Recent Advances in Cryptography and Network Security

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This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Another problem to be addressed is the security and privacy of the large amount of information communicated through wired or wireless transmission media.

Introductory Chapter: Recent Advances in Cryptography and Network Security

Introduction

In symmetric key cryptography, the same key is shared between the sender and receiver. But in public-key cryptography, the sender sends encrypted data to the receiver using the receiver's public key. In public-key cryptosystem, the sender sends the message and signature which is the encrypted version of the message with the sender's private/secret key.

Figure 3 illustrates a digital signature scheme where the digital signature S = SA(M) is a message encrypted with Alice's secret key. At the receiving end, Bob uses Alice's public key to obtain M' = PA(S) = PA(SA(M)), which should be equal to M if the signature is valid. There are several variations of signature schemes and many of them use cryptographic hashing functions.

In the field of network security, we have seen different new types of attacks with the advent of mobile computing technology where there are no fixed interconnections between mobile nodes. The main goal here is not to jeopardize the security and authenticity of the communicated data too much.

Figure 2 depicts public-key cryptosystem. In both figures, the sender is Alice and the receiver is Bob

Conclusion

Network protocol TCP/IP was replaced with RTP running over UDP for real-time applications. The topic of network security also had to face many challenges due to variable interconnect topology instead of a fixed interconnect topology.

Author details

A New Approximation Method for Constant Weight Coding and Its Hardware Implementation

• Sendrier’s methods for constant weight coding
• Proposed approximation method of d
• Proposed constant weight encoder and decoder
• Integrating with the Niederreiter encryptor
• Results and comparisons
• Conclusion

In the case of Niederreiter/McEliece encryption, the binary stream of plaintext is requested to be converted in the form of constant weight words. We propose a new approximation method of constant weight coding free from complicated floating-point arithmetic and heavy memory footprint. This method allows to implement a compact and fast constant weight code on the resource limited computing platform. Sendrier's proposal of constant weight coding and its approximation variant [17, 18] are first revisited in Section 2.

A new approximation method for constant weight coding and its hardware implementation 11 http://dx.doi.org/10.5772/intechopen.75041. A higher coding efficiency means that one can encode more bits from the source into a constant weight word. The Y-axis represents the average length (bits) of the input message read for a successful constant weight encoding.

A new approach to constant weight coding and its hardware implementation 13 http://dx.doi.org/10.5772/intechopen.75041. A New Approach to Constant Weight Coding and Its Hardware Implementation 15 http://dx.doi.org/10.5772/intechopen.75041. A new approach to constant weight coding and its hardware implementation 17 http://dx.doi.org/10.5772/intechopen.75041.

A new approximation method for constant weight coding and its hardware implementation 19 http://dx.doi.org/10.5772/intechopen.75041. We captured our constant-weight coding architecture in Verilog and prototyped our design on a Xilinx Virtex-6 FPGA (Table 5). A new approximation method for constant weight coding and its hardware implementation 21 http://dx.doi.org/10.5772/intechopen.75041.

To our knowledge, the only compact implementations of constant weight coding have been proposed by Heyse et al. In comparison, our best_d module has three stages in the pipeline, thus leading to a lower throughput, but tour architectures are smaller and improve the area-time trade-off of the constant weight coding implementations proposed by Heyseetal [19], shown in Table 5. .In particular, we use only one 18 kb memory blocks for all our experimental parameters. A new approach to determining the optimal value d in constant weight coding is proposed in this chapter.

This method innovates a more compact but efficient architecture for constant weight encoder and decoder in computer systems with limited resources. A New Approach to Constant Weight Coding and Its Hardware Implementation 23 http://dx.doi.org/10.5772/intechopen.75041.

Table 1. Parameters recommended used in the Niederreiter cryptosystem, referenced partly from [13, 19, 23, 25]

Protocol for Multiple Black Hole Attack Avoidance in Mobile Ad Hoc Networks

• Black hole attack in MANETs
• Materials and methods
• The proposed protocol: enhanced RID-AODV
• Simulation and network environment
• Performance metrics
• Results and analysis

Black hole attack is a type of active attack that exploits the route reply message feature (RREP) of the routing protocol. Protocol for Avoiding Multiple Black Hole Attacks in Mobile Ad Hoc Networks 27 http://dx.doi.org/10.5772/intechopen.73310. It was found that the black hole attack is more dangerous than other attacks mentioned in this paper [7].

They also considered the attack on the black hole as its impact on ad hoc networks. Protocol for avoiding multiple black hole attacks in mobile ad hoc networks 29 http://dx.doi.org/10.5772/intechopen.73310. The downside is that it cannot detect multiple black hole attacks and the control messages are increased [15].

