cybersecurity solutions in the long run. AI has made important advances in a variety of fields, including cybersecurity. It does, however, introduce additional obstacles and threats, particularly in the form of AI-enhanced hacking. Organizations must adjust their protection methods and employ AI technology to identify, prevent, and respond to AI-driven assaults as they become more complex. Collaboration, continuing research, education, regulatory frameworks, and a team approach are critical in limiting risks and reaping the benefits of AI in cybersecurity. We can traverse the growing landscape of AI and cyber-attacks with confidence and resilience by remaining watchful, proactive, and always inventing. Artificial intelligence (AI) has surely altered various industries, including cybersecurity. The introduction of AI has created an enormous opportunity to strengthen security defenses against emerging threats. Organizations may improve their ability to detect and respond to threats in real time by leveraging the power of AI. However, the same qualities that make AI such a powerful asset in cybersecurity also offer major hazards when misused. Because of the convergence of AI and cyberattacks, a new species of risks known as AI-enhanced hacking has emerged, posing unprecedented challenges to the security landscape. AI-enhanced hacking refers to hostile actors' use of AI and machine learning techniques to increase the effectiveness, sophistication, and size of cyber-attacks. AI algorithms are being used by hackers to automate processes, boost attack success rates, elude detection, and circumvent security restrictions. This fusion of AI and hacking methodologies has significant ramifications for cybersecurity experts and companies. The implications of AI-enhanced hacking are wide-ranging and frightening. For starters, AI enables hackers to conduct more sophisticated attacks. AI systems can find vulnerabilities, build specialized attack methods, and adapt to changing protection mechanisms by analyzing massive volumes of data. Because of this sophistication, traditional security systems are finding it increasingly difficult to identify and resist AI-enhanced assaults successfully. Furthermore, AI enables unparalleled scale of automated attacks. AI algorithms can be used by hackers to automate many stages of an attack, from reconnaissance to exploitation and even post-exploitation. Because of this automation, attackers can target several systems at the same time, boosting their chances of success. The ability to launch automated attacks presents a big challenge for cybersecurity professionals, who must create similarly advanced protection measures to properly counter them. Another major problem is AI's ability to avoid discovery. AI algorithms are being used by hackers to detect trends, learn from previous attacks, and change defensive methods in real-time. Because of this adaptive behavior, attackers might go unnoticed for long periods of time, making it difficult for security analysts to identify and respond to threats quickly. Furthermore, the weaponization of AI increases the effectiveness of strikes while posing significant hazards. As AI technology becomes more widely available, thieves can use them to develop stronger hacking tools. AI algorithms can be trained to generate convincing phishing emails, deepfake movies, and even replicate human behavior in order to circumvent multi-factor authentication systems. The ability to weaponize AI raises the effect and possible harm caused by hacks dramatically. Several efforts can be made to reduce the hazards posed by AI-enhanced hacking. First and foremost, enterprises must invest in modern defense mechanisms that employ AI and machine learning. Organizations may monitor network traffic, analyze patterns, and detect anomalies in real time by using AI-powered security solutions. This proactive approach can assist in detecting and responding to attacks more quickly, limiting the effect of possible breaches. Furthermore, human-AI collaboration is critical in preventing AI-enhanced hacking. While AI is powerful, human expertise is also necessary. To increase threat intelligence and response, organizations should encourage collaboration between cybersecurity specialists and AI systems. A more effective defense posture can be built by combining human intuition and contextual knowledge with AI's computational skills. In tackling the issue of AI-enhanced hacking, ethical considerations and responsible use of AI are critical. Governments, organizations, and technology suppliers should collaborate to develop guidelines for the ethical use of AI in cybersecurity. Transparency, accountability, and privacy should be prioritized in AI development and deployment. As AI evolves at a rapid pace, continuous monitoring and training of AI systems is critical. To remain abreast of new assault strategies, regular assessments and upgrades are required. Organizations should also invest in employee training programs to educate users about the potential threats of AI-enhanced hacking, as well as how to spot and respond to them.

