The performance of Group Diffie-Hellman paradigms: a software framework and analysis

A mobile computing environment typically involves groups of small, low-power devices interconnected through a mobile and dynamic network. Attempts to secure communication over these “ad-hoc” networks must be scalable to conserve the minimal resources of mobile devices as network sizes grow. In this project, the scalability of differing Group Diffie-Hellman security key generation implementations is examined. In theory, the implementation utilizing a data structure with the lowest theoretical run-time complexity for building the Diffie-Hellman group should prove the most scalable experimentally. A common modular framework was implemented to support generic Group Diffie-Hellman key agreement implementations abstracted from the underlying data structure and traversal mechanism. For comparison, linear, tree-based, and hypercubic Group Diffie-Hellman topologies were implemented and tested. Studies were conducted upon the results to compare the experimental scalability of each implementation to the other implementations as well as the theoretic predictions. The results indicate that the benefits of implementations with low theoretic-complexity are rarely experienced in smaller networks (less than 100 nodes,) and conversely implementations with high theoretic-complexities become unsuitable in larger networks (more than 100 nodes.) These experimental results match the theoretical predictions based on the mathematical properties of each implementation. Since mobile ad-hoc networks are typically small, less efficient, less complex implementations of Group Diffie-Hellman key agreement will suit most needs, however larger networks will require more efficient implementations

A Review on Biological Inspired Computation in Cryptology

Cryptology is a field that concerned with cryptography and cryptanalysis. Cryptography, which is a key technology in providing a secure transmission of information, is a study of designing strong cryptographic algorithms, while cryptanalysis is a study of breaking the cipher. Recently biological approaches provide inspiration in solving problems from various fields. This paper reviews major works in the application of biological inspired computational (BIC) paradigm in cryptology. The paper focuses on three BIC approaches, namely, genetic algorithm (GA), artificial neural network (ANN) and artificial immune system (AIS). The findings show that the research on applications of biological approaches in cryptology is minimal as compared to other fields. To date only ANN and GA have been used in cryptanalysis and design of cryptographic primitives and protocols. Based on similarities that AIS has with ANN and GA, this paper provides insights for potential application of AIS in cryptology for further research

SMCP: a Secure Mobile Crowdsensing Protocol for fog-based applications

The possibility of performing complex data analysis through sets of cooperating personal smart devices has recently encouraged the definition of new distributed computing paradigms. The general idea behind these approaches is to move early analysis towards the edge of the network, while relying on other intermediate (fog) or remote (cloud) devices for computations of increasing complexity. Unfortunately, because both of their distributed nature and high degree of modularity, edge-fog-cloud computing systems are particularly prone to cyber security attacks that can be performed against every element of the infrastructure. In order to address this issue, in this paper we present SMCP, a Secure Mobile Crowdsensing Protocol for fog-based applications that exploit lightweight encryption techniques that are particularly suited for low-power mobile edge devices. In order to assess the performance of the proposed security mechanisms, we consider as case study a distributed human activity recognition scenario in which machine learning algorithms are performed by users’ personal smart devices at the edge and fog layers. The functionalities provided by SMCP have been directly compared with two state-of-the-art security protocols. Results show that our approach allows to achieve a higher degree of security while maintaining a low computational cost

An efficient, secure and trusted channel protocol for avionics wireless networks

Avionics networks rely on a set of stringent reliability and safety requirements. In existing deployments, these networks are based on a wired technology, which supports these requirements. Furthermore, this technology simplifies the security management of the network since certain assumptions can be safely made, including the inability of an attacker to access the network, and the fact that it is almost impossible for an attacker to introduce a node into the network. The proposal for Avionics Wireless Networks (AWNs), currently under development by multiple aerospace working groups, promises a reduction in the complexity of electrical wiring harness design and fabrication, a reduction in the total weight of wires, increased customization possibilities, and the capacity to monitor otherwise inaccessible moving or rotating aircraft parts such as landing gear and some sections of the aircraft engines. While providing these benefits, the AWN must ensure that it provides levels of safety that are at minimum equivalent to those offered by the wired equivalent. In this paper, we propose a secure and trusted channel protocol that satisfies the stated security and operational requirements for an AWN protocol. There are three main objectives for this protocol. First, the protocol has to provide the assurance that all communicating entities can trust each other, and can trust their internal (secure) software and hardware states. Second, the protocol has to establish a fair key exchange between all communicating entities so as to provide a secure channel. Finally, the third objective is to be efficient for both the initial start-up of the network and when resuming a session after a cold and/or warm restart of a node. The proposed protocol is implemented and performance measurements are presented based on this implementation. In addition, we formally verify our proposed protocol using CasperFDR.Comment: 10 pages, 2 figures, 4 tables, IEEE DAS

