Denial Of Service Attacks Research Articles

Resilient Sampled-Data Event-Triggered Control for Switched Systems Under Denial of Service Attacks

Resilient Sampled-Data Event-Triggered Control for Switched Systems Under Denial of Service Attacks

Data-Driven-Based Event-Triggered Resilient Control for Cigarette Weight Control System Under Denial of Service Attacks and False Data Injection Attacks

Data-Driven-Based Event-Triggered Resilient Control for Cigarette Weight Control System Under Denial of Service Attacks and False Data Injection Attacks

Resilient Multi-Agent Systems Against Denial of Service Attacks via Adaptive and Activatable Network Layers

Resilient Multi-Agent Systems Against Denial of Service Attacks via Adaptive and Activatable Network Layers

PREVIR: Fortifying Vehicular Networks Against Denial of Service Attacks

PREVIR: Fortifying Vehicular Networks Against Denial of Service Attacks

Cooperative Fault-Tolerant Control for a Class of Nonlinear MASs by Resilient Learning Approach.

In this article, a learning-based resilient fault-tolerant control method is proposed for a class of uncertain nonlinear multiagent systems (MASs) to enhance the security and reliability against denial-of-service (DoS) attacks and actuator faults. With the framework of cooperative output regulation, the developed algorithm consists of designing a distributed resilient observer and a decentralized fault-tolerant controller. Specifically, by using the data-driven method, an online resilient learning algorithm is first presented to learn the unknown exosystem matrix in the presence of DoS attacks. Then, a distributed resilient observer is proposed working against DoS attacks. In addition, based on the developed observer, a decentralized adaptive fault-tolerant controller is designed to compensate for actuator faults. Moreover, the convergence of error systems is shown by using the Lyapunov stability theory. The effectiveness of our result is examined by a simulation example.

Security and Safety-Critical Learning-Based Collaborative Control for Multiagent Systems.

This article presents a novel learning-based collaborative control framework to ensure communication security and formation safety of nonlinear multiagent systems (MASs) subject to denial-of-service (DoS) attacks, model uncertainties, and barriers in environments. The framework has a distributed and decoupled design at the cyber-layer and the physical layer. A resilient control Lyapunov function-quadratic programming (RCLF-QP)-based observer is first proposed to achieve secure reference state estimation under DoS attacks at the cyber-layer. Based on deep reinforcement learning (RL) and control barrier function (CBF), a safety-critical formation controller is designed at the physical layer to ensure safe collaborations between uncertain agents in dynamic environments. The framework is applied to autonomous vehicles for area scanning formations with barriers in environments. The comparative experimental results demonstrate that the proposed framework can effectively improve the resilience and robustness of the system.

Dynamic event-triggered consensus control for nonlinear multi-agent systems under DoS attacks.

In this paper, we investigated leader-following consensus control for nonlinear multi-agent systems (MASs) experiencing denial-of-service (DoS) attacks. We proposed a distributed control strategy incorporating an adaptive scheme and a state feedback control gain to eliminate the effects of system nonlinear dynamics and uncertainties. In addition, we introduced a dynamic event-triggered control (DETC) to minimize the utilization of communication resources. Finally, we provided simulation results to show the validity of the proposed approach.

Exploring a novel framework for DoS/DDoS attack detection and simulation in contemporary networks

Currently, the internet serves as the predominant means of communication and is utilized by a vast number of individuals worldwide. Simultaneously, the commercial aspect of the internet is contributing to a rise in susceptibility to cybercrimes, leading to a significant surge in the occurrence of distributed Denial of Service (DDoS) assaults over the last decade. DoS/DDoS assaults primarily target network resources such as network bandwidth, CPU time, memory consumption, web servers, and network switches. Network security is an essential and crucial problem in the modern interconnected society. Numerous studies have been undertaken by multiple researchers thus far in order to identify this attack. However, there is still room for improvement in past investigations. This paper presents a novel approach for detecting and simulating DoS/DDoS attacks in modern networking environments, introducing a new paradigm. It is done in a controlled environment. The primary focus of this work is to simulate an attacker's perspective of a DoS/DDoS attack by repeatedly sending huge SYN flood packets to a specific target or network server using the hping3 tool. On the server side, the proposed attacker detector script continuously monitors incoming network connections on the network server using the netstat command. It identifies potential DoS/DDoS attacks by analyzing the connection count and comparing connections count with an assumed threshold. This experiment results in 61% CPU usage and 7.1% memory consumption while a DDoS attack triggers on the target server. Additionally, the proposed script performs statistical analysis and displays warning messages on the console when suspicious activity is detected on the network server. Wireshark is also utilized in this work to detect anomalous network traffic patterns in order to identify distributed denial-ofservice (DDoS) attacks that are targeting a network server. Additionally, it offers the capability to block the IP address of the attacker if the configuration allows for it. This proposed approach efficiently identifies DDoS activity in real-time network traffic, further helping to improve network security.

