The resilience of cyberphysical systems (CPS) to denial of service (DoS) and integrity attacks is studied. The CPS is modeled as a linear structured system, and its resilience to various attack scenarios is interpreted in a graph theoretical framework. The structural resilience of the CPS to DoS and integrity attacks is characterized in terms of unmatched vertices in maximum matchings of the bi...

Constructing an efficient and accurate model from security events to determine an attack scenario for an enterprise network is challenging. In this paper, we discuss how to use the information obtained from security events to construct an attack scenario and build an evidence graph. To achieve the accuracy and completeness of the evidence graph, we use Prolog inductive and abductive reasoning t...

An attack graph depicts multiple-step attack and provides a description of system security vulnerabilities. It illustrates critical information necessary to identify potential weaknesses and areas for enhanced defense. Attack graphs include multiple attack paths, which are a focus for further detailed analysis and risk mitigation. Considering that different vulnerabilities have different probab...

Graph neural networks (GNNs) have shown significant performance in various practical applications due to their strong learning capabilities. Backdoor attacks are a type of attack that can produce hidden on machine models. GNNs take backdoor datasets as input an adversary-specified output poisoned data but perform normally clean data, which grave implications for applications. under-researched t...

A transitive signature scheme allows a signer to publish a graph in an authenticated and cost-saving manner. The resulting authenticated graph is indeed the transitive closure of the graph constructed by edges which are explicitly signed by the signer. A property of the transitive signature scheme enables such scenario is called composability which means that by knowing signatures on two edges ...