AI and Cyber Attacks: The Growing Threat of AI-Enhanced Hacking

AI and Cyber Attacks: The Growing Threat of AI-Enhanced Hacking PDF Author: AQEEL AHMED
Publisher: AQEEL AHMED
ISBN: 199881050X
Category : Computers
Languages : en
Pages : 100

Book Description
AI and Cyber Attacks: The Growing Threat of AI-Enhanced Hacking Introduction Artificial intelligence (AI) has transformed many industries, including cybersecurity. Rapid breakthroughs in artificial intelligence technology have created both opportunities and difficulties in the field of cybersecurity. While AI has enormous potential to improve security defenses and fight against cyber threats, it also poses major hazards when misused. Because of the confluence of AI and cyberattacks, a new breed of threats known as AI-enhanced hacking has emerged, which mixes AI algorithms and tactics with malicious intent. AI-enhanced hacking refers to hostile actors' use of AI and machine learning (ML) tools to increase the effectiveness, sophistication, and scope of cyberattacks. AI algorithms are being used by hackers to automate processes, boost attack success rates, elude detection, and circumvent security restrictions. Cybercriminals can substantially increase the effect and speed of their attacks by leveraging the capabilities of AI. For hackers, one of the most important benefits of AI is the capacity to launch more sophisticated and targeted attacks. AI systems can find vulnerabilities, build specialized attack methods, and adapt to changing protection mechanisms by analyzing massive volumes of data. Because of this sophistication, traditional security systems are finding it increasingly difficult to identify and resist AI-enhanced threats. AI algorithms can be used by hackers to undertake extensive reconnaissance, uncover system weaknesses, and launch precise and well-coordinated attacks. As a result, attack sophistication has increased, posing substantial problems for cybersecurity professionals. Furthermore, artificial intelligence enables hackers to automate many stages of an attack, from reconnaissance to exploitation and even post-exploitation activities. This automation enables attackers to undertake large-scale attacks, targeting several systems at the same time and improving their chances of success. Automated attacks present a big challenge to cybersecurity specialists, who must devise equally sophisticated protection systems to counter them. Hackers can save time and resources by automating their attacks while increasing their impact. Another significant benefit of AI for hackers is its ability to circumvent standard security measures and avoid discovery. In real-time, AI algorithms can evaluate trends, learn from previous attacks, and change defensive methods. Because of this adaptive behavior, attackers might go unnoticed for long periods of time, making it difficult for security analysts to identify and respond to threats quickly. AI-powered assaults can imitate legitimate user behavior, making it difficult to discern between legitimate and malicious activity. Hackers can extend their access to networks and collect critical information without alerting security measures by escaping detection. Another troubling element of AI-enhanced hacking is the weaponization of AI. As AI technology becomes more widely available, thieves can use them to develop stronger hacking tools. AI algorithms can be trained to generate convincing phishing emails, deepfake movies, and even replicate human behavior in order to circumvent multi-factor authentication systems. The weaponization of AI increases the potency of attacks and poses major hazards to individuals, organizations, and even governments. In the cybersecurity landscape, the potential for AI-powered assaults to deceive and manipulate users is becoming a significant worry. The growing threat of AI-enhanced hacking has necessitated the implementation of preventative measures to limit the hazards. To confront the shifting threat landscape, organizations and cybersecurity experts must adjust their protection measures. Advanced protection systems that use AI and machine learning can assist detect and respond to AI-enhanced threats more quickly, lessening the effect of possible breaches. AI-powered security systems can improve threat detection and response capabilities by monitoring network traffic, evaluating patterns, and recognizing anomalies in real-time. Collaboration between human expertise and AI technologies is also critical. AI can help cybersecurity professionals handle and analyze massive amounts of data, detect trends, and provide insights. Human specialists contribute critical thinking skills, contextual knowledge, and the capacity to make sound decisions in difficult situations. Organizations can develop a more effective security posture by combining human intuition and knowledge with AI's computational capabilities. In the development and deployment of Certainly! Ethical considerations are critical. There are various other factors to consider when it comes to AI and cyber-attacks, in addition to the ones described above. One critical issue is the continued need for AI-powered cybersecurity tool research and development. As AI-enhanced hacking techniques evolve, cybersecurity experts must stay on the cutting edge of technology. Continued research and development efforts can result in the development of creative technologies capable of detecting, preventing, and responding to AI-driven cyber-attacks. Collaboration and information sharing among cybersecurity specialists and companies are also critical. The cybersecurity community can collectively improve its ability to prevent AI-enhanced hacking by sharing knowledge, insights, and best practices. Collaborative initiatives such as information sharing platforms, industry conferences, and public-private partnerships can help to facilitate information flow and develop a collective defense against cyber threats. Furthermore, incorporating AI into threat intelligence can boost the ability to anticipate and respond to cyber-attacks dramatically. To identify prospective risks and deliver actionable insight, AI systems can scan enormous amounts of data, including previous attack patterns, new