A Secure Federated Data-Driven Evolutionary Multi-objective Optimization Algorithm

Data-driven evolutionary algorithms usually aim to exploit the information behind a limited amount of data to perform optimization, which have proved to be successful in solving many complex real-world optimization problems. However, most data-driven evolutionary algorithms are centralized, causing privacy and security concerns. Existing federated Bayesian algorithms and data-driven evolutionary algorithms mainly protect the raw data on each client. To address this issue, this paper proposes a secure federated data-driven evolutionary multi-objective optimization algorithm to protect both the raw data and the newly infilled solutions obtained by optimizing the acquisition function conducted on the server. We select the query points on a randomly selected client at each round of surrogate update by calculating the acquisition function values of the unobserved points on this client, thereby reducing the risk of leaking the information about the solution to be sampled. In addition, since the predicted objective values of each client may contain sensitive information, we mask the objective values with Diffie-Hellmann-based noise, and then send only the masked objective values of other clients to the selected client via the server. Since the calculation of the acquisition function also requires both the predicted objective value and the uncertainty of the prediction, the predicted mean objective and uncertainty are normalized to reduce the influence of noise. Experimental results on a set of widely used multi-objective optimization benchmarks show that the proposed algorithm can protect privacy and enhance security with only negligible sacrifice in the performance of federated data-driven evolutionary optimization.Comment: This paper has been accepted by IEEE Transactions on Emerging Topics in Computational Intelligence journa

Private and Secure Post-Quantum Verifiable Random Function with NIZK Proof and Ring-LWE Encryption in Blockchain

We present a secure and private blockchain-based Verifiable Random Function (VRF) scheme addressing some limitations of classical VRF constructions. Given the imminent quantum computing adversarial scenario, conventional cryptographic methods face vulnerabilities. To enhance our VRF's secure randomness, we adopt post-quantum Ring-LWE encryption for synthesizing pseudo-random sequences. Considering computational costs and resultant on-chain gas costs, we suggest a bifurcated architecture for VRF design, optimizing interactions between on-chain and off-chain. Our approach employs a secure ring signature supported by NIZK proof and a delegated key generation method, inspired by the Chaum-Pedersen equality proof and the Fiat-Shamir Heuristic. Our VRF scheme integrates multi-party computation (MPC) with blockchain-based decentralized identifiers (DID), ensuring both security and randomness. We elucidate the security and privacy aspects of our VRF scheme, analyzing temporal and spatial complexities. We also approximate the entropy of the VRF scheme and detail its implementation in a Solidity contract. Also, we delineate a method for validating the VRF's proof, matching for the contexts requiring both randomness and verification. Conclusively, using the NIST SP800-22 of the statistical randomness test suite, our results exhibit a 98.86% pass rate over 11 test cases, with an average p-value of 0.5459 from 176 total tests.Comment: 21 pages, 5 figures, In the 2023 Proceedings of International Conference on Cryptography and Blockchai

Choosing Secure Remote Access Technologies

This study proposes the need for secure remote communications to protect the data and information infrastructure of an organization. Several common remote access technologies are discussed, along with their various flaws and strengths. End-to-end encrypted VPN tunnels appear to be the most secure method of remote network access, and are discussed in terms of their performance and implementation details. A performance test for a VPN tunnel was performed to highlight the differences in network latency and throughput when additional levels of security are added. Cryptographic functions like hashing and Perfect Forward Secrecy are discussed and compared along with different cryptographic algorithms like DES and 3DES. Ultimately, the differences in performance between cryptographic configurations are slight, though could be amplified by network conditions

Survey on Hardware Implementation of Montgomery Modular

This paper gives the information regarding different methodology for modular multiplication with the modification of Montgomery algorithm. Montgomery multiplier proved to be more efficient multiplier which replaces division by the modulus with series of shifting by a number and an adder block. For larger number of bits, Modular multiplication takes more time to compute and also takes more area of the chip. Different methods ensure more speed and less chip size of the system. The speed of the multiplier is decided by the multiplier. Here three modified Montgomery algorithm discussed with their output compared with each other. The three methods are Iterative architecture, Montgomery multiplier for faster Cryptography and Vedic multipliers used in Montgomery algorithm for multiplication.Here three boards have been used for the analysis and they are Altera DE2-70, FPGA board Virtex 6 and Kintex 7