AI-Driven Cybersecurity andThreat Intelligence - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook AI-Driven Cybersecurity andThreat Intelligence write by Iqbal H. Sarker. This book was released on . AI-Driven Cybersecurity andThreat Intelligence available in PDF, EPUB and Kindle.
Artificial Intelligence for Security
Artificial Intelligence for Security - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Artificial Intelligence for Security write by Tuomo Sipola. This book was released on . Artificial Intelligence for Security available in PDF, EPUB and Kindle.
Hands-On Artificial Intelligence for Cybersecurity
Hands-On Artificial Intelligence for Cybersecurity - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Hands-On Artificial Intelligence for Cybersecurity write by Alessandro Parisi. This book was released on 2019-08-02. Hands-On Artificial Intelligence for Cybersecurity available in PDF, EPUB and Kindle. 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.
Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence
Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence write by Yassine Maleh. This book was released on 2023-04-28. Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence available in PDF, EPUB and Kindle. 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
AI in Cybersecurity
AI in Cybersecurity - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook AI in Cybersecurity write by Leslie F. Sikos. This book was released on 2018-09-27. AI in Cybersecurity available in PDF, EPUB and Kindle. 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.
