Intermittent Attacks Research Articles

Optimal Intermittent Deception Attacks With Energy Constraints for Cyber-Physical Systems

Optimal Intermittent Deception Attacks With Energy Constraints for Cyber-Physical Systems

Distributed-observer-based adaptive fault tolerant formation maneuver for autonomous surface vehicles under stochastic cyber-attack

This paper investigates the distributed adaptive fault-tolerant formation maneuver control strategy for multiple autonomous surface vehicles (ASVs) systems subject to stochastic cyber-attack and actuator failures. Existing works have provided solutions against continuous attacks on communication channels while ignoring the increasingly prevalent intermittent attacks. Compared to the former, the latter are more challenging to detect, having been insufficiently described and addressed. Motivated by this observation, this article is concerned with the stochastic intermittent injection attacks, which are modeled as stochastic impulsive sequences, characterized by stochastic injection instant and intensity, leading to unpredictable changes in the state information transmitted by the neighbors. Taking this dilemma into consideration, a novel distributed observer is proposed, capable of effectively observing the target formation even in the presence of stochastic intermittent injection attacks. Meanwhile, a large feedback gain is incorporated into the observer to reduce the impact of attacks on system stability. A linear sliding manifold, together with the adaptive algorithm, is utilized to construct a fault tolerant control architecture for each follower ASV without employing model parameters which can confront the embarrassing scenario of actuator failures. Eventually, theoretical deduction and numerical simulations are conducted to confirm the feasibility of the proposed collaborative control scheme.

Zero-Sum-Game-Based Distributed Fuzzy Adaptive Self-Triggered Control of Swarm UAVs Under Intermittent Communication and DoS Attacks

Zero-Sum-Game-Based Distributed Fuzzy Adaptive Self-Triggered Control of Swarm UAVs Under Intermittent Communication and DoS Attacks

Secure pinning synchronization on aperiodic intermittent event-triggered control in discrete-time complex networks against multi-pattern link attacks

This paper investigates the problem of secure synchronization in aperiodic intermittent event-triggered pinning control for discrete-time complex networks (DCNs) against multi-pattern link attacks. Firstly, in order to reduce communication burden and control cost, a novel aperiodic intermittent event-triggered control (AIEC) with discontinuous characteristics is designed based on periodic sampling, where triggering instants are determined by the intermittent control (IC). Secondly, multiple pattern attack are modeled, as they can interrupt different edges and change the network topology. In addition, multi-pattern attacks for each link are independent and their impact on the coupling topology is analyzed. Thirdly, under destroyed network topology, this paper designs aperiodic intermittent event-triggered pinning control (AIEPC) by combining pinning control (PC) with the AIEC. Meanwhile, based on PC, the isolated node and pinned nodes form a like-directed spanning tree with an asymmetrical coupling matrix, where rooted at the isolated node and only directed connections between the isolated node and pinned nodes. Fourthly, using the segmentation analysis method and the inequality iteration technique, a sufficient condition for exponential synchronization of error system is obtained by considering the instants neighboring different intermittent control and attack intervals. Finally, a simulation example on Chua’s circuit network is provided to verify the validity of the theoretical results achieved in this paper.

Adaptive quantized control based on output feedback for nonlinear systems with sensor faults under intermittent DoS attacks

AbstractQuantized signal control has been widely recognized as an effective means for conserving communication resources. However, ensuring stability of quantization‐driven nonlinear systems becomes particularly challenging in the presence of intermittent denial‐of‐service (DoS) attacks and sensor failures. This article explores the stable control problem of quantized nonlinear systems subject to DoS attacks. When an attack exists, all signals are unmeasurable. During the dormant phase of a DoS attack, only the quantized output signal is measurable, while there is a deviation between the received signal and the ideal signal due to sensor failure. To address these challenges, a switch‐type quantized observer is designed in this article to estimate unmeasurable state signals. In addition, we integrate the first‐order dynamic filter into the back‐stepping design process, which not only avoid the obstacles arisen from non‐differentiable output signals, but also simplifies the design process. Furthermore, this article adopts a more flexible sector quantizer and derives a set of adaptive laws to compensate for unknown quantization parameters. It is shown that, by utilizing the estimated signal, the proposed quantized adaptive control is able to effectively fight against DoS attacks and also is fault‐tolerant to sensor failures, guaranteeing semi‐globally uniformly ultimately bounded for all closed‐loop signals. Finally, simulation results validate the effectiveness of the proposed theory.

