Synthesis of Covert Actuator Attackers for Free

In this paper, we shall formulate and address a problem of covert actuator attacker synthesis for cyber-physical systems that are modelled by discrete-event systems. We assume the actuator attacker partially observes the execution of the closed-loop system and is able to modify each control command issued by the supervisor on a specified attackable subset of controllable events. We provide straightforward but in general exponential-time reductions, due to the use of subset construction procedure, from the covert actuator attacker synthesis problems to the Ramadge-Wonham supervisor synthesis problems. It then follows that it is possible to use the many techniques and tools already developed for solving the supervisor synthesis problem to solve the covert actuator attacker synthesis problem for free. In particular, we show that, if the attacker cannot attack unobservable events to the supervisor, then the reductions can be carried out in polynomial time. We also provide a brief discussion on some other conditions under which the exponential blowup in state size can be avoided. Finally, we show how the reduction based synthesis procedure can be extended for the synthesis of successful covert actuator attackers that also eavesdrop the control commands issued by the supervisor.Comment: The paper has been accepted for the journal Discrete Event Dynamic System

Forward Intensity Model Monitoring Using Multivariate Exponential Weighted Moving Average Scheme

We propose a parameter monitoring method for the forward intensity model – the default probability prediction model of the Credit Research Initiative (CRI). We review the relative statistical process control scheme in the field of engineering. Based on this, we propose a new Multivariate Exponential Weighted Moving Average (MEWMA) scheme to monitor the forward intensity model monthly. This new chart might be applied to identify and diagnose the out-of-control (OC) parameters in real time as the data updating, which reduces the cost of recalculating all parameters and improve the operational and calculational efficiency of the default prediction models in practical application

Networked Supervisor Synthesis Against Lossy Channels with Bounded Network Delays as Non-Networked Synthesis

In this work, we study the problem of supervisory control of networked discrete event systems. We consider lossy communication channels with bounded network delays, for both the control channel and the observation channel. By a model transformation, we transform the networked supervisor synthesis problem into the classical (non-networked) supervisor synthesis problem (for non-deterministic plants), such that the existing supervisor synthesis tools can be used for synthesizing networked supervisors. In particular, we can use the (state-based) normality property for the synthesis of the supremal networked supervisors, whose existence is guaranteed by construction due to our consideration of command non-deterministic supervisors. The effectiveness of our approach is illustrated on a mini-guideway example that is adapted from the literature, for which the supremal networked supervisor has been synthesized in the synthesis tools SuSyNA and TCT.Comment: This paper is under review for Automatic

Proposing a New Research Framework for Loan Allocation Strategies in P2P Lending

One of the frontier Web 2.0 applications is online peer-to-peer (P2P) lending marketplace, where individual lenders and borrowers can virtually meet for loan transactions. From a lender’s perspective, she not only wants to lower investment risk but also to gain as much return as possible. However, P2P lenders possess the inherent problem of information asymmetry that they don’t really know if a borrower has capability to pay the loan or is truthfully willing to pay it in due time, leading them to a disadvantaged situation when making the decision of lending money to the borrower. This study intends to consider the loan allocation as an optimization research problem using the research framework based upon modern portfolio theory with the aim of helping lenders achieve the two goals of gaining high return and lowering risk at the same time. The expected results of this research are twofold: 1) compared to a logistic regression based credit scoring method, we expect to make more profits for lenders with risk level unchanged, and 2) compared to a linear regression based profit scoring method, we expect to lower risk without lowering return. Our proposed new model could offer insights into how individual lenders can optimize their loan allocation strategies when considering return and risk simultaneously

Using Glycated Albumin and Stimulated C-Peptide to Define Partial Remission in Type 1 Diabetes

ObjectiveTo propose a new definition of partial remission (PR) for patients with type 1 diabetes (T1D) of all-ages using insulin dose and glycated albumin (GA), and find the optimal cut-off values for stimulated C-peptide to diagnose PR in different age-groups.Research Design and MethodsPatients with newly diagnosed T1D (n=301) were included. GA/insulin dose was used to diagnose PR, and insulin dose-adjusted glycated albumin (IDAGA) was proposed to facilitate clinical application. The optimal diagnostic levels of IDAGA and stimulated C-peptide were determined in different age-groups (≤ 12y, 12-18y and ≥ 18y). Furthermore, the diagnostic consistency between different PR definitions was studied.ResultsGA≤ 23%/insulin dose ≤ 0.5u/kg/day was used to define PR, and IDAGA (GA (%) + 40 * insulin dose(u/kg/day)) ≤ 40 was feasible in all age-groups. Whereas, the optimal diagnostic level showed difference for stimulated C-peptide (265.5, 449.3 and 241.1 pmol/L for the ≤ 12y, 12-18y and ≥ 18y age-group, respectively). About 40% of patients met the PR definition by stimulated C-peptide but not GA/insulin dose or IDAGA, who showed dyslipidemia and higher insulin resistance.ConclusionsA new definition of the PR phase is proposed using GA/insulin dose, and the calculated IDAGA≤ 40 applies to all age-groups. The stimulated C-peptide to diagnose PR is the highest in the 12-18y age-group, which reflects the effect of puberty on metabolism. For patients with insulin resistance, it is not recommended to use stimulated C-peptide alone to diagnose PR