Biblio

The paper presents the design of fuzzy logic controller based unified power flow controller (UPFC) to improve power system security performance during steady state as well as fault conditions. Fuzzy interference has been design with two inputs Vref and Vm for the shunt voltage source Converter and two inputs for Series Id, Idref, Iq, Iqref at the series voltage source converter location. The coordination of shunt and series VSC has been achieved by using fuzzy logic controller (FLC). The comparative performance of PI based UPFC and fuzzy based UPFC under abnormal condition has been validated in MATLB domain. The combination of fuzzy with a UPFC is tested on multi machine system in MATLAB domain. The results shows that the power system security enhancement as well as oscillations damping.

Mortality from lung cancer has ranked high among cancers for many years. Early detection of lung cancer is critical for disease prevention, cure, and mortality rate reduction. Many existing detection methods on lung nodules can achieve high sensitivity but meanwhile introduce an excessive number of false-positive proposals, which is clinically unpractical. In this paper, we propose the multi-head detection and spatial attention network, shortly MHSnet, to address this crucial false-positive issue. Specifically, we first introduce multi-head detectors and skip connections to capture multi-scale features so as to customize for the variety of nodules in sizes, shapes, and types. Then, inspired by how experienced clinicians screen CT images, we implemented a spatial attention module to enable the network to focus on different regions, which can successfully distinguish nodules from noisy tissues. Finally, we designed a lightweight but effective false-positive reduction module to cut down the number of false-positive proposals, without any constraints on the front network. Compared with the state-of-the-art models, our extensive experimental results show the superiority of this MHSnet not only in the average FROC but also in the false discovery rate (2.64% improvement for the average FROC, 6.39% decrease for the false discovery rate). The false-positive reduction module takes a further step to decrease the false discovery rate by 14.29%, indicating its very promising utility of reducing distracted proposals for the downstream tasks relied on detection results.

Frame detection is an important part of the reconnaissance satellite receiver to identify the terrestrial application specific messages (ASM) / VHF data exchange (VDE) signal, and has been challenged by Doppler shift and message collision. A constant false alarm rate (CFAR) frame detection strategy insensitive to Doppler shift has been proposed in this paper. Based on the double Barker sequence, a periodical sequence has been constructed, and differential operations have been adopted to eliminate the Doppler shift. Moreover, amplitude normalization is helpful for suppressing the interference introduced by message collision. Simulations prove that the proposed CFAR frame detection strategy is very attractive for the reconnaissance satellite to identify the terrestrial ASM/VDE signal.

The object detection tasks based on edge computing have received great attention. A common concern hasn't been addressed is that edge may be unreliable and uploads the incorrect data to cloud. Existing works focus on the consistency of the transmitted data by edge. However, in cases when the inputs and the outputs are inherently different, the authenticity of data processing has not been addressed. In this paper, we first simply model the tampering detection. Then, bases on the feature insertion and game theory, the tampering detection and economic incentives mechanism (TDEI) is proposed. In tampering detection, terminal negotiates a set of features with cloud and inserts them into the raw data, after the cloud determines whether the results from edge contain the relevant information. The honesty incentives employs game theory to instill the distrust among different edges, preventing them from colluding and thwarting the tampering detection. Meanwhile, the subjectivity of nodes is also considered. TDEI distributes the tampering detection to all edges and realizes the self-detection of edge results. Experimental results based on the KITTI dataset, show that the accuracy of detection is 95% and 80%, when terminal's additional overhead is smaller than 30% for image and 20% for video, respectively. The interference ratios of TDEI to raw data are about 16% for video and 0% for image, respectively. Finally, we discuss the advantage and scalability of TDEI.

Wireless sensor networks are used in many areas such as war field surveillance, monitoring of patient, controlling traffic, environmental and building surveillance. Wireless technology, on the other hand, brings a load of new threats with it. Because WSNs communicate across radio frequencies, they are more susceptible to interference than wired networks. The authors of this research look at the goals of WSNs in terms of security as well as DDOS attacks. The majority of techniques are available for detecting DDOS attacks in WSNs. These alternatives, on the other hand, stop the assault after it has begun, resulting in data loss and wasting limited sensor node resources. The study finishes with a new method for detecting the UDP Reflection Amplification Attack in WSN, as well as instructions on how to use it and how to deal with the case.