Distributed quantized secure bipartite consensus of linear multi‐agent systems with switching topologies and sequential scaling attacks

AbstractThis paper considers the secure distributed control consensus problem of linear multi‐agent systems (MASs) under switching topologies, subject to intermittent sequential scaling attacks, which was compelled to scaling factor, attack frequency, duration and cooperative‐competitive networks. First, the scenario of a fixed topology is considered, and a novel control protocol combined with a logarithmic quantizer and relative state measurements of neighbouring agents is discussed. The sighed graph is utilized to characterize the communication topology determined by the information flow directions and captured by the graph Laplacian matrix. After that, sufficient conditions for effectiveness of the developed control methods in guiding the MASs to secure bipartite leader‐following consensus are constructed. Second, the scenario of switching topologies is considered, and it is derived that the secure bipartite consensus will be achieved if the designed state feedback control protocol with the scaling factor, the attack duration, attack frequency and switching signal are selected properly. At last, to prove the effectiveness of the designed controllers, a simulation example depended on the real‐word actual military is introduced.

Residual-Based Detection of Attacks in Cyber-Physical Inverter-Based Microgrids

This paper discusses the challenges faced by cyber-physical microgrids (MGs) due to the inclusion of information and communication technologies in their already complex, multi-layered systems. The work identifies a research gap in modeling and analyzing stealthy intermittent integrity attacks in MGs, which are designed to maximize damage and cancel secondary control objectives. To address this, the paper proposes a nonlinear residual-based observer approach to detect and mitigate such attacks. In order to ensure a stable operation of the MG, the formulation then incorporates stability constraints along with the detection observer. The proposed design is validated through case studies on a MG benchmark with four distributed generators, demonstrating its effectiveness in detecting attacks while satisfying network and stability constraints.

Event-Triggered Reverse Attacks on Remote State Estimation

Security issues in cyber-physical systems have attracted increasing attention in recent years. In this paper, a security problem in a remote estimation application is considered, where an attacker tries to degrade estimation performance via malicious attacks. In our scenario, a smart sensor transmits its innovation to a remote estimator with a residue-based false data detector. Instead of assuming that the attacker launches a consecutive man-in-the-middle attack, we consider the case with intermittent attacks. Reverse attack is a simple attack strategy, which enables an attacker to change signs of the innovation sequences. Therefore, owing to the above reasons, an event-triggered reverse attack strategy is proposed to degrade system performance. First, the stealthiness of the event-triggered linear deception attack strategy is studied. Then, the evolution of the estimation error covariance is computed and the reverse attack is proven to be the optimal linear deception attack. We demonstrate that our event-triggered reverse attack is more destructive than a random reverse attack. Furthermore, a convex optimization problem is established to design event-triggered parameters. Comparisons of attack strategies are provided in a numerical example to validate the superiority of the reverse attack.

Finite-time switching-like sliding mode fault-tolerant control for discrete-time cyber-physical systems under DoS attacks and intermittent faults

In this article, the finite-time sliding mode fault-tolerant control problem is addressed for discrete-time cyber-physical systems with intermittent faults and denial-of-service (DoS) attacks. To model the intermittent nature of faults, two sequences of shifted gate functions are employed to depict the fault appearance and disappearance moments. Considering that DoS attacks can prevent transmission of signals, resulting in measurement data losses over the sensor to observer channel, switching-like observer and sliding mode fault-tolerant controller are presented to accommodate both situations with and without attacks. The designed sliding mode fault-tolerant controller can ensure the finite-time reachability of the sliding surface such that it can enter the quasi-sliding mode domain within finite time from any initial state. Moreover, based on the Lyapunov theory, sufficient criteria are derived to guarantee the finite-time boundedness of the closed-loop systems with intermittent faults and DoS attacks in both the reaching and sliding motion phases. Finally, the effectiveness of the proposed sliding mode fault-tolerant control scheme is verified by a numerical example and a practical example.

