Blockchain Technologies: Potential Use of Cryptographic Protocol in Financing Forests Conservation Stewardship

Environmental markets that consider trade-offs of benefits flow and conservation burdens among economic units contributes to the sustainability of natural resource capital. Despite the benefits of environmental markets, the existence of bureaucratic processes in ecosystem financing such as Payment for Environmental Services creates a perverse market structure, which impedes the efforts of internalising environmental costs through distributional effects of conservation rewards and burdens among economic units. Therefore, this paper explores the applicability of using cryptographic protocols in blockchain technologies as a paradigm shift in financing conservation stewardship at the micro-level. Secondary data from documented literature was used as the source of information in this study. Systematic searches on different websites were used to identify relevant scientific papers, journals, abstracts, reports and presentations that resonated with the theme of this study. To gain hands-on information regarding blockchain technologies, the snowballing research design was used to identify individuals with technological know-how on the functionality and blockchain operability. Blockchain technologies can be merited because it portrays a high degree of transparency and trustworthiness among economic units when used in environmental markets. Therefore, designing a robust cryptographic protocol that facilitates efficient trade-offs of conservation rewards and burdens in present environmental market creates incentives for the resource conservation and protection.

AriaNN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing

We propose AriaNN, a low-interaction privacy-preserving framework for private neural network training and inference on sensitive data. Our semi-honest 2-party computation protocol (with a trusted dealer) leverages function secret sharing, a recent lightweight cryptographic protocol that allows us to achieve an efficient online phase. We design optimized primitives for the building blocks of neural networks such as ReLU, MaxPool and BatchNorm. For instance, we perform private comparison for ReLU operations with a single message of the size of the input during the online phase, and with preprocessing keys close to 4× smaller than previous work. Last, we propose an extension to support n-party private federated learning. We implement our framework as an extensible system on top of PyTorch that leverages CPU and GPU hardware acceleration for cryptographic and machine learning operations. We evaluate our end-to-end system for private inference between distant servers on standard neural networks such as AlexNet, VGG16 or ResNet18, and for private training on smaller networks like LeNet. We show that computation rather than communication is the main bottleneck and that using GPUs together with reduced key size is a promising solution to overcome this barrier.

Experience of Implementation of the Protocol TLS 1.3 Verification

This paper presents the experience of verifying server implementations of the TLS cryptographic protocol version 1.3. TLS is a widely used cryptographic protocol designed to create secure data transmission channels and provides the necessary functionality for this: confidentiality of the transmitted data, data integrity, and authentication of the parties. The new version 1.3 of the TLS protocol was introduced in August 2018 and has a number of significant differences compared to the previous version 1.2. A number of TLS developers have already included support for the latest version in their implementations. These circumstances make it relevant to do research in the field of verification and security of the new TLS protocol implementations. We used a new test suite for verifying implementations of the TLS 1.3 for compliance with Internet specifications, developed on the basis of the RFC8446, using UniTESK technology and mutation testing methods. The current work is part of the TLS 1.3 protocol verification project and covers some of the additional functionality and optional protocol extensions. To test implementations for compliance with formal specifications, UniTESK technology is used, which provides testing automation tools based on the use of finite state machines. The states of the system under test define the states of the state machine, and the test effects are the transitions of this machine. When performing a transition, the specified impact is passed to the implementation under test, after which the implementation's reactions are recorded and a verdict is automatically made on the compliance of the observed behavior with the specification. Mutational testing methods are used to detect non-standard behavior of the system under test by transmitting incorrect data. Some changes are made to the protocol exchange flow created in accordance with the specification: either the values of the message fields formed on the basis of the developed protocol model are changed, or the order of messages in the exchange flow is changed. The protocol model allows one to make changes to the data flow at any stage of the network exchange, which allows the test scenario to pass through all the significant states of the protocol and in each such state to test the implementation in accordance with the specified program. So far, several implementations have been found to deviate from the specification. The presented approach has proven effective in several of our projects when testing network protocols, providing detection of various deviations from the specification and other errors.

Lightweight Cryptography for the Encryption of Data Communication of IoT Devices

We are at the beginning of the age of the Internet of things. Soon, we will be surrounded by smart homes, cities, and infrastructure. To achieve this vision, millions of devices will have to be able to communicate with each other. The demands for communication channels will increase significantly. An increasing amount of data will be transmitted with a requirement of minimal delay. The capacities of transmission systems can be quickly depleted. Building new communication channels is very time consuming but also financially demanding. To maximize existing infrastructure, we should pay attention today to the issue of transmitted data. One of the ways is to focus attention on reducing the volume of transmitted data. In this paper, we present a method of reducing the volume of data transmission between a server and an IoT device, focusing on the bandwidth, transmission security, and system resources of the IoT device. The required reduction is achieved by data compression and replacing the SSL/TLS cryptographic protocol with lightweight cryptography based on the Vernam cipher principle. The original SSL/TLS protocol is still used for device management needs only.

Fair and Secure Multi-Party Computation with Cheater Detection

Secure multi-party computation (SMC) is a cryptographic protocol that allows participants to compute the desired output without revealing their inputs. A variety of results related to increasing the efficiency of SMC protocol have been reported, and thus, SMC can be used in various applications. With the SMC protocol in smart grids, it becomes possible to obtain information for load balancing and various statistics, without revealing sensitive user information. To prevent malicious users from tampering with input values, SMC requires cheater detection. Several studies have been conducted on SMC with cheater detection, but none of these has been able to guarantee the fairness of the protocol. In such cases, only a malicious user can obtain a correct output prior to detection. This can be a critical problem if the result of the computation is real-time information of considerable economic value. In this paper, we propose a fair and secure multi-party computation protocol, which detects malicious parties participating in the protocol before computing the final output and prevents them from obtaining it. The security of our protocol is proven in the universal composability framework. Furthermore, we develop an enhanced version of the protocol that is more efficient when computing an average after detecting cheaters. We apply the proposed protocols to a smart grid as an application and analyze their efficiency in terms of computational cost.

Asymmetric cryptographic protocols with a blockchain core: development problems and their solutions

The problem of axiomatic construction of secure cryptographic protocols is closely related to the choice of basic cryptographic blocks from which a cryptographic protocol of arbitrary complexity can be built. Let’s call such blocks primitive cryptographic protocols. Along with a traditional choice as primitive secret sharing protocols and non-interactive proof protocols today blockchain is considered to be a primitive cryptographic protocol. The security of such cryptographic protocols with a blockchain core is studied a bit today. We consider the methods for increasing the security of protocols with blockchain core by using a new agreement protocol in the blockchain, which is secure in the information theoretically sense.

RV-TEE: secure cryptographic protocol execution based on runtime verification

Analytical security of cryptographic protocols does not immediately translate to operational security due to incorrect implementation and attacks targeting the execution environment. Code verification and hardware-based trusted execution solutions exist, however these leave it up to the implementer to assemble the complete solution, imposing a complete re-think of the hardware platforms and software development process. We rather aim for a comprehensive solution for secure cryptographic protocol execution, which takes the form of a trusted execution environment based on runtime verification and stock hardware security modules. RV-TEE can be deployed on existing platforms and protocol implementations. Runtime verification lends itself well at several conceptual levels of the execution environment, ranging from high level protocol properties, to lower level checks such as taint inference. The proposed architectural setup involving two runtime verification modules is instantiated through a case study using a popular web browser. We successfully monitor high and low level properties with promising results with respect to practicality.