Identification of Important FPGA Modules Based on Complex Network

The globalization of hardware designs and supply chains,as well as the integration of third-party intellectual property(IP)cores,has led to an increased focus from malicious attackers on computing hardware.However,existing defense or detection approaches often require additional circuitry to perform security verification,and are thus constrained by time and resource limitations.Considering the scale of actual engineering tasks and tight project schedules,it is usually difficult to implement designs for all modules in field programmable gate array(FPGA)circuits.Some studies have pointed out that the failure of key modules tends to cause greater damage to the network.Therefore,under limited conditions,priority protection designs need to be made on key modules to improve protection efficiency.We have conducted research on FPGA designs including single FPGA systems and multi-FPGA systems,to identify key modules in FPGA systems.For the single FPGA designs,considering the topological structure,network characteristics,and directionality of FPGA designs,we propose a node importance evaluationmethod based on the technique for order preference by similarity to an ideal solution(TOPSIS)method.Then,for the multi-FPGA designs,considering the influence of nodes in intra-layer and inter-layers,they are constructed into the interdependent network,and we propose a method based on connection strength to identify the important modules.Finally,we conduct empirical research using actual FPGA designs as examples.The results indicate that compared to other traditional indexes,node importance indexes proposed for different designs can better characterize the importance of nodes.

CoRE:Constrained Robustness Evaluation of Machine Learning-Based Stability Assessment for Power Systems

Dear Editor,Machine learning(ML) approaches have been widely employed to enable real-time ML-based stability assessment(MLSA) of largescale automated electricity grids. However, the vulnerability of MLSA to malicious cyber-attacks may lead to wrong decisions in operating the physical grid if its resilience properties are not well understood before deployment. Unlike adversarial ML in prior domains such as image processing, specific constraints of power systems that the attacker must obey in constructing adversarial samples require new research on MLSA vulnerability analysis for power systems.

Impact Analysis of MTD on the Frequency Stability in Smart Grid

Dear Editor, In order to accommodate the effects of false data injection attacks(FDIAs), the moving target defense(MTD) strategy is recently proposed to enhance the security of the smart grid by perturbing branch susceptances. However, most pioneer work only focus on the defending performance of MTD in terms of detecting FDIAs and the impact of MTD on the static factors such as the power and economic losses.

Detecting the One-Shot Dummy Attack on the Power Industrial Control Processes With an Unsupervised Data-Driven Approach

Dear Editor,Dummy attack(DA), a deep stealthy but impactful data integrity attack on power industrial control processes, is recently recognized as hiding the corrupted measurements in normal measurements. In this letter, targeting a more practical case, we aim to detect the oneshot DA, with the purpose of revealing the DA once it is launched.Specifically, we first formulate an optimization problem to generate one-shot DAs. Then, an unsupervised data-driven approach based on a modified local outlier factor(MLOF) is proposed to detect them.

长链非编码RNA-p21调控微小RNA-9/去乙酰化酶1信号通路逆转结直肠癌细胞奥沙利铂耐药性

目的探讨长链非编码RNA(LncRNA)-p21调控微小RNA-9(miR-9)/去乙酰化酶1(SIRT1)信号通路逆转结直肠癌(CRC)奥沙利铂相关的细胞自噬及耐药性的分子机制。方法采用qPCR方法LncRNA-p21的表达检测,Westbloting blotting法检测细胞自噬相关蛋白(微管相关蛋白1轻链3-Ⅰ((LC3-I)、微管相关蛋白1轻链3-Ⅱ(LC3-Ⅱ)),自噬底物(P62)、去乙酰化酶1(Sirtuin-1,SIRT1)、miR-9的表达水平;克隆形成实验检测细胞活性。结果(1)LncRNA-p21在奥沙利铂耐药的结直肠肿瘤细胞HCT116,SW620中高表达,差异有统计学意义(P<0.001);(2)敲降LncRNA-p21可抑制细胞自噬,改善HCT116细胞对奥沙利铂的化疗敏感性;(3)敲降LncRNA-p21后miR-9表达上调,而miR-9过表达可增强HCT116细胞对奥沙利铂的化疗敏感性,差异有统计学意义(P<0.001);(4)同时,SIRT1的表达受到LncRNA-p21和miR-9的调控。结论结直肠肿瘤对于化疗药奥沙利铂抵抗可能由LncRNA-p21诱导细胞自噬增强而引起,其过程可能通过LncRNA-p21调控miR-9/SIRT1信号通路而实现。

Detection and localization of cyber attacks on water treatment systems:an entropy-based approach

With the advent of Industry 4.0,water treatment systems(WTSs)are recognized as typical industrial cyber-physical systems(iCPSs)that are connected to the open Internet.Advanced information technology(IT)benefits the WTS in the aspects of reliability,efficiency,and economy.However,the vulnerabilities exposed in the communication and control infrastructure on the cyber side make WTSs prone to cyber attacks.The traditional IT system oriented defense mechanisms cannot be directly applied in safety-critical WTSs because the availability and real-time requirements are of great importance.In this paper,we propose an entropy-based intrusion detection(EBID)method to thwart cyber attacks against widely used controllers(e.g.,programmable logic controllers)in WTSs to address this issue.Because of the varied WTS operating conditions,there is a high false-positive rate with a static threshold for detection.Therefore,we propose a dynamic threshold adjustment mechanism to improve the performance of EBID.To validate the performance of the proposed approaches,we built a high-fidelity WTS testbed with more than 50 measurement points.We conducted experiments under two attack scenarios with a total of 36attacks,showing that the proposed methods achieved a detection rate of 97.22%and a false alarm rate of 1.67%.