Audio Content Security: Attack Analysis on Audio Watermarking describes research using a common audio watermarking method for four different genres of music, also providing the results of many test attacks to determine the robustness of the watermarking in the face of those attacks. The results of this study can be used for further studies and to establish the need to have a particular way of audio watermarking for each particular group of songs, each with different characteristics. An additional aspect of this study tests and analyzes two parameters of audio host file and watermark on a specific evaluation method (PSNR) for audio watermarking.

Mobile Ad Hoc Networks (MANETs) are a popular form of network for data transfer due to the fact that they are dynamic, require no fixed infrastructure, and are scalable. However, MANETs are particularly susceptible to several different types of widely perpetrated cyberattack. One of the most common hacks aimed at MANETs is the Black Hole attack, in which a particular node within the network displays itself as having the shortest path for the node whose packets it wants to intercept. Once the packets are drawn to the Black Hole, they are then dropped instead of relayed, and the communication of the MANET is thereby disrupted, without knowledge of the other nodes in the network. Due to the sophistication of the Black Hole attack, there has been a lot of research conducted on how to detect it and prevent it. The authors of this short format title provide their research results on providing an effective solution to Black Hole attacks, including introduction of new MANET routing protocols that can be implemented in order to improve detection accuracy and network parameters such as total dropped packets, end-to-end delay, packet delivery ratio, and routing request overhead.

Phishing is one of the most widely-perpetrated forms of cyber attack, used to gather sensitive information such as credit card numbers, bank account numbers, and user logins and passwords, as well as other information entered via a web site. The authors of A Machine-Learning Approach to Phishing Detetion and Defense have conducted research to demonstrate how a machine learning algorithm can be used as an effective and efficient tool in detecting phishing websites and designating them as information security threats. This methodology can prove useful to a wide variety of businesses and organizations who are seeking solutions to this long-standing threat. A Machine-Learning Approach to Phishing Detetion and Defense also provides information security researchers with a starting point for leveraging the machine algorithm approach as a solution to other information security threats.

In the past decade, the number of wireless devices has grown exponentially. Decades ago, all systems were wired computer systems. Wireless technology was not accessible in mobile and portable devices until in recent years, and has followed a variety of methods for encryption and resource management. The purpose of the research in Optimizing IEE 802.11i Resources and Security Essentials is to determine the issues of the performance in current encryption methods in AES-CCMP in different types of devices and handle it so that an optimized resource usage would be achieved with the required security. Two modes for 802.11i for two different groups of devices is suggested and evaluated with the current encryption method for AES-CCMP to compare the performance. Almost every organization in today's world relies on wireless networks to transmit information, and much of that information should be kept secure. Banking, healthcare, and the military are all vital industries that rely on wireless security for a huge section of their operations. Security experts of today and tomorrow will learn a lot from Optimizing IEE 802.11i Resources and Security Essentials, and it can be used for master level in computer science, information security, wireless network security and cryptography.

Denial of Service (DoS) attacks are a form of attack that seeks to make a network resource unavailable due to overloading the resource or machine with an overwhelming number of packets, thereby crashing or severely slowing the performance of the resource. Distributed Denial of Service (DDoS) is a large scale DoS attack which is distributed in the Internet. Every computer which has access to the Internet can behave as an attacker. Typically bandwidth depletion can be categorized as either a flood or an amplification attack. Flood attacks can be done by generating ICMP packets or UDP packets in which it can utilize stationary or random variable ports. Smurf and Fraggle attacks are used for amplification attacks. DDoS Smurf attacks are an example of an amplification attack where the attacker sends packets to a network amplifier with the return address spoofed to the victim's IP address. This book presents new research and methodologies along with a proposed algorithm for prevention of DoS attacks that has been written based on cryptographic concepts such as birthday attacks to estimate the rate of attacks generated and passed along the routers. Consequently, attackers would be identified and prohibited from sending spam traffic to the server which can cause DDoS attacks. Due to the prevalence of DoS attacks, there has been a lot of research conducted on how to detect them and prevent them. The authors of this short format title provide their research results on providing an effective solution to DoS attacks, including introduction of the new algorithm that can be implemented in order to deny DoS attacks.