Detection and Localization of Hardware-Assisted Intermittent Power Attacks in Mixed-Critical Systems

Detection and Localization of Hardware-Assisted Intermittent Power Attacks in Mixed-Critical Systems

Distributed observer for LTI systems under stochastic impulsive sequential attacks

In this paper, we consider the distributed state estimation problem of continuous-time linear time-invariant (LTI) systems, where communication channels are attacked by stochastic impulsive sequences. In a networked system, the communication channel between an agent and its neighbor is vulnerable to being attacked. Continuous attacks have been widely studied so far, but with the development of attack techniques, intermittent attacks have been emerging, which are more difficult to be identified and detected, and have not been well portrayed and studied. Therefore, this paper investigates a random intermittent injection attack, which leads to abrupt and random changes of the state information transmitted by the neighbors. First, this attack is modeled as a stochastic impulsive sequential attack, where both its impulsive time and impulsive intensity are random. Then a distributed observer under stochastic impulsive sequential attack is proposed. Since the impulsive attack destroys the stability of the system, in order to attenuate the impact of the impulsive attack, a large feedback gain is necessary. By using the graph theory, matrix theory and stochastic analysis, sufficient conditions for the existence of the distributed observer in the sense of mean square and in the sense of almost sure are presented, respectively. Finally, the effectiveness of the proposed distributed observer is verified by numerical simulations.

A rare case of β-ketothiolase deficiency presenting as mimicker of diabetic ketoacidosis

β-ketothiolase (3-oxothiolase, BKT), also called mitochondrial acetoacetyl-coenzyme-A thiolase (T2), is a mitochondrial enzyme involved in isoleucine catabolism and ketone metabolism. BKT or T2 deficiency is inherited as an autosomal recessive trait and results in a rare inborn error of metabolism called alpha-acetoacetic aciduria. Patients with this disorder usually present with intermittent attacks of ketoacidosis. Here, we report a case of BKT deficiency that mimicked diabetic ketoacidosis (DKA) at presentation and discuss the clinical profile and interpretation of laboratory findings. An 8-month-old male child presented with seizures, coma, hyperglycemia, shock, and high anion gap metabolic acidosis with normal serum lactate and negative urinary ketone requiring correction with sodium bicarbonate, management of shock and sepsis, and mechanical ventilation. During his stay in the hospital, he developed ketonuria and episodes of hypoglycemia on a glucose insulin infusion with persistent metabolic acidosis which prompted us to look for an inborn error of metabolism, as hemoglobin A1C (HbA1C) and C-peptide levels were normal. Both tandem mass spectrometry (TMS) and urinary gas chromatography mass spectrometry (GCMS) were confirmatory. Diagnosis of BKT deficiency was further confirmed with genetic testing which revealed a novel homozygous mutation in the acetyl-CoA acetyltransferase 1 (ACAT1) gene. In infants manifesting with clinical features of diabetic ketoacidosis (DKA), cautious interpretation of laboratory findings and consideration of inborn errors of metabolism including the rare BKT deficiency are needed for a favorable outcome and prediction of prognosis.

Clinicopathologic Features, Genetics, Treatment, and Long-Term Outcomes in Japanese Children and Young Adults with Benign Recurrent Intrahepatic Cholestasis: A Multicenter Study.

Few reports of benign recurrent intrahepatic cholestasis (BRIC) have focused on East Asian patients. We describe the clinicopathologic features, genetics, treatment, and outcomes in Japanese BRIC patients. We recruited patients with BRIC type 1 (BRIC-1) or 2 (BRIC-2) treated at four pediatric centers and one adult center between April 2007 and March 2022. Demographics, clinical course, laboratory results, molecular genetic findings concerning ATP8B1 and ABCB11 genes, histopathology, and treatment response were examined retrospectively. Seven Japanese patients with BRIC were enrolled (four male, three female; four BRIC-1 and three BRIC-2). The median age at onset for BRIC-1 was 12 years; for BRIC-2, it was 1 month. Intermittent cholestatic attacks numbered from one to eight during the 11 years of median follow-up. Six patients received a mainstream education; only one patient attended special education. None developed cirrhosis. Three with BRIC-1 showed compound heterozygosity for a variant ATP8B1 gene, while one was heterozygous; two BRIC-2 patients showed compound heterozygosity in ABCB11 and one was heterozygous. Liver biopsy specimens obtained during cholestatic attacks showed fibrosis varying from none to moderate; inflammation was absent or mild. Rifampicin administered to three patients for cholestatic attacks was effective in all, as was cholestyramine in two of three. To our knowledge, this is the first East Asian multicenter study of BRIC patients. Onset age and number of cholestatic attacks varied. Rifampicin and cholestyramine were effective against attacks. No patient developed cirrhosis; most had normal growth and development. The long-term outcomes were satisfactory.