Optimal DoS attack on multi-channel cyber-physical systems: A Stackelberg game analysis

In this commentary, optimal denial-of-service (DoS) attack strategies on multi-channel cyber-physical systems (CPSs) are considered, which focus on energy allocation on communication channels. For simplicity, a Stackelberg game between one defender and one attacker is constructed. Compared with the existing literature, which mainly pay attention to static equilibrium, the dynamic process of the game is also exhibited in this paper, which fills the gap in the demonstration of dynamic decision-making between both players of the game. In the solution of Stackelberg equilibrium, a self-adaptive particle swarm optimization (PSO) algorithm with Sigmoid-like update function is applied to cope with the nonlinearity of the reward function with faster convergence and wider adaptability. Besides, to acquire better performance of both sides to allocate energy, an online computation algorithm is proposed for dynamic Stackelberg game. Finally, numerical examples are provided to illustrate similarities between theoretic static equilibrium and optimal strategies obtained by Monte Carlo simulations.

Secured Service Oriented Communication in V2X Technology

From the day communication started and messages being transmitted and received from one endpoint to another, security was always a concern. And nowadays this is not different from the old ages. In the era of IOT and V2X technology, communication protocols must be safe and secured and the traditional communication approaches like using CAN, LIN and Flexray will be hard to be integrated with IOT systems. Modern approaches are introduced for IOT integration through Ethernet, one of the most used approaches nowadays for vehicle communication is Service Oriented Communication which is represented by several protocols. One of protocols designed by AUTOSAR community is Service Oriented Middleware over Internet Protocol known as SOME/IP. After Surveying Service Oriented Communication, we propose a solution that adds security features to vanilla SOME/IP that prevents possible Denial of Service attacks. In this paper, we will survey the current solution used and tested and compare it with our proposal.

Unlocking Security : The World of Ethical Hacking

As nowadays all the information is available online, a large number of users are accessing it, some of them use this information for gaining knowledge and some use it to know how to use this information to destroy or steal the data of websites or databases without the knowledge of the owner. The purpose of this paper is to tell what is hacking, who is hackers, what is ethical hacking, what is the code of conduct of ethical hackers and the need of them. A small introduction of Linux Operating System is given in this paper. All the techniques are performed on the Linux operating system named Kali Linux. After this some basic hacking attacks covered in the paper are MiTM Attack (Man in The Middle Attack), Phishing Attack, DoS Attack (Denial of Services Attack). Further what is Wi-Fi, what are the techniques used in the Wi-Fi protection and the methods used by the hackers to hacks Wi-Fi passwords is covered in the paper.

Artificial Intelligence the Strategic Key of Cybersecurity

Despite the fact that digital transformation introduces multiple advantages, it also introduces crucial security challenges, since it combines heterogeneous communications, the integration of digital devices, legacy technologies. In the case of power grid, in addition to damage to the availability, integrity and confidentiality of information; there may be manipulation and take control of assets through the infection of operational systems. In this context, powerful cybersecurity schemes and mechanisms that guarantee the safe transmission of information and the safe operation of assets are required. The goal is develop cyber security schemes and mechanisms based on intelligent cyber defense mechanisms that provide flexibility and self-learning capacity to support humans in the analysis and generation of containment measures against cyber-attacks. This paper presents the developed and validation of an Intrusion Detection and Prediction System (IDPS) based on individual classifiers and ensemble algorithms. The IDPS has demonstrated be an efficient countermeasure against several cyberattacks. The proposed IDPS uses J48 (decision tree), CLONAL-G (artificial immune system), bayesian classifier and ensemble algorithm and was validated with the KDDCup databases. The attacks in the data set are categorized into four attack types: DoS (denial-of-service attacks), R2L (root-to-local attacks), U2R (user-to-root attack), and Probe (probing attacks). The results show that the individual classifiers perform well for particular attack, so it was necessary to build an ensemble algorithm that combine the information from each classifier for better performance. The idea is not to rely on a single classifier for the decision, but rather individual information from different classifiers is combined to make the final decision.

