Cryptography is a ubiquitous tool in secure software development in order to guarantee security requirements in general. However, software developers have scarce knowledge about cryptography and rely on limited support tools that cannot properly detect bad uses of cryptography, thus generating vulnerabilities in software. In this work, we extend the scarcely use of machine learning to detect cryptography misuse in source code by using a state of the art deep learning model (i.e.,code2vec) through transfer learning to generate features that feed machine learning models. In addition, we compare this approach to previous ones in different types of binary models. Also, we adapt code obfuscation to serve as data augmentation in machine learning source code related tasks. Finally, we show that through transfer learningcode2veccan be a competitive feature generator for cryptography misuse detection and simple code obfuscation can be used to generate data to enhance machine learning models training in source code related tasks.

A 3-flow for a graph G is an assignment of directions and weights in {1, 2} to the edges of G, such that the netsum of weights on the edges incident to every vertex of G is equal to zero (weights on incoming and outgoing edges are added with opposite signs). Not every graph admits a 3-flow. Aside from graphs with an edge cut of size one, K4 is the simplest graph that does not admit a 3-flow. Tutte’s famous 3-flow Conjecture postulates that every 2-edge-connected graph without edge cuts of size three (3-cuts) admits a 3-flow. A slightly stronger form of this conjecture allows up to three 3-cuts. In this work, our objective is to study classes of graphs with up to four 3-cuts, in fact four vertices of degree three (3-vertices), that admit a 3-flow. We focus on almost even graphs, i.e., graphs with a small number of odd vertices. We obtain a characterization for graphs with up to four odd vertices. We also obtain partial characterizations for graphs with up to four 3-vertices and two odd vertices of higher degree. As expected, 3-vertices play a central role in blocking the existence of 3-flows. Our attempt at understanding this role is motivated by the need to allow a small number of additional 3-vertices in inductive proofs of restricted forms of Tutte’s Conjecture.

Cryptography is an essential aspect of software development. Nevertheless, software developers have limited knowledge of cryptography primitives, and support tools are limited. In this work, we present a comparison between graph embedding techniques, node2vec and Bag of Graphs, as embedding generators of source code graph representations. We combined these techniques with machine learning models in order to detect cryptography misuses in source codes. We show that Bag of Graphs outperforms node2vec in this task; also, both techniques outperform previously evaluated tools.

Elliptic curve cryptosystems are considered an efficient alternative to conventional systems such as DSA and RSA. Recently, Montgomery and Edwards elliptic curves have been used to implement cryptosystems. In particular, the elliptic curves Curve25519 and Curve448 were used for instantiating Diffie-Hellman protocols named X25519 and X448. Mapping these curves to twisted Edwards curves allowed deriving two new signature instances, called Ed25519 and Ed448, of the Edwards Digital Signature Algorithm. In this work, we focus on the secure and efficient software implementation of these algorithms using SIMD parallel processing. We present software techniques that target the Intel AVX2 vector instruction set for accelerating prime field arithmetic and elliptic curve operations. Our contributions result in a high-performance software library for AVX2-ready processors. For example, our library computes digital signatures 19% (for Ed25519) and 29% (for Ed448) faster than previous optimized implementations. Also, our library improves by 10% and 20% the execution time of X25519 and X448, respectively.

The use of cryptography is nowadays common in software systems, with cryptographic libraries widely available to software developers. As such, the likely weakest link in sensitive software has moved from cryptographic function implementations to the application code surrounding such functions. Ordinary developers usually lack knowledge in practical cryptography, and support from specialists is rare. Frequently, these difficulties are addressed by running static analysis tools to automatically detect cryptography misuse during coding and reviews. However, the effectiveness of such tools is not yet well understood. This article studies how well programmatic misuse of cryptography is detected by free static code analysis tools. The performance of such tools in detecting misuse is correlated to coding tasks and use cases commonly found in development efforts; also, cryptography misuse is classified in comprehensive categories, easily recognizable by software security practitioners. Our research shows that the coverage of public-key cryptography by static code analysis tools is full of blind spots, because tools prioritize only those misuses related to the most frequent coding tasks and use cases, while neglecting infrequent use cases. We found that, in addition to a relatively low recall in our tests, evaluated tools also have a small overlap regarding the misuses detected by all the evaluated tools, as well as an intersection of false alarms, suggesting lack of discrimination between specific misuses and corresponding good uses of cryptography. In spite of that, well-selected tools can be useful when developing cryptographic software, but support of experts is still required for solving complex cases.

The incorrect use of cryptography is a common source of critical software vulnerabilities. As developers lack knowledge in applied cryptography and support from experts is scarce, this situation is frequently addressed by adopting static code analysis tools to automatically detect cryptography misuse during coding and reviews, even if the effectiveness of such tools is far from being well understood. This paper proposes a method for benchmarking static code analysis tools for the detection of cryptography misuse, and evaluates the method in a case study, with the goal of selecting the most adequate tools for specific development contexts. Our method classifies cryptography misuse in nine categories recognized by developers (weak cryptography, poor key management, bad randomness, etc.) and provides the workload, metrics and procedure needed for a fair assessment and comparison of tools. We found that all evaluated tools together detected only 35% of cryptography misuses in our tests. Furthermore, none of the evaluated tools detected insecure elliptic curves, weak parameters in key agreement, and most insecure configurations for RSA and ECDSA. This suggests cryptography misuse is underestimated by tool builders. Despite that, we show that it is possible to benefit from an adequate tool selection during the development of cryptographic software.