threats, and indicators of compromise. Organizations can proactively discover vulnerabilities, prioritize mitigation efforts, and improve incident response capabilities by employing AI in threat intelligence. End-user education and awareness are also critical in limiting the hazards of AI-enhanced hacking. Individuals must be educated on the risks posed by AI-driven cyber-attacks, such as phishing schemes, social engineering, and malware. Promoting cyber hygiene measures such as using strong passwords, being skeptical of questionable emails or links, and keeping software up to date can reduce the likelihood of falling victim to AI-powered assaults dramatically. Furthermore, legal frameworks and standards to control the development and deployment of AI technologies should be established. Governments and regulatory agencies can play an important role in establishing rules, verifying compliance, and encouraging the ethical use of AI in cybersecurity. These policies can address issues such as data privacy, algorithmic transparency, accountability, and ethical considerations, increasing trust in AI-powered cybersecurity solutions in the long run. AI has made important advances in a variety of fields, including cybersecurity. It does, however, introduce additional obstacles and threats, particularly in the form of AI-enhanced hacking. Organizations must adjust their protection methods and employ AI technology to identify, prevent, and respond to AI-driven assaults as they become more complex. Collaboration, continuing research, education, regulatory frameworks, and a team approach are critical in limiting risks and reaping the benefits of AI in cybersecurity. We can traverse the growing landscape of AI and cyber-attacks with confidence and resilience by remaining watchful, proactive, and always inventing. Artificial intelligence (AI) has surely altered various industries, including cybersecurity. The introduction of AI has created an enormous opportunity to strengthen security defenses against emerging threats. Organizations may improve their ability to detect and respond to threats in real time by leveraging the power of AI. However, the same qualities that make AI such a powerful asset in cybersecurity also offer major hazards when misused. Because of the convergence of AI and cyberattacks, a new species of risks known as AI-enhanced hacking has emerged, posing unprecedented challenges to the security landscape. AI-enhanced hacking refers to hostile actors' use of AI and machine learning techniques to increase the effectiveness, sophistication, and size of cyber-attacks. AI algorithms are being used by hackers to automate processes, boost attack success rates, elude detection, and circumvent security restrictions. This fusion of AI and hacking methodologies has significant ramifications for cybersecurity experts and companies. The implications of AI-enhanced hacking are wide-ranging and frightening. For starters, AI enables hackers to conduct more sophisticated attacks. AI systems can find vulnerabilities, build specialized attack methods, and adapt to changing protection mechanisms by analyzing massive volumes of data. Because of this sophistication, traditional security systems are finding it increasingly difficult to identify and resist AI-enhanced assaults successfully. Furthermore, AI enables unparalleled scale of automated attacks. AI algorithms can be used by hackers to automate many stages of an attack, from reconnaissance to exploitation and even post-exploitation. Because of this automation, attackers can target several systems at the same time, boosting their chances of success. The ability to launch automated attacks presents a big challenge for cybersecurity professionals, who must create similarly advanced protection measures to properly counter them. Another major problem is AI's ability to avoid discovery. AI algorithms are being used by hackers to detect trends, learn from previous attacks, and change defensive methods in real-time. Because of this adaptive behavior, attackers might go unnoticed for long periods of time, making it difficult for security analysts to identify and respond to threats quickly. Furthermore, the weaponization of AI increases the effectiveness of strikes while posing significant hazards. As AI technology becomes more widely available, thieves can use them to develop stronger hacking tools. AI algorithms can be trained to generate convincing phishing emails, deepfake movies, and even replicate human behavior in order to circumvent multi-factor authentication systems. The ability to weaponize AI raises the effect and possible harm caused by hacks dramatically. Several efforts can be made to reduce the hazards posed by AI-enhanced hacking. First and foremost, enterprises must invest in modern defense mechanisms that employ AI and machine learning. Organizations may monitor network traffic, analyze patterns, and detect anomalies in real time by using AI-powered security solutions. This proactive approach can assist in detecting and responding to attacks more quickly, limiting the effect of possible breaches. Furthermore, human-AI collaboration is critical in preventing AI-enhanced hacking. While AI is powerful, human expertise is also necessary. To increase threat intelligence and response, organizations should encourage collaboration between cybersecurity specialists and AI systems. A more effective defense posture can be built by combining human intuition and contextual knowledge with AI's computational skills. In tackling the issue of AI-enhanced hacking, ethical considerations and responsible use of AI are critical. Governments, organizations, and technology suppliers should collaborate to develop guidelines for the ethical use of AI in cybersecurity. Transparency, accountability, and privacy should be prioritized in AI development and deployment. As AI evolves at a rapid pace, continuous monitoring and training of AI systems is critical. To remain abreast of new assault strategies, regular assessments and upgrades are required. Organizations should also invest in employee training programs to educate users about the potential threats of AI-enhanced hacking, as well as how to spot and respond to them.

