In this paper we focus on model risk and risk sensitivity when addressing the insurability of cyber risk. The standard statistical approaches to assessment
This study aims to develop an ML-centric approach for cyber risk assessment in construction projects, with four key objectives: (1) Develop ML models to process project characteristics and predict cyber risk degrees, ranging from 0 to 1, representing the probability of risk occurrence. (2) Use ...
which achieves 100% completeness of the mapping rule. It means that all secret messages codeword can be matched to at least one image in CIHDN’s image database, avoiding a risk of communication failure. Wu and Xue
· Consider qualitative and quantitative differentiating factors, including industries served, operational processes, product/service portfolio, business size, economic environment, and risk transfer mechanisms. · Document the qualitative and quantitative calculation approach and seek internal and legal counsel ...
Whether security-sensitive bytes are corrupted during the overflowIf only some non-pointer data is corrupted, there may be no security impacts on the running process. However, this is not absolute, as some bytes may be mistakenly used as pointers. The security risk is higher if pointers are ...
the framework models a graph to depict the dependenciesdiamongvi. The exploitability level is then assigned to each edge of the graph and is updated according to the formulaEi+1=max(E0(vi),min(E(di),Ei(Ei))), which indicates the risk of exploitation. Moreover, the approach enables scal...
the improved method has been deployed to the super computer Tianhe-2 to meet the service efficiency for the offshore petroleum risk management. Sufficient computing on resource Tianhe-2 supports the numerical simulation and spill source detection with massive parallel execution. The proposed hierarchical...
This definition of loss is in line with the well-known formula, risk = expected damage (I(t)) × probability of occurrence (T(t)) [21]. While the implementation of a cyber security control strengthens the defence of D’s organisation, it is associated with two types of costs namely; ...
The training dataset is utilized for the purpose of constructing the analytical models, while the validation dataset serves the purpose of fine-tuning the models and mitigating the risk of overfitting. Lastly, the test dataset shall be employed to assess the performance of the final model. High-...
This process helps mitigate the risk of key compromise and strengthens the overall security of the network. Key Management Systems: In real-world deployments, key management systems (KMS) may be employed to enhance key security and management. KMS solutions provide centralized control and protection ...