In this paper, we study an underlay Cognitive Radio (CR) system with energy harvesting over Nakagami-m fading channel. This system consists of a secondary source, a secondary receiver, a primary receiver and a single eavesdropper. The source in the secondary network has one antenna and transmits information to the secondary receiver equipped with two separated antennas to operate in a Full-Duplex (FD) mode. The upper and lower bounds for the Strictly Positive Secrecy Capacity (SPSC) are derived and the numerical results demonstrate that the performance of the proposed system can be improved by increasing the average channel power gain between the source and the destination. Here, the lower and upper bounds are merged to form the exact SPSC when the total interference is below a predefined limit.

There has been a significant rise in the use of wireless sensor networks (WSNs) in the past few years. It is evident that WSNs operate in unlicensed spectrum bands [1]. But due to the increasing usage in unlicensed spectrum band this band is getting overcrowded. The recent development of cognitive radio technology [2, 3] has made possible the utilization of licensed spectrum band in an opportunistic manner. This paper studies an introduction to Cognitive Radio Technology, Cognitive Radio Wireless Sensor Networks, its Advantages & Challenges, Cognitive Radio Technology Applications and a comparative analysis of node clustering techniques in CWSN.

The internet has grown increasingly important in everyone's everyday lives due to the availability of numerous web services such as email, cloud storage, video streaming, music streaming, and search engines. On the other hand, attacks by computer programmes such as bots are a common hazard to these internet services. Captcha is a computer program that helps a server-side company determine whether or not a real user is requesting access. Captcha is a security feature that prevents unauthorised access to a user's account by protecting restricted areas from automated programmes, bots, or hackers. Many websites utilise Captcha to prevent spam and other hazardous assaults when visitors log in. However, in recent years, the complexity of Captcha solving has become difficult for humans too, making it less user friendly. To solve this, we propose creating a Captcha that is both simple and engaging for people while also robust enough to protect sensitive data from bots and hackers on the internet. The suggested captcha scheme employs animated artifacts, rotation, and variable fonts as resistance techniques. The proposed captcha technique proves successful against OCR bots with less than 15% accuracy while being easier to solve for human users with more than 98% accuracy.

Acoustic communication is a key enabler for underwater Internet of Things networks between autonomous underwater platforms. Underwater Internet of Things networks face a harsh communications environment and limited energy resources which makes them susceptible to interference, whether intentional (i.e., jamming) or unintentional. Resilient, power efficient waveforms and modulation schemes are needed for underwater acoustic communications in order to avoid outages and excessive power drain. We explore the impact of modulation scheme on the resiliency of underwater acoustic communications in the presence of channel impairments, interference, and jamming. In particular, we consider BFSK and OFDM schemes for underwater acoustic communications and assess the utility of Polar coding for strengthening resiliency.

5G has received significant interest from commercial as well as defense industries. However, resiliency in 5G remains a major concern for its use in military and defense applications. In this paper, we explore physical layer resiliency enhancements for 5G and use narrow-band Internet of Things (NB-IoT) as a study case. Two physical layer modifications, frequency hopping, and direct sequence spreading, are analyzed from the standpoint of implementation and performance. Simulation results show that these techniques are effective to harden the resiliency of the physical layer to interference and jamming. A discussion of protocol considerations for 5G and beyond is provided based on the results.

In recent times, Network-on-Chip (NoC) has become state of the art for communication in Multiprocessor System-on-Chip due to the existing scalability issues in this area. However, these systems are exposed to security threats such as extraction of secret information. Therefore, the need for secure communication arises in such environments. In this work, we present a communication protocol based on authenticated encryption with recovery mechanisms to establish secure end-to-end communication between the NoC nodes. In addition, a selected key agreement approach required for secure communication is implemented. The security functionality is located in the network adapter of each processing element. If data is tampered with or deleted during transmission, recovery mechanisms ensure that the corrupted data is retransmitted by the network adapter without the need of interference from the processing element. We simulated and implemented the complete system with SystemC TLM using the NoC simulation platform PANACA. Our results show that we can keep a high rate of correctly transmitted information even when attackers infiltrated the NoC system.