Fixed-Time Synchronization of Multilayer Complex Networks Under Denial-of-Service Attacks

This paper addresses the fixed-time synchronization (FXTS) problem of multilayer complex networks (MCNs) under denial-of-service (DoS) attacks. Generally, when a control strategy is introduced, it will be affected by DoS attacks. Considering the DoS attacks that occur in the control channel, the model of MCNs under DoS attacks is constructed. Using the average non-attack rate of intermittent attacks and the Lyapunov method, the fixed-time convergence theorem is given to achieve the FXTS of the MCNs. The results indicate that the settling time has a connection with the controller parameters and the attack parameters. Moreover, we find that the higher the average non-attack rate of the intermittent attacks, the shorter the settling time of FXTS. Besides, the energy consumption of the control strategy is estimated. Finally, the feasibility of the theoretical results is verified by Chua’s circuit in numerical simulations.

Cessation of ocular hypertensive attacks following iStent trabecular micro-bypass stent implantation in a patient with Posner-Schlossman syndrome: a case report

Background: Posner-Schlossman syndrome (PSS) is an ocular condition with self-limiting recurrent episodes of markedly elevated intraocular pressure (IOP) and non-granulomatous anterior chamber inflammation. Surgical treatment is indicated if medical therapy fails to control IOP.
 Case presentation: A 58-year-old male presented with intermittent attacks of blurred vision and pain in the right eye for 6 months. Examination revealed keratic precipitates with IOP of 56 mmHg in the right eye. Gonioscopy revealed open angles in both eyes. Erythrocyte sedimentation rate was within normal limits, while aqueous tapfor viral PCR, rapid plasma reagent test, and Mantoux test were negative. IOP was in the high-teens (inappropriate) on 2 topical antiglaucoma medications and the patient developed ocular surface problems. iStent was implanted. IOP remained stable within the mid-teens with no further episodes of raised IOP in the following 6 months.
 Conclusion: This case showed cessation of ocular hypertensive attacks in PSS after iStent implantation.

The role of cochlear implantation in alleviating Tumarkin drop attacks of Meniere's disease; a case report

Ménière's disease (MD) patients may suffer episodes of sudden falls, named Tumarkin drop attacks (DAs). This fall occurs abruptly and without warning or loss of consciousness. DAs usually aggravate the clinical picture of MD and are challenging to manage. The present report describes a case treated by cochlear implantation (CI) due to concomitant deafness and offers some clinical considerations for this condition. A male patient aged 48 years with a 10-year history of definite bilateral MD had profound SNHL on the right and severe SNHL on the left side. He suffered from intermittent attacks of vertigo, ear fullness, and tinnitus and, in the last year, had developed DAs and experienced 14 episodes in the previous six months. The preoperative category of acoustic performance was 3. The Dizziness Handicap Inventory (DHI) questionnaire showed a total score of 46, which indicated a moderate degree of disability. A CI was planned for the right side. The patient did not report any further DAs episode for two years since then. The postoperative category of acoustic performance became 11, and the postoperative DHI questionnaire showed a decrease in the total score (from 46 to 19), which indicated a mild disability. Unilateral CI effectively alleviated the DAs associated with bilateral MD. Our report proposes a new modality for managing vertiginous symptoms in cases of MD with hearing loss without the need for more aggressive surgical interventions with the need for clinical trials to confirm our results.

Differentially expressed microRNAs in peripheral blood cell are associated with downregulated expression of IgE in nonallergic childhood asthma

Childhood asthma is a heterogeneous disease characterized by chronic airway inflammation, leading to a broad range of clinical presentations. Nonallergic asthma is asthma without allergic sensitization. Both clinical manifestations and immunopathological mechanisms of nonallergic childhood asthma were rarely investigated. We aimed to compare the clinical features between nonallergic and allergic childhood asthma and apply microRNA to explore the underlying mechanism of nonallergic childhood asthma. We enrolled 405 asthmatic children (76 nonallergic, 52 allergic with total IgE < 150 IU/mL and 277 allergic with total IgE > 150 IU/mL). Clinical characteristics were compared between groups. Comprehensive miRNA sequencing (RNA-seq) was performed using peripheral blood from 11 nonallergic and 11 allergic patients with elevated IgE, respectively. Differentially expressed miRNA (DEmiRNA) were determined with DESeq2. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis was performed to determine functional pathways involved. Publicly available mRNA expression data was applied to investigate the predicted target mRNA networks via Ingenuity Pathway Analysis (IPA). The average age of nonallergic asthma was significantly younger (5.614 ± 2.743 vs 6.676 ± 3.118 years-old). Higher severity and worse control were more common in nonallergic asthma (two-way ANOVA, P < 0.0001). Long-term severity was higher, and intermittent attacks persisted in nonallergic patients. We identified 140 top DEmiRNAs based on false discovery rate (FDR) q-value < 0.001. Forty predicted target mRNA gene were associated with nonallergic asthma. The enriched pathway based on GO included Wnt signaling pathway. IgE expression was predicted to be downregulated by a network involving simultaneous interaction with IL-4, activation of IL-10 and inhibition of FCER2. Nonallergic childhood asthma were distinct in their younger age, higher long-term severity and more persistent course. Differentially expressed miRNA signatures associate with downregulation of total IgE expression and predicted target mRNA genes related molecular networks contribute to canonical pathways of nonallergic childhood asthma. We demonstrated the negative role of miRNAs involved in regulating IgE expression indicating differences between asthma phenotypes. Identification of biomarkers of miRNAs could contribute to understand the molecular mechanism of endotypes in nonallergic childhood asthma, which can potentially allow delivery of precision medicine to pediatric asthma.

