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The popularity of Internet of Things (IoT) devices in smart homes has raised significant concerns regarding data security and privacy. Traditional machine learning (ML) methods for anomaly detection often require sharing sensitive IoT data with a central server, posing security and efficiency challenges. In response, this paper introduces FedGroup, a novel Federated Learning (FL) method inspired by FedAvg. FedGroup revolutionizes the central model’s learning process by updating it based on the learning patterns of distinct groups of IoT devices. Our experimental results demonstrate that FedGroup consistently achieves comparable or superior accuracy in anomaly detection when compared to both federated and non-federated learning methods. Additionally, Ensemble Learning (EL) collects intelligence from numerous contributing models, leading to enhanced prediction performance. Furthermore, FedGroup significantly improves the detection of attack types and their details, contributing to a more robust security framework for smart homes. Our approach demonstrates exceptional performance, achieving an accuracy rate of 99.64% with a minimal false positive rate (FPR) of 0.02% in attack type detection, and an impressive 99.89% accuracy in attack type detail detection. [ABSTRACT FROM AUTHOR]

Owing to their flexibility and rapid response, grid-connected distributed energy resources (DERs) are wielding growing influence in frequency regulation markets (FRMs). Nevertheless, compared with conventional large-scale generators, small-scale DERs are usually weakly shielded by cyber security measures. This offers attackers the opportunity of disrupting the clearing and settlement of FRMs by manipulating the bid information of DERs. In this paper, the frequency regulation market equilibrium is studied considering the dynamic gaming between attackers and defenders, both of which need the knowledge of FRMs for their interventions. Specifically, a tri-level programming model characterizing the attacker–defender–operator (ADO) interdiction problem in FRMs is developed and then analyzed using a column and constraint generation algorithm, thereby achieving market equilibrium representing the defender's best response to the attacker. The defense strategy in the market equilibrium can attenuate the negative influence of cyber attacks upon the FRMs to the maximum extent. Finally, based on the operating rules of the California Independent System Operator, the FRM process considering the ADO interdiction is simulated and the numerical equilibrium results are presented. [ABSTRACT FROM AUTHOR]

This work studies the H ∞ performance of T-S fuzzy networked control systems under denial-of-service (DoS) attacks. First, the weight coefficient is introduced to measure the damage to the control signal caused by DoS attacks. Then, novel looped Lyapunov-Krasovskii functions are constructed based on the fuzzy membership function, and the nonlinear problem of the system is considered under the premise of reducing the initial condition constraints. Next, the issue of finding the suitable sampling period is transformed into an optimization problem of finding the optimal sampling period to reduce sampling times. An intelligent sampling controller is designed to ensure the asymptotic stability of the system. Finally, the effectiveness of the proposed method is verified with a truck trailer model. [ABSTRACT FROM AUTHOR]

Medical images are treated as sensitive as it carries patients' confidential information and hence must be protected from unauthorized access. So, a strong encryption mechanism is a primary criterion to transmit these images over the internet to protect them from intruders. In many existing algorithms, noise affection in the extracted images is high, hence not suitable for medical data encryption. Here, we present a new method using phase grating to multiplex as well as encrypting 32 cross-sectional CT scan images (slices) in a single canvas for optimization of storage space and improvement of security. The entire process is divided into a few steps. Before transmission, the main canvas is encrypted with the help of a random phase matrix. The main canvas is further encrypted by the transposition method to enhance security. After decryption, inverse Fourier transform is applied at the proper location of the decrypted canvas to extract the images from the spectra. Quality is measured with peak-signal-to-noise ratio and correlation coefficient methods. Here, it is greater than 38 and the correlation coefficient is close to 1 for all images, thereby indicating of good quality of extracted images. The effect of three common cyber-attacks (viz. known-plaintext attack, chosen-plaintext attack, and chosen-ciphertext attack) is also presented here. The correlation coefficient during cyber-attacks is found to be close to zero, which implies the robustness of the algorithm against cyber-attacks. Finally, a comparison with existing techniques shows the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Wide area monitoring and control of modern power network demand real-time estimation of state variables from sensor measurements. Maintaining a high degree of reliability and accuracy in the state estimation process is important in avoiding any disruption in the electricity market operation. The market operation in power networks aims at providing a win-win situation for both the utility and consumer. The exposure and vulnerability of cyber components in smart grids allow for manipulating the electricity market by falsifying the state variables. The attacker can cause intentional profit/loss to the utility/consumer by misdirecting the estimated states through the injection of false data into the sensor information. Hence, maintaining integrity in the market operation demands a mechanism for detecting false data injection attack (FDIA). This paper proposes a classification-based approach for detecting FDIAs aiming at electricity market disruption. For any variation in the predicted and real-time nodal electricity price, the proposed decision tree (DT) based ensemble classifier is executed using state information to identify the prevailing scenario as a contingency or FDIA. The effectiveness of the proposed scheme has been extensively validated for various contingency and FDIA scenarios in IEEE 14 bus, 39 bus, and 57 bus test power systems. [ABSTRACT FROM AUTHOR]

