In this article, a modeling process is defined to address challenges in analyzing attack scenarios and mitigating vulnerabilities in networked environments. Known system vulnerability data, system configuration data, and vulnerability scanner results are considered to create exploitation graphs (e-graphs) that are used to represent attack scenarios. Experiments carried out in a cluster computin...

In general, automation involves less human intervention, which leads to dependence on preprogrammed machines and processes that operate continually carry out numerous tasks. This predictable repeating behavior can be used advantage. Due the incorporation of Internet Things into such automated processes, these cyber–physical systems are now vulnerable cyberattacks, patterns difficult identify un...

All node certificate based transitive signature schemes available in the literature make use of any digital signature scheme which is assumed to be provably secure against adaptive chosen-message attack, as a building block to produce node certificates in a graph. Consequently the algebraic structures to represent nodes in the graph are independent of the algebraic structure of signature scheme...

All node certificate based transitive signature schemes available in the literature make use of any digital signature scheme which is assumed to be provably secure against adaptive chosen-message attack, as a building block to produce node certificates in a graph. Consequently the algebraic structures to represent nodes in the graph are independent of the algebraic structure of signature scheme...

We propose a variational quantum attack algorithm (VQAA) for classical advanced encryption standard (AES)-like symmetric cryptography, as exemplified by the simplified-data (S-DES). In VQAA, known ciphertext is encoded ground state of Hamiltonian that constructed through regular graph, and can be found using approach. designed ansatz cost function S-DES’s attack. It surprising sometimes VQAA ev...

AND/OR graphs and minimum-cost solution graphs have been studied extensively in artificial intelligence (see, e.g., Nilsson [14]). Generally, the AND/OR graphs are used to model problem solving processes. The minimum-cost solution graph can be used to attack the problem with the least resource. However, in many cases we want to solve the problem within the shortest time period and we assume tha...

Graph representation learning, which maps high-dimensional graphs or sparse into a low-dimensional vector space, has shown its superiority in numerous learning tasks. Recently, researchers have identified some advantages of context-sensitive graph methods functions such as link predictions and ranking recommendations. However, most existing depend on convolutional neural networks recursive to o...