Ai Driven Cybersecurity And Threat Intelligence
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Ai Driven Cybersecurity Andthreat Intelligence
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Author : Iqbal H. Sarker
language : en
Publisher: Springer Nature
Release Date :
Ai Driven Cybersecurity Andthreat Intelligence written by Iqbal H. Sarker and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Ai Driven Cybersecurity And Threat Intelligence
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Author : Iqbal H. Sarker
language : en
Publisher: Springer
Release Date : 2024-04-14
Ai Driven Cybersecurity And Threat Intelligence written by Iqbal H. Sarker and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-14 with Computers categories.
This book explores the dynamics of how AI (Artificial Intelligence) technology intersects with cybersecurity challenges and threat intelligence as they evolve. Integrating AI into cybersecurity not only offers enhanced defense mechanisms, but this book introduces a paradigm shift illustrating how one conceptualize, detect and mitigate cyber threats. An in-depth exploration of AI-driven solutions is presented, including machine learning algorithms, data science modeling, generative AI modeling, threat intelligence frameworks and Explainable AI (XAI) models. As a roadmap or comprehensive guide to leveraging AI/XAI to defend digital ecosystems against evolving cyber threats, this book provides insights, modeling, real-world applications and research issues. Throughout this journey, the authors discover innovation, challenges, and opportunities. It provides a holistic perspective on the transformative role of AI in securing the digital world. Overall, the use of AI can transform the way one detects, responds and defends against threats, by enabling proactive threat detection, rapid response and adaptive defense mechanisms. AI-driven cybersecurity systems excel at analyzing vast datasets rapidly, identifying patterns that indicate malicious activities, detecting threats in real time as well as conducting predictive analytics for proactive solution. Moreover, AI enhances the ability to detect anomalies, predict potential threats, and respond swiftly, preventing risks from escalated. As cyber threats become increasingly diverse and relentless, incorporating AI/XAI into cybersecurity is not just a choice, but a necessity for improving resilience and staying ahead of ever-changing threats. This book targets advanced-level students in computer science as a secondary textbook. Researchers and industry professionals working in various areas, such as Cyber AI, Explainable and Responsible AI, Human-AI Collaboration, Automation and Intelligent Systems, Adaptive and Robust Security Systems, Cybersecurity Data Science and Data-Driven Decision Making will also find this book useful as reference book.
Ai Driven Cyber Security
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Author : S. R. Jena
language : en
Publisher: Scholars' Press
Release Date : 2024-01-17
Ai Driven Cyber Security written by S. R. Jena and has been published by Scholars' Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-17 with Computers categories.
Welcome to the forefront of modern cyber security – a landscape shaped and transformed by the relentless evolution of Artificial Intelligence (AI) and Deep Learning technologies. As we stand at the precipice of the digital era, the need for robust, intelligent defense mechanisms against cyber threats has never been more pressing. This book, "AI-Driven Cyber Security: Navigating the Digital Frontier with Deep Learning" embarks on a comprehensive journey through the intricate realm where cutting-edge AI meets the ever-evolving challenges of cyber security. In the interconnected world we inhabit, where data is the lifeblood of every organisation, the marriage of AI and cyber security becomes not just a choice but a necessity. Moreover, the book contains 8 chapters. They are: 1. Introduction to Cyber Security 2. Foundations of Cyber Security 3. Basics of AI and Deep Learning 4. AI in Cyber Security: An Overview 5. Deep Learning for Threat Detection 6. Natural Language Processing (NLP) in Cyber Security 7. Adversarial Machine Learning 8. Explainability and Transparency in AI Security
Data Science In Cybersecurity And Cyberthreat Intelligence
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Author : Leslie F. Sikos
language : en
Publisher: Springer Nature
Release Date : 2020-02-05
Data Science In Cybersecurity And Cyberthreat Intelligence written by Leslie F. Sikos and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-05 with Computers categories.