Visible light communication (VLC) is an important alternative and/or complementary technology for next generation indoor wireless broadband communication systems. In order to ensure data security for VLC in public areas, many studies in literature consider physical layer security (PLS). These studies generally neglect the reflections in the VLC channel and assume no inter symbol interference (ISI). However, increasing the data transmission rate causes ISI. In addition, even if the power of the reflections is small compared to the line of sight (LoS) components, it can affect the secrecy rate in a typical indoor VLC system. In this study, we investigate the effects of ISI and reflected channel components on secrecy rate in multiple-input single-output (MISO) VLC scenario utilized null-steering (NS) and artificial noise (AN) PLS techniques.

The Internet of Things (IoT) is a novel paradigm that enables the development of a slew of Services for the future of technology advancements. When it comes to IoT applications, the cyber and physical worlds can be seamlessly integrated, but they are essentially limitless. However, despite the great efforts of standardization bodies, coalitions, companies, researchers, and others, there are still a slew of issues to overcome in order to fully realize the IoT's promise. These concerns should be examined from a variety of perspectives, including enabling technology, applications, business models, and social and environmental consequences. The focus of this paper is on open concerns and challenges from a technological standpoint. We will study the differences in technical such Sigfox, NB-IoT, LoRa, and 6LowPAN, and discuss their advantages and disadvantage for each technology compared with other technologies. Demonstrate that each technology has a position in the internet of things market. Each technology has different advantages and disadvantages it depends on the quality of services, latency, and battery life as a mention. The first will be analysis IoT technologies. SigFox technology offers a long-range, low-power, low-throughput communications network that is remarkably resistant to environmental interference, enabling information to be used efficiently in a wide variety of applications. We analyze how NB-IoT technology will benefit higher-value-added services markets for IoT devices that are willing to pay for exceptionally low latency and high service quality. The LoRa technology will be used as a low-cost device, as it has a very long-range (high coverage).

Physical layer security has gained importance with the widespread use of wireless communication systems. Multiantenna systems and multi-point transmission techniques in 5G and beyond are promising techniques not only for enhancing data rates, but also physical layer security. Coordinated multipoint transmission is used for enhancing the service quality and decreasing inter-cell interference especially for cell-edge users. In this study, analysis of physical layer security enhancement via multi-antenna technologies and coordinated multi-point for 5G and beyond networks is provided. The proposed scheme is evaluated on calculations from real-life mobile network topologies. As a figure of performance, the secure and successful detection probability is computed with varying antenna array size, number of coordinated transmission points, and different service requirements.

Considered is a network of parallel wireless channels in which individual parties are engaged in secret communication under the protection of cooperative jamming. A strategic eavesdropper selects the most vulnerable channels to attack. Existing works usually suggest the defender allocate limited cooperative jamming power to various channels. However, it usually requires some strong assumptions and complex computation to find such an optimal power control policy. This paper proposes a probabilistic cooperative jamming scheme such that the defender focuses on protecting randomly selected channels. Two different cases regarding each channel’s eavesdropping capacity are discussed. The first case studies the general scenario where each channel has different eavesdropping capacity. The second case analyzes an extreme scenario where all channels have the same eavesdropping capacity. Two non-zero-sum Nash games model the competition between the network defender and an eavesdropper in each case. Furthermore, considering the case that the defender does not know the eavesdropper’s channel state information (CSI) leads to a Bayesian game. For all three games, we derive conditions for the existence of a unique Nash equilibrium (NE), and obtain the equilibria and the value functions in closed form.

