Cryptoraptor : high throughput reconfigurable cryptographic processor for symmetric key encryption and cryptographic hash functions

textIn cryptographic processor design, the selection of functional primitives and connection structures between these primitives are extremely crucial to maximize throughput and flexibility. Hence, detailed analysis on the specifications and requirements of existing crypto-systems plays a crucial role in cryptographic processor design. This thesis provides the most comprehensive literature review that we are aware of on the widest range of existing cryptographic algorithms, their specifications, requirements, and hardware structures. In the light of this analysis, it also describes a high performance, low power, and highly flexible cryptographic processor, Cryptoraptor, that is designed to support both today's and tomorrow's encryption standards. To the best of our knowledge, the proposed cryptographic processor supports the widest range of cryptographic algorithms compared to other solutions in the literature and is the only crypto-specific processor targeting the future standards as well. Unlike previous work, we aim for maximum throughput for all known encryption standards, and to support future standards as well. Our 1GHz design achieves a peak throughput of 128Gbps for AES-128 which is competitive with ASIC designs and has 25X and 160X higher throughput per area than CPU and GPU solutions, respectively.Electrical and Computer Engineerin

Evaluation of mobile network security in Ghana

Applied project submitted to the Department of Computer Science, Ashesi University College, in partial fulfillment of Bachelor of Science degree in Computer Science, April 2015Mobile technology is one of the most successful technologies on the African continent. Personal and professional communication as well as critical services like banking and remittances are widely made through mobile networks and platforms in Ghana. However, little is known about the security of the underlying infrastructure and devices consumers use to interact with the mobile network. The focus of this project is to determine if the core systems of the mobile network operators, the technology infrastructure, and the 2G/3G dongles have exploitable security vulnerabilities, demonstrate some of those exploits, and make recommendations on how to mitigate or eliminate the risk of exploitation.Ashesi University Colleg

Improving the security of wireless sensor networks

With the rapid technological advancements of sensors, Wireless Sensor Networks (WSNs) have become the main technology for the Internet of Things (IoT). We investigated the security of WSNs in an environmental monitoring system with the goal to improve the overall security. We implemented a Secure Temperature Monitoring System (STMS), which served as our investigational environment. Our results revealed a security flaw found in the bootstrap loader (BSL) password used to protect firmware in the MSP430 MCU chips. We demonstrated how the BSL password could be brute forced in a matter of days. Furthermore, we illustrate how an attacker can reverse engineer firmware and obtain copies of cryptographic keys. We contributed a solution to improve the BSL password and better protect firmware found in the MSP430 chips. The Secure-BSL software we contributed allows the randomization of the BSL password. Our solution increases the brute force time to decades. The impractical brute force time improves the security of firmware and prevents future reverse engineering tactics. In addition, our Secure-BSL software supports two-factor authentication that allows developers to specify a user-defined passphrase to further protect the MSP430 MCU. Our research serves as proof that any security implemented in a WSN environment is broken if an attacker has access to firmware found in sensor devices

E-commerce security enhancement and anomaly intrusion detection using machine learning techniques

