Wireless communication has become an integral part of modern vehicles. However, securing the information exchanged between interconnected terminals poses a significant challenge. Effective security ...solutions should be computationally inexpensive, ultra-reliable, and capable of operating in any wireless propagation environment. Physical layer secret key generation has emerged as a promising technique, which leverages the inherent randomness of wireless-channel responses in amplitude and phase to generate high-entropy symmetric shared keys. The sensitivity of the channel-phase responses to the distance between network terminals makes this technique a viable solution for secure vehicular communication, given the dynamic behavior of these terminals. However, the practical implementation of this technique in vehicular communication is hindered by fluctuations in the communication link between line-of-sight (LoS) and non-line-of-sight (NLoS) conditions. This study introduces a key-generation approach that uses a reconfigurable intelligent surface (RIS) to secure message exchange in vehicular communication. The RIS improves the performance of key extraction in scenarios with low signal-to-noise ratios (SNRs) and NLoS conditions. Additionally, it enhances the network's security against denial-of-service (DoS) attacks. In this context, we propose an efficient RIS configuration optimization technique that reinforces the signals received from legitimate users and weakens the signals from potential adversaries. The effectiveness of the proposed scheme is evaluated through practical implementation using a 1-bit RIS with 64×64 elements and software-defined radios operating within the 5G frequency band. The results demonstrate improved key-extraction performance and increased resistance to DoS attacks. The hardware implementation of the proposed approach further validated its effectiveness in enhancing key-extraction performance in terms of the key generation and mismatch rates, while reducing the effect of the DoS attacks on the network.
Internet-of-things has emerged out as an important invention towards employing the tremendous power of wireless media in the real world. We can control our surroundings by interacting with numerous ...smart applications running independently on different platforms, almost everywhere in the world. IoT, with such a ubiquitous popularity often serve itself as a potential platform for escalating malicious entities. These entities get an access to the legitimate devices by exploiting IoT vulnerabilities which results from several constraints like limited resources, weaker security, etc. and can further take form of various attacks. Distributed Denial-of-service (DDoS) in IoT network is an attack which targets the availability of the servers by flooding the communication channel with impersonated requests coming from distributed IoT devices. Defending DDoS in IoT has now become an exigent area of research due to the recent incidents of demolishment of some renowned servers, reported in previous few years. In this paper, we discuss the concept of malware and botnets working behind ‘Distributed’ DoS in IoT. The various DDoS defence techniques are broadly described and compared in order to identify the security gaps present in them. Moreover, we list out the open research issues and challenges that need to be addressed for a stronger as well as smarter DDoS defence.
Multiagent systems (MASs) are distributed systems with two or more intelligent agents. Formation control is a significant control technique of MASs. To date, formation control on MASs is widely used ...in various fields, such as robots, spacecrafts, satellites, and unmanned aerial/surface/underwater vehicles. However, there is a relatively small body of literature that is concerned with security problems of formation control on MASs in past years. Our research represents the first step toward developing security attacks of formation control on MASs. Our study aims to investigate potential security problems of formation control on a multirobot system for the first time. We propose two kinds of control-level attacks and each kind of attack includes several specific attack forms. Then, we discuss specific features of formation control on a classical multirobot system and utilize theoretical analyses to illustrate how cyberattacks can influence the physical movements of robots. The experimental results of the proposed attacks show that attacks can easily interrupt formation movements of a multirobot system and several carefully designed attacks even can cause irreversible loss.
A distributed denial of service (DDoS) attack on any of the major components (e.g., controller, switches, and southbound channel) of software defined networking (SDN) architecture is a critical ...security threat. For example, the breakdown of controller could disrupt the data communication in the whole SDN network. A possible way to perform DoS is to generate a large number of new, but short length traffic flows. These flows will trigger malicious flooding requests to overload the controller and causes overflow in flow tables at SDN switches. In this paper, we propose two lightweight and practically feasible countermeasures against two different types of DDoS attacks called
Route Spoofing
and
Resource Exhaustion
in SDN networks. For
Route Spoofing
attack, we introduce a technique called “selective blocking”, which stops an adversary node from maliciously using other users active communication routes. To countermeasure
Resource Exhaustion
attack, we propose a solution called “periodic monitoring”, which detects adversary nodes based on the traffic analysis statistics that are gathered within a time window. We implement and perform result analysis of the attacks and their proposed countermeasures. When using our proposed countermeasures in the target SDN scenarios, the simulation results indicate an adequate reduction in bandwidth consumption and processing delay of new request, and it also depicts substantial gain in packet delivery rate. Additionally, we present the receiver operating characteristic curve, which shows the sensitivity and specificity of our countermeasures along with their detection accuracy.
Software-Defined Networking (SDN), which is used in Industrial Internet of Things, uses a controller as its “network brain” located at the control plane. This uniquely distinguishes it from the ...traditional networking paradigms because it provides a global view of the entire network. In SDN, the controller can become a single point of failure, which may cause the whole network service to be compromised. Also, data packet transmission between controllers and switches could be impaired by natural disasters, causing hardware malfunctioning or Distributed Denial of Service (DDoS) attacks. Thus, SDN controllers are vulnerable to both hardware and software failures. To overcome this single point of failure in SDN, this paper proposes an attack-aware logical link assignment (AALLA) mathematical model with the ultimate aim of restoring the SDN network by using logical link assignment from switches to the cluster (backup) controllers. We formulate the AALLA model in integer linear programming (ILP), which restores the disrupted SDN network availability by assigning the logical links to the cluster (backup) controllers. More precisely, given a set of switches that are managed by the controller(s), this model simultaneously determines the optimal cost for controllers, links, and switches.