Nowadays, source location privacy in underwater acoustic sensor networks (UASNs) has gained a lot of attention. The aim of source location privacy is to use specific technologies to protect the location of the source from being compromised. Among the many technologies available are fake packet technology, multi-path routing technology and so on. The fake packet technology uses a certain amount of fake packets to mask the transmission of the source packet, affecting the adversary's efficiency of hop-by-hop backtracking to the source. However, during the operation of the fake packet technology, the fake packet, and the source packet may interfere with each other. Focus on this, a fake packet time slot assignment-based source location privacy protection (FPTSA-SLP) scheme. The time slot assignment is adopted to avoid interference with the source packet. Also, a relay node selection method based on the handshake is further proposed to increase the diversity of the routing path to confuse the adversary. Compared with the comparison algorithm, the simulation results demonstrate that the proposed scheme has a better performance in safety time.

Nowadays, automotive products are intelligence intensive and thus inevitably handle multiple functionalities under the current high-speed networking environment. The embedded virtualization has high potentials in the automotive industry, thanks to its advantages in function integration, resource utilization, and security. The invention of ARM virtualization extensions has made it possible to run open-source hypervisors, such as Xen and KVM, for embedded applications. Nevertheless, there is little work to investigate the performance of these hypervisors on automotive platforms. This paper presents a detailed analysis of different types of open-source hypervisors that can be applied in the ARM platform. We carry out the virtualization performance experiment from the perspectives of CPU, memory, file I/O, and some OS operation performance on Xen and Jailhouse. A series of microbenchmark programs have been designed, specifically to evaluate the real-time performance of various hypervisors and the relevant overhead. Compared with Xen, Jailhouse has better latency performance, stable latency, and little interference jitter. The performance experiment results help us summarize the advantages and disadvantages of these hypervisors in automotive applications.

Modern cars are becoming more accessible targets for cyberattacks due to the proliferation of wireless communication channels. The intra-vehicle Controller Area Network (CAN) bus lacks authentication, which exposes critical components to interference from less secure, wirelessly compromised modules. To address this issue, we propose vProfile, a sender authentication system based on voltage fingerprints of Electronic Control Units (ECUs). vProfile exploits the physical properties of ECU output voltages on the CAN bus to determine the authenticity of bus messages, which enables the detection of both hijacked ECUs and external devices connected to the bus. We show the potential of vProfile using experiments on two production vehicles with precision and recall scores of over 99.99%. The improved identification rates and more straightforward design of vProfile make it an attractive improvement over existing methods.

Compressive beamforming has been successfully applied to the estimation of the direction of arrival (DOA) of array signals, and has higher angular resolution than traditional high-resolution beamforming methods. However, most of the existing compressive beamforming methods are based on narrow signal models. Wideband signal processing using these existing compressive beamforming methods is to divide the frequency band into several narrow-bands and add up the beamforming results of each narrow-band. However, for sonar application, signals usually consist of continuous spectrum and line spectrum, and the line spectrum is usually more than 10dB higher than the continuous spectrum. Due to the large difference of signal-to-noise ratio (SNR) of each narrow-band, different regularization parameters should be used, otherwise it is difficult to get an ideal result, which makes compressive beamforming highly complicated. In this paper, a compressive beamforming method based on spatial resampling for uniform linear arrays is proposed. The signals are converted into narrow-band signals by spatial resampling technique, and compressive beamforming is then performed to estimate the DOA of the sound source. Experimental results show the superiority of the proposed method, which avoids the problem of using different parameters in the existing compressive beamforming methods, and the resolution is comparable to the existing methods using different parameters for wideband models. The spatial-resampling compressive beamforming has a better robustness when the regularization parameter is fixed, and exhibits lower levels of background interference than the existing methods.