With the fast growth of the Internet and the World Wide Web, security has become a major concern of many organizations, enterprises and users. Criminal attacks and intrusions into computer and information systems are spreading quickly and they can come from anywhere on the globe. Intrusion prevention measures, such as user authentication, firewalls and cryptography have been used as the first line of defence to protect computer and information systems from intrusions. As intrusion prevention alone may not be sufficient in a highly dynamic environment, such as the Internet, intrusion detection has been used as the second line of defence against intrusions. However, existing cryptography-based intrusion prevention measures implemented in software, have problems with the protection of long-term private keys and the degradation of system performance. Moreover, the security of these software-based intrusion prevention measures depends on the security of the underlying operating system, and therefore they are vulnerable to threats caused by security flaws of the underlying operating system. On the other hand, existing anomaly intrusion detection approaches usually produce excessive false alarms. They also lack in efficiency due to high construction and maintenance costs. In our approach, we employ the "defence in depth" principle to develop a solution to solve these problems. Our solution consists of two lines of defence: preventing intrusions at the first line and detecting intrusions at the second line if the prevention measures of the first line have been penetrated. At the first line of defence, our goal is to develop an encryption model that enhances communication and end-system security, and improves the performance of web-based E-commerce systems. We have developed a hardware-based RSA encryption model to address the above mentioned problems of existing software-based intrusion prevention measures. The proposed hardware-based encryption model is based on the integration of an existing web-based client/server model and embedded hardware-based RSA encryption modules. DSP embedded hardware is selected to develop the proposed encryption model because of its advanced security features and high processing capability. The experimental results showed that the proposed DSP hardware-based RSA encryption model outperformed the software-based RSA implementation running on Pentium 4 machines that have almost double clock speed of the DSP's clock speed at large RSA encryption keys. At the second line of defence, our goal is to develop an anomaly intrusion detection model that improves the detection accuracy, efficiency and adaptability of existing anomaly detection approaches. Existing anomaly detection systems are not effective as they usually produce excessive false alarms. In addition, several anomaly detection approaches suffer a serious efficiency problem due to high construction costs of the detection profiles. High construction costs will eventually reduce the applicability of these approaches in practice. Furthermore, existing anomaly detection systems lack in adaptability because no mechanisms are provided to update their detection profiles dynamically, in order to adapt to the changes of the behaviour of monitored objects. We have developed a model for program anomaly intrusion detection to address these problems. The proposed detection model uses a hidden Markov model (HMM) to characterize normal program behaviour using system calls. In order to increase the detection rate and to reduce the false alarm rate, we propose two detection schemes: a two-layer detection scheme and a fuzzy-based detection scheme. The two-layer detection scheme aims at reducing false alarms by applying a double-layer test on each sequence of test traces of system calls. On the other hand, the fuzzy-based detection scheme focuses on further improving the detection rate, as well as reducing false alarms. It employs the fuzzy inference to combine multiple sequence information to correctly determine the sequence status. The experimental results showed that the proposed detection schemes reduced false alarms by approximately 48%, compared to the normal database scheme. In addition, our detection schemes generated strong anomaly signals for all tested traces, which in turn improve the detection rate. We propose an HMM incremental training scheme with optimal initialization to address the efficiency problem by reducing the construction costs, in terms of model training time and storage demand. Unlike the HMM batch training scheme, which updates the HMM model using the complete training set, our HMM incremental training scheme incrementally updates the HMM model using one training subset at a time, until convergence. The experimental results showed that the proposed HMM incremental training scheme reduced training time four-fold, compared to the HMM batch training, based on the well-known Baum-Welch algorithm. The proposed training scheme also reduced storage demand substantially, as the size of each training subset is significantly smaller than the size of the complete training set. We also describe our complete model for program anomaly detection using system calls in chapter 8. The complete model consists of two development stages: training stage and testing stage. In the training stage, an HMM model and a normal database are constructed to represent normal program behaviour. In addition, fuzzy sets and rules are defined to represent the space and combined conditions of the sequence parameters. In the testing stage, the HMM model and the normal database, are used to generate the sequence parameters which are used as the input for the fuzzy inference engine to evaluate each sequence of system calls for anomalies and possible intrusions. The proposed detection model also provides a mechanism to update its detection profile (the HMM model and the normal database) using online training data. This makes the proposed detection model up-to-date, and therefore, maintains the detection accuracy

A Salad of Block Ciphers

This book is a survey on the state of the art in block cipher design and analysis. It is work in progress, and it has been for the good part of the last three years -- sadly, for various reasons no significant change has been made during the last twelve months. However, it is also in a self-contained, useable, and relatively polished state, and for this reason I have decided to release this \textit{snapshot} onto the public as a service to the cryptographic community, both in order to obtain feedback, and also as a means to give something back to the community from which I have learned much. At some point I will produce a final version -- whatever being a ``final version\u27\u27 means in the constantly evolving field of block cipher design -- and I will publish it. In the meantime I hope the material contained here will be useful to other people

Statistical cryptanalysis of block ciphers

Since the development of cryptology in the industrial and academic worlds in the seventies, public knowledge and expertise have grown in a tremendous way, notably because of the increasing, nowadays almost ubiquitous, presence of electronic communication means in our lives. Block ciphers are inevitable building blocks of the security of various electronic systems. Recently, many advances have been published in the field of public-key cryptography, being in the understanding of involved security models or in the mathematical security proofs applied to precise cryptosystems. Unfortunately, this is still not the case in the world of symmetric-key cryptography and the current state of knowledge is far from reaching such a goal. However, block and stream ciphers tend to counterbalance this lack of "provable security" by other advantages, like high data throughput and ease of implementation. In the first part of this thesis, we would like to add a (small) stone to the wall of provable security of block ciphers with the (theoretical and experimental) statistical analysis of the mechanisms behind Matsui's linear cryptanalysis as well as more abstract models of attacks. For this purpose, we consider the underlying problem as a statistical hypothesis testing problem and we make a heavy use of the Neyman-Pearson paradigm. Then, we generalize the concept of linear distinguisher and we discuss the power of such a generalization. Furthermore, we introduce the concept of sequential distinguisher, based on sequential sampling, and of aggregate distinguishers, which allows to build sub-optimal but efficient distinguishers. Finally, we propose new attacks against reduced-round version of the block cipher IDEA. In the second part, we propose the design of a new family of block ciphers named FOX. First, we study the efficiency of optimal diffusive components when implemented on low-cost architectures, and we present several new constructions of MDS matrices; then, we precisely describe FOX and we discuss its security regarding linear and differential cryptanalysis, integral attacks, and algebraic attacks. Finally, various implementation issues are considered