In this study, a hybrid deep belief network (DBN) cyber intrusion detection system was proposed to provide a secure network by controlling network traffic in Industrial control systems (ICS). The disadvantages of DBN have been analyzed and improved to create attack detectors in network traffic. The output is combined with Softmax Regression for effective intrusion detection and classification detection. Training and testing of the hybrid DBN model were carried out with the actual and original data set generated by ICS. DBNs are a much-preferred approach for detecting malicious attacks in network traffic. In instances where there is a lot of data, it is important to select the most appropriate structure for the DBN model. Therefore, in the model the hidden layers are updated by contrastive divergence (CD), and the output layer is combined with the Softmax classifier. The proposed model architecture has proved successful in many limitations, such as the complexity and size of training data. The proposed hybrid DBN model provided 99.72% accuracy in intrusion detection and classification. These results showed that the model achieved better performance than the existing intrusion detection system (IDS). It also provided approximately 5% more accuracy improvements with the hybrid model than with older DBN-based systems. [ABSTRACT FROM AUTHOR]

This paper is concerned with the H∞ controller design problem for a class of network-based nonlinear systems (NCSs) represented by the Takagi-Sugeno (T-S) fuzzy model. A multiple packets compensation scheme is developed which uses all the data stored in a finite memory buffer to compensate the negative effects of packet dropouts. This model contains the medium access constraint problem as a special case. The time-multiplexing mechanism may be used for such a case so that there are multiple packets arrive at the receiver side. By taking the stochastic cyber attacks into account, the desired controller in terms of linear matrix inequalities (LMIs) is designed by using fuzzy-rule-dependent Lyapunov method. The sufficient condition is obtained which makes the closed-loop system be asymptotically mean-square stable and achieve the prescribed H∞ disturbance-rejection-attenuation level. Finally, a mass-spring-damping system is given to show the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

Application of the ant algorithm for ensuring the cyber resilience of a distributed system in conditions of various types of cyber attacks is considered. The principle of operation of the ant algorithm is described, a mathematical model of the network infrastructure is developed, and possible types of cyberattacks are determined within the framework of the model. The results of the experimental studies demonstrated the applicability of the ant algorithm for ensuring the cyber resilience of large-scale networks. [ABSTRACT FROM AUTHOR]

This paper presents an approach for tolerant control and compensation of cyber attacks on the inputs and outputs of a cyber-physical system of rotary gantry type. The proposed control schemes are designed based on classic–intelligent control strategies for trajectory tracking and vibration control of a networked control system, which are developed for tip angular position control, while the system is prone to cyber attacks. The malicious attacks are assumed to be of denial of service (DoS) kind and cause packet loss with high probability in the two signals; control input and sensor output. In this paper, several classic and intelligent control strategies are studied in terms of robustness and effectiveness to attacks. Based on the results, a new hybrid control scheme is designed using linear quadratic regulation, sliding mode control, and artificial radial basis function neural network to alleviate the effect of DoS attacks and maintain the performance of the cyber-rotary gantry system in tracking applications. The neural network controller is trained during the control process. Its learning algorithm is based on the minimization of a cost function which contains the sliding surface. The hybrid control system is analyzed from the stability perspective. Moreover, the efficiency of the proposed scheme is validated by simulation on MATLAB Simulink platform. [ABSTRACT FROM AUTHOR]