The security of computing systems relies heavily on their hardware architecture. Currently, hardware is evaluated using mostly manual processes that are prone to errors, and generate a large, complex workload. In this paper, we are the first to report the use of the Assurance Case methodology to guide a hardware architecture security analysis. We were able to analyze real-world systems, and to detect known and some possibly unknown vulnerabilities. We also show that, by employing Assurance Cases, other benefits are gained, such as better security analysis coverage and better documentation of the security-relevant aspects of the system.

Smartphone manufacturers frequently customize Android distributions so as to create competitive advantages by adding, removing and modifying packages and configurations. In this paper we show that such modifications have deep architectural implications for security. We analysed five different distributions: Google Nexus 4, Google Nexus 5, Sony Z1, Samsung Galaxy S4 and Samsung Galaxy S5, all running OS versions 4.4.X (except for Samsung S4 running version 4.3). Our conclusions indicate that serious security issues such as expanded attack surface and poorer permission control grow sharply with the level of customization.

Some hard problems from lattices, like LWE (Learning with Errors), are particularly suitable for application in Cryptography due to the possibility of using worst-case to average-case reductions as evidence of strong security properties. In this work, we show two LWE-based constructions of zero-knowledge identification schemes and discuss their performance and security. We also highlight the design choices that make our solution of both theoretical and practical interest.

This paper introduces FORTUNA, a probabilistic framework that supports the conception and early design stages of hardware-based secure systems. FORTUNA can point out potential weaknesses of complex systems, involving physical and logical attacks, basic human interaction or even a few classes of unknown threats. FORTUNA consists of two main elements: a) a logical-probabilistic theoretic model in which quantitative and qualitative security assessments of hardware-based systems can be done; and b) a semiautomatic tool, based on the proposed model, that can assist secure system designing from the very initial development stages. To the best of our knowledge, FORTUNA is the first framework (and tool) to support such a broad scope of interactions and also the first aimed at the conception and early design phases of hardware-based systems. Other contributions include a proof of the “policy of least privileges” under our model and an example of use of the framework in the design of a secure microprocessor.

We present a hardware trusted computing base (TCB) aimed at Direct Recording Voting Machines (T-DRE), with novel design features concerning vote privacy, device verifiability, signed-code execution and device resilience. Our proposal is largely compliant with the VVSG (Voluntary Voting System Guidelines), while also strengthening some of its rec-comendations. To the best of our knowledge, T-DRE is the first architecture to employ multi-level, certification-based, hardware-enforced privileges to the running software. T-DRE also makes a solid case for the feasibility of strong security systems: it is the basis of 165,000 voting machines, set to be used in a large upcoming national election. In short, our contribution is a viable computational trusted base for both modern and classical voting protocols.

RAWVec is a private watermarking method for vector maps that uses a raster image as watermark. Visually recognizable watermarks can add extra information like integrity and authentication, while blind watermarks do not need the original data to be published for the detection. This work presents a semi-blind version of RAWVec, i.e. a method that uses the original vector map during the detection without revealing it, but maintains the watermark as a raster image.

After a few years of intense research, wireless sensor networks (WSNs) still demand new secure and cryptographic schemes. On the other hand, the advent of cryptography from pairings has enabled a wide range of novel cryptosystems. In this work we present TinyTate, the first known implementation of pairings for sensor nodes based on the 8-bit/7.3828-MHz ATmega128L microcontroller (e.g., MICA2 and MICAz motes). We then conclude that cryptography from pairings is indeed viable in resource-constrained nodes.

This paper presents two new algorithms for point compression for elliptic curves defined over F2m, m odd. The first algorithm works for curves with Tr(a) = 1 and offers computational advantages over previous methods. The second algorithm is based on the λ representation of an elliptic point. The proposed algorithms require m bits to compress an elliptic point and can be used for all random binary curves recommended by NIST.

Clustered sensor networks have been shown to increase system throughput, decrease system delay, and save energy. While those with rotating cluster heads, such as LEACH, have also advantages in terms of security, the dynamic nature of their communication makes most existing security solutions inadequate for them. In this paper, we show how random key predistribution, widely studied in the context of flat networks, can be used to secure communication in hierarchical (cluster-based) protocols such as LEACH. To our knowledge, it is the first work that investigates random key predistribution as applied to hierarchical WSNs

Fast algorithms for multiplication in finite fields are required for several cryptographic applications, in particular for implementing elliptic curve operations over binary fields F/sub 2m/. In this paper, we present new software algorithms for efficient multiplication over F/sub 2m/ that use a Gaussian normal basis representation. Two approaches are presented, direct normal basis multiplication and a method that exploits a mapping to a ring where fast polynomial-based techniques can be employed. Our analysis, including experimental results on an Intel Pentium family processor, shows that the new algorithms are faster and can use memory more efficiently than previous methods. Despite significant improvements, we conclude that the penalty in multiplication is still sufficiently large to discourage the use of normal bases in software implementations of elliptic curve systems.

The paper presents a scheme for the design, analysis and comparison of electronic payment systems. Three systems are described in detail through this scheme. PayWord is a micro payment system designed by R. Rivest and A. Shamir (1995). It is efficient for repeated payments to the same vendor, and is designed to reduce the use of public key algorithms through the use of hash functions and fast symmetric ciphers. Digicash's E-cash is one of the most popular electronic payment systems in use today. It is an Internet based system with full user anonymity by the use of blind signatures (D. Chaum, 1982). The central authority must apply a signature on a blinded user generated token. The Internet Keyed Protocol was designed by IBM's research labs. It is an adequate system for transactions using credit cards or account numbers on open networks, such as the Internet. iKP (P. Janson and M. Waidner, 1996) is in reality, a system that may be used to securely transmit account numbers on the Internet.