Mastering hacking with AI

Mastering hacking with AI PDF Author: Kris Hermans
Publisher: Cybellium Ltd
ISBN:
Category : Computers
Languages : en
Pages : 95

Book Description
In the rapidly evolving world of cybersecurity, the intersection of hacking and artificial intelligence (AI) has become an arena of immense potential. "Mastering Hacking with AI" by Kris Hermans is your comprehensive guide to harnessing the power of AI for ethical hacking purposes. This groundbreaking book takes you on a transformative journey, equipping you with the knowledge and skills to master the fusion of hacking and AI. Inside this groundbreaking book, you will: Explore the core principles of hacking and AI, including machine learning techniques, natural language processing, anomaly detection, and adversarial attacks, enabling you to develop advanced hacking strategies. Gain hands-on experience through real-world examples, step-by-step tutorials, and AI-driven tools, allowing you to apply AI techniques to identify vulnerabilities, automate penetration testing, and enhance threat intelligence. Understand the ethical implications of AI-driven hacking and learn how to responsibly use AI for cybersecurity purposes, adhering to legal and ethical frameworks. Stay ahead of the curve with discussions on emerging trends in AI and their impact on cybersecurity, such as AI-powered defences, deepfake detection, and autonomous threat hunting.

Cyber Defence in the Age of AI, Smart Societies and Augmented Humanity

Cyber Defence in the Age of AI, Smart Societies and Augmented Humanity PDF Author: Hamid Jahankhani
Publisher: Springer Nature
ISBN: 3030357465
Category : Computers
Languages : en
Pages : 445

Book Description
This publication highlights the fast-moving technological advancement and infiltration of Artificial Intelligence into society. Concepts of evolution of society through interconnectivity are explored, together with how the fusion of human and technological interaction leading to Augmented Humanity is fast becoming more than just an endemic phase, but a cultural phase shift to digital societies. It aims to balance both the positive progressive outlooks such developments bring with potential issues that may stem from innovation of this kind, such as the invasive procedures of bio hacking or ethical connotations concerning the usage of digital twins. This publication will also give the reader a good level of understanding on fundamental cyber defence principles, interactions with Critical National Infrastructure (CNI) and the Command, Control, Communications and Intelligence (C3I) decision-making framework. A detailed view of the cyber-attack landscape will be garnered; touching on the tactics, techniques and procedures used, red and blue teaming initiatives, cyber resilience and the protection of larger scale systems. The integration of AI, smart societies, the human-centric approach and Augmented Humanity is discernible in the exponential growth, collection and use of [big] data; concepts woven throughout the diversity of topics covered in this publication; which also discusses the privacy and transparency of data ownership, and the potential dangers of exploitation through social media. As humans are become ever more interconnected, with the prolificacy of smart wearable devices and wearable body area networks, the availability of and abundance of user data and metadata derived from individuals has grown exponentially. The notion of data ownership, privacy and situational awareness are now at the forefront in this new age.