Through simulation, our method shows significant effectiveness in detecting the black hole attack [16]. This is why routing is targeted in many types of MANET attacks, especially black hole attacks. Therefore, we took all the advantages of the previous protocols in mitigating the bad impact of the existence of malicious black hole nodes in the ad hoc network.

Protocol for Avoiding Multiple Black Hole Attacks in Mobile Ad Hoc Networks 31 http://dx.doi.org/10.5772/intechopen.73310. Protocol for Avoiding Multiple Black Hole Attacks in Mobile Ad Hoc Networks 33 http://dx.doi.org/10.5772/intechopen.73310. Protocol for Avoiding Multiple Black Hole Attacks in Mobile Ad Hoc Networks 35 http://dx.doi.org/10.5772/intechopen.73310.

A Protocol for Avoiding Multiple Black Hole Attacks in Mobile Ad Hoc Networks 37 http://dx.doi.org/10.5772/intechopen.73310. Just one black hole node in the network can reduce the PDR to about 10%. A Protocol for Avoiding Multiple Black Hole Attacks in Mobile Ad Hoc Networks 39 http://dx.doi.org/10.5772/intechopen.73310.

Several mechanisms and protocols have been proposed to detect and mitigate the effects of multiple black hole attacks using different strategies. A Protocol for Avoiding Multiple Black Hole Attacks in Mobile Ad Hoc Networks 41 http://dx.doi.org/10.5772/intechopen.73310.

Figure 1. Black hole attack illustration.

A Survey of Machine Learning Techniques for Behavioral-Based Biometric User Authentication

Provisional chapter

A Survey of Machine Learning Techniques for Behavioral-Based Biometric User Authentication

• Authentication
• User authentication methods
• Behavioral-based biometric authentication
• Discussion
• Conclusion

This application focuses on extracting the behavioral features related to the user and using these features for authentication measure. However, there is a downside to static authentication in that this approach will only authenticate the user at the start of each session. The user has to drag the numbers in the right direction to the center of the screen.

The authentication task requires the user to respond to the service server by entering an existing combination of text-based and graphical passwords to provide better accuracy. The location is verified and compared before deciding whether the user is valid or not. During the registration phase, the user selects a username and a textual password and then chooses an object as a password by drawing.

During the authentication process, the user enters username and text password and then signs the pre-selected objects. This method makes use of things that the user personally owns, such as token, smart card and QR code. Using human characteristics is the best solution compared to the user who knows and owns personally [14].

These authentication methods identify the user as themselves based on measurable physiological or behavioral characteristics. Keystroke dynamics is one of the automated methods to verify the user's identity based on the manner and rhythm of typing on the keyboard [35]. During the verification process, the user follows the dot pattern identical to that of a sign-up phase.

Compare — value against the range of the user's counter value (exact value) Decision tree — algorithm. Can be lost and duplicated Something the user is Finger scan, iris scan, retina scan, hand scan, face scan, etc. Something the user Signature, corridors (the way people walk), keystroke dynamics Not possible to share and.

Figure 1. Taxonomy of user authentication methods.

Acknowledgements

A Survey of Machine Learning Techniques for Behavioral Biometric User Authentication 55 http://dx.doi.org/10.5772/intechopen.76685. This research provides a comprehensive study on machine learning techniques in the field of behavioral biometric authentication. In the behavioral biometric authentication section, we discuss two subcategories of machine learning techniques, which are supervised (classification) and unsupervised (clustering) techniques.

We examine each subcategory that has been implemented in the previous behavioral biometric authentication. At the end of this paper, we should be able to acquire relevant knowledge required to improve the performance of the behavioral biometric authentication.

Conflict of interest

In: IIH-MSP the International Conference on Intelligent Information Hiding and Multimedia Signal Processing; 2009, pp. In: Proceedings of the 2009 IEEE Symposium on Computational Intelligence in Security and Defense Applications (CISDA 2009) Evolution, (Cisda); 2009. A Survey of Machine Learning Techniques for Behavior-Based Biometric User Authentication 57 http://dx.doi.org/10.5772/intechopen.76685.

In: 2012 Eighth IEEE International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP); 2012. Hold and Draw: A New Behavioral Biometric for Smartphone User Authentication Hold and Draw: A New Behavioral Biometric for Smartphone User Authentication. A Survey of Machine Learning Techniques for Behavior-Based Biometric User Authentication 59 http://dx.doi.org/10.5772/intechopen.76685.