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With the quick advancement of web technology and network applications, protecting digitized information from unwanted access and modification has become a critical problem in today’s digital world. The security issue in electronic media has presented a complex challenge, initiating the development of cryptographic algorithms incorporating Chaos theory and secret sharing schemes. Chaos theory and secret sharing have been used to develop various multimedia application encryption strategies. Encryption converts multimedia data, i.e., images, audio, and videos, into noise-like data. The chaotic map characteristics, such as nonlinearity and sensitivity to the initial conditions, make it suitable for use in cryptography. At the same time, secret schemes can protect essential information against loss, modification, or destruction. Numerous techniques based on Chaos theory and secret sharing have been created to overcome these issues. These security techniques have become very popular for developing image and video cryptosystems. Also, the authors have developed chaotic map-based cryptosystems for other forms of multimedia data and other research fields such as IoT, cloud computing, smart grid, etc. Moreover, the authors have proposed different secret-sharing schemes to recognize and secure multimedia data based on their characteristics. Furthermore, some books have been edited by the authors, concentrating only on different methodologies proposed by the researchers. However, no authored book that discusses this important research topic from the viewpoint of chaotic map-based multimedia encryption is available in the market. To this end, the book aims to review and highlight the challenges of intelligent multimedia security and present the recent developments to address those challenges.

With the quick advancement of web technology and network applications, protecting digitized information from unwanted access and modification has become a critical problem in today’s digital world. The security issue in electronic media has presented a complex challenge, initiating the development of cryptographic algorithms incorporating Chaos theory and secret sharing schemes. Chaos theory and secret sharing have been used to develop various multimedia application encryption strategies. Encryption converts multimedia data, i.e., images, audio, and videos, into noise-like data. The chaotic map characteristics, such as nonlinearity and sensitivity to the initial conditions, make it suitable for use in cryptography. At the same time, secret schemes can protect essential information against loss, modification, or destruction. Numerous techniques based on Chaos theory and secret sharing have been created to overcome these issues. These security techniques have become very popular for developing image and video cryptosystems. Also, the authors have developed chaotic map-based cryptosystems for other forms of multimedia data and other research fields such as IoT, cloud computing, smart grid, etc. Moreover, the authors have proposed different secret-sharing schemes to recognize and secure multimedia data based on their characteristics. Furthermore, some books have been edited by the authors, concentrating only on different methodologies proposed by the researchers. However, no authored book that discusses this important research topic from the viewpoint of chaotic map-based multimedia encryption is available in the market. To this end, the book aims to review and highlight the challenges of intelligent multimedia security and present the recent developments to address those challenges.

Audio Spoof Detection (ASD) systems play a pivotal role in evaluating whether the input speech signal has been manipulated by an imposter attempting unauthorized access to an authentic user's account or if it genuinely originates from the declared user. Primarily used for person authentication, these systems strive to verify the speaker's claimed identity. Despite substantial technological advancements, recent testing has revealed persistent vulnerabilities to spoofing, commonly referred to as a spoof attack. Various techniques such as mimicry, replay, text to speech (TTS), and voice conversion (VC) are frequently used in ASV systems to execute logical access (LA) or physical access (PA) spoofing attacks. To protect an ASD system from these attacks, many researchers have proposed effective security models as countermeasures. In addition, numerous review papers by different researchers have discussed various countermeasures developed to secure ASD systems. However, there is a notable absence of an authored book that comprehensively addresses this critical research topic, encompassing frontend, backend, dataset, and types of attacks considerations. Therefore, there is an urgent need for a book that can serve as a valuable resource for upcoming researchers, offering insights into securing ASD systems and bridging the existing gap in the literature. Hence, this book represents an effort by the authors in that direction.

Audio Spoof Detection (ASD) systems play a pivotal role in evaluating whether the input speech signal has been manipulated by an imposter attempting unauthorized access to an authentic user's account or if it genuinely originates from the declared user. Primarily used for person authentication, these systems strive to verify the speaker's claimed identity. Despite substantial technological advancements, recent testing has revealed persistent vulnerabilities to spoofing, commonly referred to as a spoof attack. Various techniques such as mimicry, replay, text to speech (TTS), and voice conversion (VC) are frequently used in ASV systems to execute logical access (LA) or physical access (PA) spoofing attacks. To protect an ASD system from these attacks, many researchers have proposed effective security models as countermeasures. In addition, numerous review papers by different researchers have discussed various countermeasures developed to secure ASD systems. However, there is a notable absence of an authored book that comprehensively addresses this critical research topic, encompassing frontend, backend, dataset, and types of attacks considerations. Therefore, there is an urgent need for a book that can serve as a valuable resource for upcoming researchers, offering insights into securing ASD systems and bridging the existing gap in the literature. Hence, this book represents an effort by the authors in that direction.

Audio Spoof Detection (ASD) systems play a pivotal role in evaluating whether the input speech signal has been manipulated by an imposter attempting unauthorized access to an authentic user's account or if it genuinely originates from the declared user. Primarily used for person authentication, these systems strive to verify the speaker's claimed identity. Despite substantial technological advancements, recent testing has revealed persistent vulnerabilities to spoofing, commonly referred to as a spoof attack. Various techniques such as mimicry, replay, text to speech (TTS), and voice conversion (VC) are frequently used in ASV systems to execute logical access (LA) or physical access (PA) spoofing attacks. To protect an ASD system from these attacks, many researchers have proposed effective security models as countermeasures. In addition, numerous review papers by different researchers have discussed various countermeasures developed to secure ASD systems. However, there is a notable absence of an authored book that comprehensively addresses this critical research topic, encompassing frontend, backend, dataset, and types of attacks considerations. Therefore, there is an urgent need for a book that can serve as a valuable resource for upcoming researchers, offering insights into securing ASD systems and bridging the existing gap in the literature. Hence, this book represents an effort by the authors in that direction.