In this article, we study the distributed resilient cooperative control problem for directed networked Lagrangian systems under denial-of-service (DoS) attacks. The DoS attacks will block the ...communication channels between the agents. Compared with the existing methods for the linear networked systems, the considered nonlinear networked Lagrangian systems with asymmetric channels under DoS attacks are more challenging and still not well explored. In order to solve this problem, a novel resilient cooperative control scheme is proposed by using the sampling control approach. Sufficient conditions are first derived in the absence of DoS attacks according to a multidimensional small-gain scheme. Then, in the presence of DoS attacks, the proposed resilient scheme works in a switching manner. Inspired by multidimensional small-gain techniques, the Lyapunov approach is used to analyze the closed-loop system, which enables us to establish sufficient stability conditions for the control gains in terms of the duration and frequency of the DoS attacks.
Summary
This study investigates the ℋ∞$$ {\mathscr{H}}_{\infty } $$ secure consensus issue for Markov jump multi‐agent systems with denial‐of‐service attacks and disturbance. Considering that the ...mode of the system cannot be directly obtained in the actual situation, a detector is constructed to obtain the mode of the system indirectly with the help of the hidden Markov model. The network communications between agents are undirected, and denial‐of‐service attacks are encountered randomly and represented by a random variate obeying Bernoulli distribution. The reduced‐order decomposed system is obtained by the method of model reduction. On this basis, the Lyapunov stability theory is applied to derive some sufficient conditions to guarantee that the system achieves consensus with a stipulated ℋ∞$$ {\mathscr{H}}_{\infty } $$ performance index. Finally, a numerical example is employed to verify the validity of the proposed protocol.
IoT devices provide a significant medium for distributed denial-of-service (DDoS) attacks. In 2016, a large-scale DDoS attack, named Dyn, caused massive damage to several well-known companies. One ...effective countermeasure is observing previous network traffic information or abnormal behavior determined by the host machines and determining the latest DDoS-attack IP addresses. Because of the lack of a fair exchange mechanism, most security operation centers (SOCs) are unwilling to share their real-time DDoS data. In this article, we propose a decentralized DDoS data exchange platform, namely SOChain, using blockchain technology to overcome the trust and fairness issues. The platform incentivizes SOCs through the DDoS_coin token. The more DDoS information an SOC contributes, the more coins it earns. To confirm the validity of uploaded information, we enlist a content verifier to examine uploaded abnormal IP addresses. Moreover, the verifier is incentivized by the DDoS_coin . To decrease the management effort, the entire flow is automatically executed in smart contract deployed onto the blockchain system. To address the issue of privacy in smart contracts, we devise a novel dual-level Bloom filter to enable efficient searches with privacy protection. Herein, a verifiable method is designed without revealing the information to public.
Anomaly detection is playing an increasingly important role in hyperspectral image (HSI) processing. The traditional anomaly detection methods mainly extract knowledge from the background and use the ...difference between the anomalies and the background to distinguish them. Anomaly contamination and the inverse covariance matrix problem are the main difficulties with these methods. The low-rank and sparse matrix decomposition (LRaSMD) technique may have the potential to solve the aforementioned hyperspectral anomaly detection problem since it can extract knowledge from both the background and the anomalies. This paper proposes an LRaSMD-based Mahalanobis distance method for hyperspectral anomaly detection (LSMAD). This approach has the following capabilities: 1) takes full advantage of the LRaSMD technique to set the background apart from the anomalies; 2) explores the low-rank prior knowledge of the background to compute the background statistics; and 3) applies the Mahalanobis distance differences to detect the probable anomalies. Extensive experiments were carried out on four HSIs, and it was found that LSMAD shows a better detection performance than the current state-of-the-art hyperspectral anomaly detection methods.
Distributed denial-of-service (DDoS) defense is still a difficult problem though it has been extensively studied. The existing approaches are not capable of detecting various types of DDoS attacks. ...In particular, new emerging sophisticated DDoS attacks (e.g., Crossfire) constructed by low-rate and short-lived benign traffic are even more challenging to capture. Moreover, it is difficult to enforce realtime defense to throttle these detected attacks since the attack traffic can be concealed in benign traffic. Software defined networking (SDN) opens a new door to address these issues. In this paper, we propose Reinforcing Anti-DDoS Actions in Realtime (RADAR) to detect and throttle DDoS attacks via adaptive correlation analysis built upon unmodified commercial off-the-shelf SDN switches. It is a practical system to defend against a wide range of flooding-based DDoS attacks, e.g., link flooding (including Crossfire), SYN flooding, and UDP-based amplification attacks, while requiring neither modifications in SDN switches/protocols nor extra appliances. It accurately detects attacks by identifying attack features in suspicious flows, and locates attackers (or victims) to throttle the attack traffic by adaptive correlation analysis. We implement RADAR prototype using open source Floodlight controller, and evaluate its performance under various DDoS attacks by real hardware testbed based experiments. We observe that our scheme can successfully detect and effectively defend against various DDoS attacks with acceptable overhead.