Implications of Artificial Intelligence for Cybersecurity

Implications of Artificial Intelligence for Cybersecurity PDF Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309494508
Category : Computers
Languages : en
Pages : 99

Book Description
In recent years, interest and progress in the area of artificial intelligence (AI) and machine learning (ML) have boomed, with new applications vigorously pursued across many sectors. At the same time, the computing and communications technologies on which we have come to rely present serious security concerns: cyberattacks have escalated in number, frequency, and impact, drawing increased attention to the vulnerabilities of cyber systems and the need to increase their security. In the face of this changing landscape, there is significant concern and interest among policymakers, security practitioners, technologists, researchers, and the public about the potential implications of AI and ML for cybersecurity. The National Academies of Sciences, Engineering, and Medicine convened a workshop on March 12-13, 2019 to discuss and explore these concerns. This publication summarizes the presentations and discussions from the workshop.

Emerging Trends in ICT Security

Emerging Trends in ICT Security PDF Author: Leonidas Deligiannidis
Publisher: Elsevier Inc. Chapters
ISBN: 0128070641
Category : Computers
Languages : en
Pages : 650

Book Description
Every day, people interact with numerous computer systems, networks, and services that require the exchange of sensitive data. However, the Internet is a highly distributed system operated by many different entities and as such should not be trusted by end users. Users, whether consumers or businesses, retain no control over how their information is routed among the many networks that comprise the Internet. Therefore, there is a strong need for cryptographic protocols to authenticate, verify trust, and establish a secure channel for exchanging data. This chapter presents a series of projects and demonstrations for systems and networking professionals who want to increase their comprehension of security concepts and protocols. The material presented here is derived from existing courses taught by the authors in the areas of cryptography, network security, and wireless security.

AI in Cybersecurity

AI in Cybersecurity PDF Author: Leslie F. Sikos
Publisher: Springer
ISBN: 9783319988412
Category : Technology & Engineering
Languages : en
Pages : 0

Book Description
This book presents a collection of state-of-the-art AI approaches to cybersecurity and cyberthreat intelligence, offering strategic defense mechanisms for malware, addressing cybercrime, and assessing vulnerabilities to yield proactive rather than reactive countermeasures. The current variety and scope of cybersecurity threats far exceed the capabilities of even the most skilled security professionals. In addition, analyzing yesterday’s security incidents no longer enables experts to predict and prevent tomorrow’s attacks, which necessitates approaches that go far beyond identifying known threats. Nevertheless, there are promising avenues: complex behavior matching can isolate threats based on the actions taken, while machine learning can help detect anomalies, prevent malware infections, discover signs of illicit activities, and protect assets from hackers. In turn, knowledge representation enables automated reasoning over network data, helping achieve cybersituational awareness. Bringing together contributions by high-caliber experts, this book suggests new research directions in this critical and rapidly growing field.

Threatcasting

Threatcasting PDF Author: Brian David Johnson
Publisher: Springer Nature
ISBN: 303102575X
Category : Mathematics
Languages : en
Pages : 285

Book Description
Impending technological advances will widen an adversary’s attack plane over the next decade. Visualizing what the future will hold, and what new threat vectors could emerge, is a task that traditional planning mechanisms struggle to accomplish given the wide range of potential issues. Understanding and preparing for the future operating environment is the basis of an analytical method known as Threatcasting. It is a method that gives researchers a structured way to envision and plan for risks ten years in the future. Threatcasting uses input from social science, technical research, cultural history, economics, trends, expert interviews, and even a little science fiction to recognize future threats and design potential futures. During this human-centric process, participants brainstorm what actions can be taken to identify, track, disrupt, mitigate, and recover from the possible threats. Specifically, groups explore how to transform the future they desire into reality while avoiding an undesired future. The Threatcasting method also exposes what events could happen that indicate the progression toward an increasingly possible threat landscape. This book begins with an overview of the Threatcasting method with examples and case studies to enhance the academic foundation. Along with end-of-chapter exercises to enhance the reader’s understanding of the concepts, there is also a full project where the reader can conduct a mock Threatcasting on the topic of “the next biological public health crisis.” The second half of the book is designed as a practitioner’s handbook. It has three separate chapters (based on the general size of the Threatcasting group) that walk the reader through how to apply the knowledge from Part I to conduct an actual Threatcasting activity. This book will be useful for a wide audience (from student to practitioner) and will hopefully promote new dialogues across communities and novel developments in the area.