Resilient distributed control of islanded microgrids under hybrid attacks

In this paper, a resilient control strategy is proposed to improve the stability of frequency and voltage recovery for the islanded microgrid (MG) under hybrid cyber attacks. To deal with the common false data injection attacks (FDI) and denial of service attacks (DoS) in MGs, the proposed resilient control strategy utilizes the observers to accurately estimate the potential FDI signals on both the sensors and actuators of each distributed generation unit (DG) and reconstruct the unavailable states in the system to enhance the system’s ability actively. The ultimate uniform boundedness (UUB) of the system under hybrid cyber attacks is proved by the Lyapunov stability theory. Finally, an islanded MG system is established in MATLAB/SIMULINK, and multiple scenarios are simulated to verify the effectiveness of the method.

Event-triggered prescribed performance adaptive secure control for nonlinear cyber physical systems under denial-of-service attacks

For a class of nonlinear cyber physical systems (CPSs) under intermittent denial-of-service attacks (DoS), this paper investigates a novel adaptive security control scheme. A switched fuzzy observer is designed to estimate unmeasurable states. In addition, the relative threshold-based event-triggered approach is introduced to reduce the released data, and the dynamic surface control technique is used to remove the ‘explosion of terms’ problem. Meanwhile, an observer-based adaptive event-triggered prescribed performance controller is constructed, which ensures that all closed-loop signals remain bounded and system output approaches a designed performance bound within a predefined finite time. Simultaneously, the Zeno behavior can be thoroughly eliminated. Finally, a numerical simulation is used to demonstrate the validity of the results.

TANTANGAN TERKINI DALAM KEAMANAN INFORMASI ANALISIS RESIKO DAN UPAYA PERLINDUNGAN

Threats and attacks that can result in leaks of personal or sensitive data or reduced business performance have a significant impact on the security of networks and information systems. Insider attacks, eavesdropping, misconfiguration, missing functionality, confusion, man-in- attacks, virus attacks, denial of service attacks are some of the dangers that threaten your network security or threaten the security of your network. Attacks are possible. Influencing information systems. Companies risk losing information appropriate security measures, such as network and information system security. You can implement the right security solutions to predict and prevent various security risks and attacks. Confidentiality, integrity, and availability are three characteristics of security, and to determine which security technology best suits your organization's needs, you must first compare the various threats and attacks with the security technologies in use. Recommended security technologies intrusion detection systems (IDS), antivirus programs, and encryption systems. This is because this technology relies on predicting and protecting networks and information systems in many security elements.

Switching-like dynamic event-triggered load frequency control for multi-area power systems with electric vehicles under DoS attacks

The load frequency control (LFC) for multi-area power systems with electric vehicles (EVs) is investigated under Denial of Service (DoS) attacks. First, a new dynamic event-triggered mechanism is proposed, where the event parameters can be switched according to whether DoS attacks occur or not. Then, a time-delay model with parameter uncertainty is developed by considering the state of charge (SOC) of EVs batteries and DoS attacks. Particularly, asymptotic stability criterion with prescribed H∞ performance is derived, and the relationship between the packet losses induced by DoS attacks and the event parameters is revealed. Further, a co-design scheme of the controller gain and the event-triggered weighting matrix is provided. Finally, simulation results show that the proposed method is advantageous to resist DoS attacks and save communication resources.