Cyberspace is an integration of cyber physical system components that integrates computation, networking, physical processes, embedded computers and network monitors which uses feedback loops for controlling the processes where the computations are affected by processes and vice versa. More general, cyber physical systems include all equipments operated on preprogrammed instructions ranging from simple electronic devices to the ultra-modern warfare equipments along with life saving devices. Active cyber-attacks can cause cyber warfare situations by disrupting an entire community of people, which in turn raises an emergency situation to the nation. Thus, cyber warfare is a major threat to the nation at large. In this paper, we analyze the various aspects of cyber warfare situations and a survey on ongoing attacks, defense and cyber forensics strategies in that field. Internet of Things (IoT) is an emerging computing area which enables Machine to Machine communication in cyber physical systems. An attack on IoT causes major issues to the security on the devices and thus, the various threats and attacks on IoT are analyzed here. Overall monitoring and data acquisition in cyber physical systems is done by Supervisory Control and Data Acquisition systems and are mainly targeted by the attackers in order to leave the cyberspace applications not functioning. Therefore, the various threats, attacks and research issues pertaining to the cyberspace are surveyed in this paper along with a few research issues and challenges that are to be solved in the area of cyber warfare. [ABSTRACT FROM AUTHOR]

In the recent years, an alarming rise in the incidence of cyber attacks has made cyber security a major concern for nations across the globe. Given the current volatile socio-political environment and the massive increase in the incidence of terrorism, it is imperative that government agencies rapidly realize the possibility of cyber space exploitation by terrorist organizations and state players to disrupt the normal way of life. The threat level of cyber terrorism has never been as high as it is today, and this has created a lot of insecurity and fear. This study has focused on different aspects of cyber attacks and explored the reasons behind their increasing popularity among the terrorist organizations and state players. This study proposes an empirical model that can be used to estimate the risk levels associated with different types of cyber attacks and thereby provide a road map to conceptualize and formulate highly effective counter measures and cyber security policies. [ABSTRACT FROM AUTHOR]

Many government branches report that internal networks are managed safely by separating them from the outside, but there is often a vulnerability that allows malicious codes to attack an internal network. Recently, the Ministry of National Defense of Korea announced that the internal network operated by the Korean military was attacked though hacking. It is difficult to detect cyber-attacks in real time within an internal network, which can be connected to an Internet of Everything (IoE). In this paper, we propose a fast attack detection system for the internal network that can be used by the government or public organizations. This system generates a tree to which the attack level is applied, notifies the user when the level is reached, and can block the system before an attack. Using this system, it is possible to protect the data and physical aspects by preventing the destruction of a system with large amounts of data, including important confidential or intellectual property. The proposed method offers a proper methodology for designing a malware protection system by categorizing the problem into a tree structure. [ABSTRACT FROM AUTHOR]

In the envisioned smart grid, high penetration of uncertain renewables, unpredictable participation of (industrial) customers, and purposeful manipulation of smart meter readings, all highlight the need for accurate, fast, and robust power system state estimation (PSSE). Nonetheless, most real-time data available in the current and upcoming transmission/distribution systems are nonlinear in power system states (i.e., nodal voltage phasors). Scalable approaches to dealing with PSSE tasks undergo a paradigm shift toward addressing the unique modeling and computational challenges associated with those nonlinear measurements. In this study, we provide a contemporary overview of PSSE and describe the current state of the art in the nonlinear weighted least-squares and least-absolutevalue PSSE. To benchmark the performance of unbiased estimators, the Cramér-Rao lower bound is developed. Accounting for cyber attacks, new corruption models are introduced, and robust PSSE approaches are outlined as well. Finally, distribution system state estimation is discussed along with its current challenges. Simulation tests corroborate the effectiveness of the developed algorithms as well as the practical merits of the theory. [ABSTRACT FROM AUTHOR]