A New Method for Designing Lightweight S-boxes with High Differential and Linear Branch Numbers, and Its Application

Bit permutations are efficient linear functions often used for lightweight cipher designs. However, they have low diffusion effects, compared to word-oriented binary and MDS matrices. Thus, the security of bit permutation-based ciphers is significantly affected by differential and linear branch numbers (DBN and LBN) of nonlinear functions. In this paper, we introduce a widely applicable method for constructing S-boxes with high DBN and LBN. Our method exploits constructions of S-boxes from smaller S-boxes and it derives/proves the required conditions for smaller S-boxes so that the DBN and LBN of the constructed S-boxes are at least 3. These conditions enable us to significantly reduce the search space required to create such S-boxes. In order to make cryptographically good and efficient S-boxes, we propose a unbalanced-Bridge structure that accepts one 3-bit and two 5-bit S-boxes, and produces 8-bit S-boxes. Using the proposed structure, we develop a variety of new lightweight S-boxes that provide not only both DBN and LBN of at least 3 but also efficient bitsliced implementations including at most 11 nonlinear bitwise operations. The new S-boxes are the first that exhibit these characteristics. Moreover, we propose a block cipher PIPO based on one of the new S-boxes, which supports a 64-bit plaintext and a 128 or 256-bit key. Our implementations demonstrate that PIPO outperforms existing block ciphers (for the same block and key lengths) in both side-channel protected and unprotected environments, on an 8-bit AVR. The security of PIPO has been scrutinized with regards to state-of-the-art cryptanalysis

A secure architecture enabling end-user privacy in the context of commercial wide-area location-enhanced web services

Mobile location-based services have raised privacy concerns amongst mobile phone users who may need to supply their identity and location information to untrustworthy third parties in order to access these applications. Widespread acceptance of such services may therefore depend on how privacy sensitive information will be handled in order to restore users’ confidence in what could become the “killer app” of 3G networks. The work reported in this thesis is part of a larger project to provide a secure architecture to enable the delivery of location-based services over the Internet. The security of transactions and in particular the privacy of the information transmitted has been the focus of our research. In order to protect mobile users’ identities, we have designed and implemented a proxy-based middleware called the Orient Platform together with its Orient Protocol, capable of translating their real identity into pseudonyms. In order to protect users’ privacy in terms of location information, we have designed and implemented a Location Blurring algorithm that intentionally downgrades the quality of location information to be used by location-based services. The algorithm takes into account a blurring factor set by the mobile user at her convenience and blurs her location by preventing real-time tracking by unauthorized entities. While it penalizes continuous location tracking, it returns accurate and reliable information in response to sporadic location queries. Finally, in order to protect the transactions and provide end-to-end security between all the entities involved, we have designed and implemented a Public Key Infrastructure based on a Security Mediator (SEM) architecture. The cryptographic algorithms used are identitybased, which makes digital certificate retrieval, path validation and revocation redundant in our environment. In particular we have designed and implemented a cryptographic scheme based on Hess’ work [108], which represents, to our knowledge, the first identity-based signature scheme in the SEM setting. A special private key generation process has also been developed in order to enable entities to use a single private key in conjunction with multiple pseudonyms, which significantly simplifies key management. We believe our approach satisfies the security requirements of mobile users and can help restore their confidence in location-based services

Security in Distributed, Grid, Mobile, and Pervasive Computing

This book addresses the increasing demand to guarantee privacy, integrity, and availability of resources in networks and distributed systems. It first reviews security issues and challenges in content distribution networks, describes key agreement protocols based on the Diffie-Hellman key exchange and key management protocols for complex distributed systems like the Internet, and discusses securing design patterns for distributed systems. The next section focuses on security in mobile computing and wireless networks. After a section on grid computing security, the book presents an overview of security solutions for pervasive healthcare systems and surveys wireless sensor network security