Research Methods for Cyber Security

Research Methods for Cyber Security PDF Author: Thomas W. Edgar
Publisher: Syngress
ISBN: 0128129301
Category : Computers
Languages : en
Pages : 428

Book Description
Research Methods for Cyber Security teaches scientific methods for generating impactful knowledge, validating theories, and adding critical rigor to the cyber security field. This book shows how to develop a research plan, beginning by starting research with a question, then offers an introduction to the broad range of useful research methods for cyber security research: observational, mathematical, experimental, and applied. Each research method chapter concludes with recommended outlines and suggested templates for submission to peer reviewed venues. This book concludes with information on cross-cutting issues within cyber security research. Cyber security research contends with numerous unique issues, such as an extremely fast environment evolution, adversarial behavior, and the merging of natural and social science phenomena. Research Methods for Cyber Security addresses these concerns and much more by teaching readers not only the process of science in the context of cyber security research, but providing assistance in execution of research as well. Presents research methods from a cyber security science perspective Catalyzes the rigorous research necessary to propel the cyber security field forward Provides a guided method selection for the type of research being conducted, presented in the context of real-world usage

Hacked Again

Hacked Again PDF Author: Scott N. Schober
Publisher: Hillcrest Publishing Group
ISBN: 0996902201
Category : Computers
Languages : en
Pages : 203

Book Description
Hacked Again details the ins and outs of cybersecurity expert and CEO of a top wireless security tech firm Scott Schober, as he struggles to understand: the motives and mayhem behind his being hacked. As a small business owner, family man and tech pundit, Scott finds himself leading a compromised life. By day, he runs a successful security company and reports on the latest cyber breaches in the hopes of offering solace and security tips to millions of viewers. But by night, Scott begins to realize his worst fears are only a hack away as he falls prey to an invisible enemy. When a mysterious hacker begins to steal thousands from his bank account, go through his trash and rake over his social media identity; Scott stands to lose everything he worked so hard for. But his precarious situation only fortifies Scott's position as a cybersecurity expert and also as a harbinger for the fragile security we all cherish in this digital life. Amidst the backdrop of major breaches such as Target and Sony, Scott shares tips and best practices for all consumers concerning email scams, password protection and social media overload: Most importantly, Scott shares his own story of being hacked repeatedly and bow he has come to realize that the only thing as important as his own cybersecurity is that of his readers and viewers. Part cautionary tale and part cyber self-help guide, Hacked Again probes deep into the dark web for truths and surfaces to offer best practices and share stories from an expert who has lived as both an enforcer and a victim in the world of cybersecurity. Book jacket.

Effective Model-Based Systems Engineering

Effective Model-Based Systems Engineering PDF Author: John M. Borky
Publisher: Springer
ISBN: 3319956698
Category : Technology & Engineering
Languages : en
Pages : 779

Book Description
This textbook presents a proven, mature Model-Based Systems Engineering (MBSE) methodology that has delivered success in a wide range of system and enterprise programs. The authors introduce MBSE as the state of the practice in the vital Systems Engineering discipline that manages complexity and integrates technologies and design approaches to achieve effective, affordable, and balanced system solutions to the needs of a customer organization and its personnel. The book begins with a summary of the background and nature of MBSE. It summarizes the theory behind Object-Oriented Design applied to complex system architectures. It then walks through the phases of the MBSE methodology, using system examples to illustrate key points. Subsequent chapters broaden the application of MBSE in Service-Oriented Architectures (SOA), real-time systems, cybersecurity, networked enterprises, system simulations, and prototyping. The vital subject of system and architecture governance completes the discussion. The book features exercises at the end of each chapter intended to help readers/students focus on key points, as well as extensive appendices that furnish additional detail in particular areas. The self-contained text is ideal for students in a range of courses in systems architecture and MBSE as well as for practitioners seeking a highly practical presentation of MBSE principles and techniques.