This paper proposes a novel framework for an artificial immune server with both innate and adaptive immune functions. The innate immune function detects cyber attacks on a known or unknown vulnerability. Upon detecting a cyber attack, the innate immune function creates a new process of the server application and terminates the compromised process. The adaptive immune function learns the requests with exploit code detected by the innate immune function. The adaptive immune function enables the server application to maintain its own service without terminating the server application after the innate immune function recognizes the attack. Performance tests of a prototype system implemented on a vulnerable web server showed that this prototype system was able to maintain the web service during all attacks except the first. [ABSTRACT FROM AUTHOR]

This paper describes a novel cyber attack-resilient server inspired by the concept of biological diversity. The server consists of several virtual machines running different operating systems and different implementations of the same server protocol specification. This approach is based on the observation that not all implementations are affected by the same vulnerability, except for vulnerabilities in specifications and on shared libraries. A prototype system was built and tested to evaluate the continuity of the service. The results showed that, by exploiting a vulnerability, the prototype system could suppress downtime of the DNS service to less than 4 s without false positives. [ABSTRACT FROM AUTHOR]

A description has been provided for a formal model of cyber attack on virtualization tools that allow one to formulate condition for the security of virtualization tools. The concept of measuring the vulnerability of virtualization tools has been introduced that characterizes the predisposition of a system to vulnerabilities that contribute to the implementation of cyber attacks in the proposed formal model. These characteristics of virtualization tools allow one to compare different hypervisors and estimate the presence of vulnerabilities in them. [ABSTRACT FROM AUTHOR]

The use of cyber force can be as severe and disruptive as traditional armed attacks are. Cyber attacks may neither provoke physical injuries nor cause property damages and still, they can affect essential functions of today's societies, such as governmental services, business processes or communication systems that progressively depend on information as a vital resource. Whereas several scholars claim that an international treaty, much as new forms of international cooperation, are necessary, a further challenge should be stressed: authors of cyber attacks can be non-state actors, and identifying the party responsible for such a use of force, whether non-state actors or national sovereign states, is often impossible. Accordingly, several programmes on online security and national defence have been developed by sovereign states to tackle this menace and yet, the endurance of Western democracies and their aim to protect basic rights have already been tested by such programmes over the past years. The new scenarios of cyber force do not only concern the field of international law, since they may represent the main threat in the fields of national and constitutional law as well. [ABSTRACT FROM AUTHOR]

Recently, studies on the Mixed Networking which guarantees the anonymity in Internet environment are actively carried. Since this technology uses the coded communication and its communication paths are changed frequently, it is difficult to detect attacks of the hackers. In this situation, if the cyber-attack occurs between countries, there shall be a high potential for the hackers to use the anonymous network technology in order to hide themselves. Anyway, the anonymous network technology is continuously being updated by the hackers and a new technology is under development. Thus, this paper verified statistically the attacking methods which the hackers shall create by increasing the data transmission rate of TOR through manipulating the speed of the anonymous network, and proposed political countermeasures to detect hacker's attacks effectively which use this technology. [ABSTRACT FROM AUTHOR]

This paper focuses on Information Warfare-the warfare characterised by the use of information and communication technologies. This is a fast growing phenomenon, which poses a number of issues ranging from the military use of such technologies to its political and ethical implications. The paper presents a conceptual analysis of this phenomenon with the goal of investigating its nature. Such an analysis is deemed to be necessary in order to lay the groundwork for future investigations into this topic, addressing the ethical problems engendered by this kind of warfare. The conceptual analysis is developed in three parts. First, it delineates the relation between Information Warfare and the Information revolution. It then focuses attention on the effects that the diffusion of this phenomenon has on the concepts of war. On the basis of this analysis, a definition of Information Warfare is provided as a phenomenon not necessarily sanguinary and violent, and rather transversal concerning the environment in which it is waged, the way it is waged and the ontological and social status of its agents. The paper concludes by taking into consideration the Just War Theory and the problems arising from its application to the case of Information Warfare. [ABSTRACT FROM AUTHOR]