In this fifth generation of vehicular communication, the security against various malicious attacks are achieved by using malicious vehicles identification and trust management (MAT) algorithm. Basically, the proposed MAT algorithm performs in two dimensions, they are (i) Node trust and (ii) information trust accompanied with a digital signature and hash chain concept. In node trust, the MAT algorithm introduces the special form of key exchanging algorithm to every members of public group key, and later the vehicles with same target location are formed into cluster. The public group key is common for each participant but everyone maintain their own private key to produce the secret key. The proposed MAT algorithm, convert the secrete key into some unique form that allows the CMs (cluster members) to decipher that secrete key by utilizing their own private key. This key exchanging algorithm is useful to prevent the various attacks, like impersonate attack, man in middle attack, etc. In information trust, the MAT algorithm assigns some special nodes (it has common distance from both vehicles) for monitoring the message forwarding activities as well as routing behavior at particular time. This scheme is useful to predict an exact intruder and after time out the special node has dropped all the information. The proposed MAT algorithm accurately evaluates the trustworthiness of each node as well as information to control different attacks and become efficient for improving a group lifetime, stability of cluster, and vehicles that are located on their target place at correct time.

Physical layer security has a paramount importance in tactical wireless networks. Traditional approaches may not fulfill all requirements, demanding additional sophisticated techniques. Thus, Combined Interference and Communications (CIC) emerges as a strategy against message interception in Cognitive Radio Military Networks (CRMN). Since CIC adopts an interference approach under specific CRMN requirements and characteristics, it saves great energy and reduces the receiver detection factor when compared to previous proposals in the literature. However, previous CIC analyses were conducted under vaguely realistic channel models. Thus, the focus of this paper is two-fold. Firstly, we identify more realistic channel models to achieve tactical network scenario channel parameters. Additionally, we use such parameters to evaluate CIC suitability to increase CRMN physical layer security. Numerical experiments and emulations illustrate potential impairments on previous work due to the adoption of unrealistic channel models, concluding that CIC technique remains as an upper limit to increase physical layer security in CRMN.

In recent years, a new type of DDoS attacks against backbone routing links have appeared. They paralyze the communication network of a large area by directly congesting the key routing links concerning the network accessibility of the area. This new type of DDoS attacks make it difficult for traditional countermeasures to take effect. This paper proposes and implements an attack detection method based on non-cooperative active measurement. Experiments show that our detection method can efficiently perceive changes of network link performance and assist in identifying such new DDoS attacks. In our testbed, the network anomaly detection accuracy can reach 93.7%.

Random number generators (RNGs) has an extensive application area from cryptography to simulation software. Piecewise linear one-dimensional (PL1D) maps are commonly preferred structures used as the basis of RNGs due to their theoretically proven chaotic behavior and ease of implementation. In this work, a skew-tent map based RNG is designed by using the chaotic sampling method in TSMC 180 nm CMOS process. Simulation data of the designed RNG is validated by the statistical randomness tests of the FIPS-140-2 and NIST 800-22 suites. The proposed RNG has three key features: the generated bitstreams can fulfill the randomness tests without using any post processing methods; the proposed RNG has immunity against external interference thanks to the chaotic sampling method; and higher bitrates (4.8 Mbit/s) can be achieved with relatively low power consumption (9.8 mW). Thus, robust RNG systems can be built for high-speed security applications with low power by using the proposed architecture.

Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA) is a type of automatic program to determine whether the user is human or not. The most common type of CAPTCHA is a kind of message interpretation by twisting the letters and adding slight noises in the background, plays a role of verification code. In this paper, we will introduce the basis of Convolutional Neural Network first. Then based on the handwritten digit recognition using CNN, we will develop a network for CAPTCHA image recognition.

Biometric data is prone to attacks and threats from hackers who are professionals in cyber-crimes. Therefore, securing the data is very essential. Steganographic approach, which is a process of concealing data, is proposed as a solution to this. Biometrics are hidden inside other biometrics for safe storage and secure transmission. Also, it is designed to be robust against attacks, and cannot be detected easily. The intention of this paper is to highlight a method of hiding one image in another image by using mid position value(mpv) technique. Here we have to choose the secret biometric on which Arnold transform will be applied resulting in a scrambled version of the secret biometric. This will be enveloped inside cover image which results in a stego-image. Lastly, hidden secret biometric will be decoded from this stego image, which will first result in a scrambled secret biometric. Inverse Arnold Transform will be applied on this to finally result in the decoded secret biometric. The paper further explains the working and processes in detail.