Passive Attack Detection for a Class of Stealthy Intermittent Integrity Attacks

This paper proposes a passive methodology for detecting a class of stealthy intermittent integrity attacks in cyber-physical systems subject to process disturbances and measurement noise. A stealthy intermittent integrity attack strategy is first proposed by modifying a zero-dynamics attack model. The stealthiness of the generated attacks is rigorously investigated under the condition that the adversary does not know precisely the system state values. In order to help detect such attacks, a backward-in-time detection residual is proposed based on an equivalent quantity of the system state change, due to the attack, at a time prior to the attack occurrence time. A key characteristic of this residual is that its magnitude increases every time a new attack occurs. To estimate this unknown residual, an optimal fixed-point smoother is proposed by minimizing a piece-wise linear quadratic cost function with a set of specifically designed weighting matrices. The smoother design guarantees robustness with respect to process disturbances and measurement noise, and is also able to maintain sensitivity as time progresses to intermittent integrity attack by resetting the covariance matrix based on the weighting matrices. The adaptive threshold is designed based on the estimated backward-in-time residual, and the attack detectability analysis is rigorously investigated to characterize quantitatively the class of attacks that can be detected by the proposed methodology. Finally, a simulation example is used to demonstrate the effectiveness of the developed methodology.

Attack parameter dependent resilient [formula omitted] path-following control design for autonomous vehicles under cyber attacks

Autonomous vehicles typically transmit information over wireless communication network, which is vulnerable to malicious cyber attacks and poses huge security threats for autonomous vehicles. To address these challenges, this paper is concerned with resilient H∞ path-following control problem for autonomous vehicles under false data injection (FDI) attacks and denial-of-service (DoS) attacks, simultaneously. Firstly, a novel observer is constructed to estimate both sensor FDI attack signal and system state. An attack parameter dependent time-varying piecewise Lyapunov function is constructed to ensure stability of the underlying system. Then, a resilient H∞ path-following control scheme is developed to suppress the impact of FDI attacks and external interference despite the presence of intermittent DoS attacks. The design criterion of resilient controller is derived to assure the exponential stability of the closed-loop system and maintain the desired H∞ performance. Finally, simulation studies are carried out to verify the efficiency and merits of the developed results.

A machine learning-based detection framework against intermittent electricity theft attack

The widespread installation of advanced metering infrastructure (AMI) brings convenience to applications including but not limited to load management and demand response. However, AMI is also at risk of electricity theft and non-technical loss. Using the smart meter data provided by AMI to dig out user electricity consumption behavior is an effective way to construct electricity theft detectors. In this paper, a new intermittent electricity theft attack behavior is presented which switches between committing electricity theft and honestly consuming electricity alternately to skillfully evade the existing detectors. Based on the assumption that the labels of intermittent adversaries are unavailable, a new machine learning-based detection framework is proposed to detect this attack. Initially electricity features are constructed based on time intervals divided by a numerical iteration method. Then light gradient boosting method (LightGBM) is used to classify the normal users and adversaries. Further, the disperse degree of users is designed for capturing the differences between the intermittent adversaries and others. A new 2D label set is then constructed by combining the predicted labels of LightGBM and the disperse degree. Finally, a variational Bayesian Gaussian mixture model is employed based on the 2D label set to sort the users into the normal users and adversaries visually. Results of the case studies show that the presented attack can evade state-of-the-art detectors but still gain high profits. In addition, the proposed machine learning-based detector outperforms state-of-the-art detectors on both persistent attacks and intermittent attacks.