This book presents a collection of state-of-the-art approaches to utilizing machine learning, formal knowledge bases and rule sets, and semantic reasoning to detect attacks on communication networks, including IoT infrastructures, to automate malicious code detection, to efficiently predict cyberattacks in enterprises, to identify malicious URLs and DGA-generated domain names, and to improve the security of mHealth wearables. This book details how analyzing the likelihood of vulnerability exploitation using machine learning classifiers can offer an alternative to traditional penetration testing solutions. In addition, the book describes a range of techniques that support data aggregation and data fusion to automate data-driven analytics in cyberthreat intelligence, allowing complex and previously unknown cyberthreats to be identified and classified, and countermeasures to be incorporated in novel incident response and intrusion detection mechanisms.
Cybersecurity In Intelligent Networking Systems
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Author : Shengjie Xu
language : en
Publisher: John Wiley & Sons
Release Date : 2022-11-02
Cybersecurity In Intelligent Networking Systems written by Shengjie Xu and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-02 with Computers categories.
CYBERSECURITY IN INTELLIGENT NETWORKING SYSTEMS Help protect your network system with this important reference work on cybersecurity Cybersecurity and privacy are critical to modern network systems. As various malicious threats have been launched that target critical online services—such as e-commerce, e-health, social networks, and other major cyber applications—it has become more critical to protect important information from being accessed. Data-driven network intelligence is a crucial development in protecting the security of modern network systems and ensuring information privacy. Cybersecurity in Intelligent Networking Systems provides a background introduction to data-driven cybersecurity, privacy preservation, and adversarial machine learning. It offers a comprehensive introduction to exploring technologies, applications, and issues in data-driven cyber infrastructure. It describes a proposed novel, data-driven network intelligence system that helps provide robust and trustworthy safeguards with edge-enabled cyber infrastructure, edge-enabled artificial intelligence (AI) engines, and threat intelligence. Focusing on encryption-based security protocol, this book also highlights the capability of a network intelligence system in helping target and identify unauthorized access, malicious interactions, and the destruction of critical information and communication technology. Cybersecurity in Intelligent Networking Systems readers will also find: Fundamentals in AI for cybersecurity, including artificial intelligence, machine learning, and security threats Latest technologies in data-driven privacy preservation, including differential privacy, federated learning, and homomorphic encryption Key areas in adversarial machine learning, from both offense and defense perspectives Descriptions of network anomalies and cyber threats Background information on data-driven network intelligence for cybersecurity Robust and secure edge intelligence for network anomaly detection against cyber intrusions Detailed descriptions of the design of privacy-preserving security protocols Cybersecurity in Intelligent Networking Systems is an essential reference for all professional computer engineers and researchers in cybersecurity and artificial intelligence, as well as graduate students in these fields.
Cyber Threat Intelligence
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Author : Ali Dehghantanha
language : en
Publisher: Springer
Release Date : 2018-04-27
Cyber Threat Intelligence written by Ali Dehghantanha and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-27 with Computers categories.
This book provides readers with up-to-date research of emerging cyber threats and defensive mechanisms, which are timely and essential. It covers cyber threat intelligence concepts against a range of threat actors and threat tools (i.e. ransomware) in cutting-edge technologies, i.e., Internet of Things (IoT), Cloud computing and mobile devices. This book also provides the technical information on cyber-threat detection methods required for the researcher and digital forensics experts, in order to build intelligent automated systems to fight against advanced cybercrimes. The ever increasing number of cyber-attacks requires the cyber security and forensic specialists to detect, analyze and defend against the cyber threats in almost real-time, and with such a large number of attacks is not possible without deeply perusing the attack features and taking corresponding intelligent defensive actions – this in essence defines cyber threat intelligence notion. However, such intelligence would not be possible without the aid of artificial intelligence, machine learning and advanced data mining techniques to collect, analyze, and interpret cyber-attack campaigns which is covered in this book. This book will focus on cutting-edge research from both academia and industry, with a particular emphasis on providing wider knowledge of the field, novelty of approaches, combination of tools and so forth to perceive reason, learn and act on a wide range of data collected from different cyber security and forensics solutions. This book introduces the notion of cyber threat intelligence and analytics and presents different attempts in utilizing machine learning and data mining techniques to create threat feeds for a range of consumers. Moreover, this book sheds light on existing and emerging trends in the field which could pave the way for future works. The inter-disciplinary nature of this book, makes it suitable for a wide range of audiences with backgrounds in artificial intelligence, cyber security, forensics, big data and data mining, distributed systems and computer networks. This would include industry professionals, advanced-level students and researchers that work within these related fields.