Observer-based impulsive consensus control of nonlinear multi-agent systems under denial-of-service attacks

This paper is concerned with the distributed impulsive consensus problem for nonlinear multi-agent systems (MASs) subject to denial-of-service (DoS) attacks, where the information of agent states is not fully available in the impulsive control design. To reconstruct the states of MASs and guarantee secure average consensus, a novel observer-based impulsive secure control protocol is put forward, and some sufficient conditions are derived by means of linear matrix inequality (LMI) technique and Lyapunov method. It should be pointed out that both the proposed state observer and control protocol adjust the state value abruptly at some discrete instants in an impulsive manner. Moreover, the considered asynchronous DoS attack model can allow jam each channel independently, under which the decay rates of different attack modes are estimated. Finally, two simulation examples, including a practical control system, verify the effectiveness of the proposed consensus algorithm.

Prescribed performance‐based resilient model‐free adaptive control for CPSs against aperiodic DoS attacks

AbstractThis paper presents a prescribed performance‐based model‐free adaptive resilient control (MFARC) algorithm to address the realization of trajectory tracking for nonlinear cyber‐physical systems (CPSs) under aperiodic denial‐of‐service (DoS) attacks. Firstly, an equivalent linear model is constructed by utilizing the dynamic linearization technique, and a novel output transformation approach is applied to convert the constrained system to an unconstrained one for the MFARC framework. Then, an attack compensation mechanism is presented to estimate the unavailable output signal when attacks are active, such that the negative impact of aperiodic DoS attacks can be compensated. Based on the unconstrained model and the compensation mechanism, a prescribed performance‐based MFARC strategy is constructed to steer the tracking error to the predetermined neighborhood around the origin in the presence of DoS attacks. A major improvement of our result over previous studies is the introduction of prescribed performance control (PPC) into MFARC while reasonably restricting the transient and steady‐state performance of the tracking error even when DoS attacks occur. Additionally, we utilize the linear matrix inequality (LMI) toolbox to obtain better tracking performance by suitably adjusting the time‐varying parameters, which is superior in practical applications. Ultimately, our results indicate that the tracking error consistently remains within a predefined bound.

Covariance intersection based event-triggered distributed state estimation under channel independent DoS attacks

This paper investigates the event-triggered distributed state estimation problem for a class of discrete time-varying systems in the presence of denial-of-service (DoS) attacks, where each sensor node selectively shares its local information with neighbors. In contrast to the previous studies where the DoS attacks are considered on sensor-to-filter channels, we deal with the situation that DoS attacks jam each filter-to-filter communication channel independently. To reduce the communication rate and save network resources, a novel event-triggered communication strategy is presented that takes into account the impact of DoS attacks and is specialized for each communication channel. Based on the covariance intersection fusion rule and weight rearrangement method, a distributed state estimation algorithm is proposed. Further, the consistency of estimates and mean-square boundedness of estimation errors are proved under system collective observability and some other mild assumptions. Lastly, a numerical simulation is conducted to demonstrate the developed results and the effectiveness of the proposed algorithm.

An efficient lightweight authentication scheme for dew‐assisted IoT networks

SummaryThe dew computing is currently considered as one of the promising technology, due to its ability to give data access in the absence of internet. However, dew computing also brings new challenges, particularly security and privacy issues. In dew computing paradigm, authentication and key agreement pose substantial challenges that must be taken into account. In this context, the present work is to provide a secure authentication scheme for Internet of Things and dew server based on elliptic curve cryptography. Moreover, the performance evaluation of proposed scheme has been assessed in terms of communication and computation cost, which shows the proposed scheme outperforms than existing related schemes. The proposed scheme has also been compared with the related schemes in terms of various security features such as location privacy, anonymity, forward secrecy, mutual authentication, key agreement, forgery attack, replay attack, denial of service attack and replay attack. Furthermore, the formal security evaluation has been verified by automated validation internet security protocols and applications (AVISPA) under on‐the‐fly model‐checker (OFMC) and constraint logic based attack searcher (CL‐AtSE) backends. The OFMC backend analyzed 228 visited nodes with four plies using search time of 0.24 s. The CL‐AtSE analyzed three states with translation time of 0.12 s. The OFMC and CL‐AtSE backends have not identified any attack trace. Therefore, the simulation results demonstrate that the proposed scheme is safe against the security threats.