Mastering Hacking With Ai
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Author : Kris Hermans
language : en
Publisher: Cybellium Ltd
Release Date :
Mastering Hacking With Ai written by Kris Hermans and has been published by Cybellium Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
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.
Ai And Cyber Attacks The Growing Threat Of Ai Enhanced Hacking
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Author : AQEEL AHMED
language : en
Publisher: AQEEL AHMED
Release Date : 2023-06-01
Ai And Cyber Attacks The Growing Threat Of Ai Enhanced Hacking written by AQEEL AHMED and has been published by AQEEL AHMED this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-01 with Computers categories.
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.
Big Data Analytics And Intelligent Systems For Cyber Threat Intelligence
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Author : Yassine Maleh
language : en
Publisher: CRC Press
Release Date : 2023-04-28
Big Data Analytics And Intelligent Systems For Cyber Threat Intelligence written by Yassine Maleh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-28 with Computers categories.
In recent years, a considerable amount of effort has been devoted to cyber-threat protection of computer systems which is one of the most critical cybersecurity tasks for single users and businesses since even a single attack can result in compromised data and sufficient losses. Massive losses and frequent attacks dictate the need for accurate and timely detection methods. Current static and dynamic methods do not provide efficient detection, especially when dealing with zero-day attacks. For this reason, big data analytics and machine intelligencebased techniques can be used. This book brings together researchers in the field of big data analytics and intelligent systems for cyber threat intelligence CTI and key data to advance the mission of anticipating, prohibiting, preventing, preparing, and responding to internal security. The wide variety of topics it presents offers readers multiple perspectives on various disciplines related to big data analytics and intelligent systems for cyber threat intelligence applications. Technical topics discussed in the book include: • Big data analytics for cyber threat intelligence and detection • Artificial intelligence analytics techniques • Real-time situational awareness • Machine learning techniques for CTI • Deep learning techniques for CTI • Malware detection and prevention techniques • Intrusion and cybersecurity threat detection and analysis • Blockchain and machine learning techniques for CTI
Hands On Artificial Intelligence For Cybersecurity
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Author : Alessandro Parisi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-08-02
Hands On Artificial Intelligence For Cybersecurity written by Alessandro Parisi and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-02 with Computers categories.
Build smart cybersecurity systems with the power of machine learning and deep learning to protect your corporate assets Key FeaturesIdentify and predict security threats using artificial intelligenceDevelop intelligent systems that can detect unusual and suspicious patterns and attacksLearn how to test the effectiveness of your AI cybersecurity algorithms and toolsBook Description Today's organizations spend billions of dollars globally on cybersecurity. Artificial intelligence has emerged as a great solution for building smarter and safer security systems that allow you to predict and detect suspicious network activity, such as phishing or unauthorized intrusions. This cybersecurity book presents and demonstrates popular and successful AI approaches and models that you can adapt to detect potential attacks and protect your corporate systems. You'll learn about the role of machine learning and neural networks, as well as deep learning in cybersecurity, and you'll also learn how you can infuse AI capabilities into building smart defensive mechanisms. As you advance, you'll be able to apply these strategies across a variety of applications, including spam filters, network intrusion detection, botnet detection, and secure authentication. By the end of this book, you'll be ready to develop intelligent systems that can detect unusual and suspicious patterns and attacks, thereby developing strong network security defenses using AI. What you will learnDetect email threats such as spamming and phishing using AICategorize APT, zero-days, and polymorphic malware samplesOvercome antivirus limits in threat detectionPredict network intrusions and detect anomalies with machine learningVerify the strength of biometric authentication procedures with deep learningEvaluate cybersecurity strategies and learn how you can improve themWho this book is for If you’re a cybersecurity professional or ethical hacker who wants to build intelligent systems using the power of machine learning and AI, you’ll find this book useful. Familiarity with cybersecurity concepts and knowledge of Python programming is essential to get the most out of this book.