Explosive growth in Information Technology has enabled many innovative application areas such as large-scale outdoor vehicular networks for vehicle-to-vehicle communications. By providing time-sensitive and location-aware information, vehicular networks can contribute to a safer and more efficient driving experience. However, the performance of vehicular networks requires robust and real-time data communications and is impacted by high mobility, intermittent connectivity, and unreliability of the wireless channel. In this paper, a novel adaptive distributed cooperative medium access control (ADC-MAC) protocol is proposed in order to address the inherent problems in the IEEE 802.11 standard when employed in vehicular networks. ADC-MAC exploits spatial diversities to maximize the system throughput as well as the service range of vehicular networks. This is accomplished through adaptively selecting the most suitable helper and transmission mode for transmit/receive pairs among direct transmission (DT), cooperative relay (CR) transmission and two-hop relay (TR) transmission, in accordance with the channel quality and the positioning of relay nodes. Both our Markov Chain modeling based theoretical analysis and ns-2 simulation experiments show that our ADC-MAC protocol outperforms existing schemes under the same network scenarios and maximizes the achieved system throughput and service distance. Index Terms-MAC Protocol, Cooperative Relaying, VehicularNetworks.

Advances in wireless multimedia communication technologies enable new types of pervasive and ubiquitous applications such as mobile health care, environmental monitoring, facility monitoring and traffic surveillance. Among different factors concerned, energy efficiency is one of the most challenging issues in multimedia communication due to the resource constraints, and the requirements for high bandwidth and low transmission delay. In this survey, we provide a broad picture of the stateof-the-art energy efficient techniques that have been proposed in wireless multimedia communication for resource-constrained systems such as wireless sensor networks and mobile devices.Following the essential stages required for multimedia communication, we categorize these techniques into two groups: multimedia compression techniques and multimedia transmission techniques. In the first group, we introduce the state-of-the-art compression algorithms and perform analyses and evaluations on energy efficiency in applying these compression algorithms to resource-constrained multimedia transmission systems. In the second group, we will further categorize the energy efficient transmission techniques into two sub-categories according to their different communication architectures. We review both cross-layer communication, including Unequal Error Protection (UEP), and independent-layer communication, focusing on Routing, MAC, and Physical layer protocols. We present the basic problem statement and objectives of these techniques, and survey multiple potential approaches that have been reported in the literature.Our focus in this survey is to provide insight into different research directions to improve energy efficiency in wireless multimedia communication protocols for future developments.

Covert channels exploit side channels within existing network resources to transmit secret messages. They are integrated into the elements of network resources that were not even designed for the purpose of communication. This means that traditional security features like firewalls cannot detect them. Their ability to evade detection makes covert channels a grave security concern. Hence, it is imperative to detect and disrupt them. However, a generic mechanism that can be used to detect a large variety of covert channels is missing. In this paper, we propose a Support Vector Machine (SVM)-based framework for reliable detection of covert communications. The machine learning framework utilizes the fingerprints derived from the traffic under investigation to classify the traffic as covert or overt. We trained our classifier using the fingerprints from four popular and diverse covert timing channel algorithms and tested each of them independently. We have shown that the machine learning framework has great potential to blindly detect covert channels, even when the covert message size is reduced. His research interests include theoretical and mathematical modeling, wireless communications, signal processing, high-speed networks, network security, among others.

We introduce CyBERT, a cybersecurity feature claims classifier based on bidirectional encoder representations from transformers and a key component in our semi-automated cybersecurity vetting for industrial control systems (ICS). To train CyBERT, we created a corpus of labeled sequences from ICS device documentation collected across a wide range of vendors and devices. This corpus provides the foundation for fine-tuning BERT’s language model, including a prediction-guided relabeling process. We propose an approach to obtain optimal hyperparameters, including the learning rate, the number of dense layers, and their configuration, to increase the accuracy of our classifier. Fine-tuning all hyperparameters of the resulting model led to an increase in classification accuracy from 76% obtained with BertForSequenceClassification’s original architecture to 94.4% obtained with CyBERT. Furthermore, we evaluated CyBERT for the impact of randomness in the initialization, training, and data-sampling phases. CyBERT demonstrated a standard deviation of ±0.6% during validation across 100 random seed values. Finally, we also compared the performance of CyBERT to other well-established language models including GPT2, ULMFiT, and ELMo, as well as neural network models such as CNN, LSTM, and BiLSTM. The results showed that CyBERT outperforms these models on the validation accuracy and the F1 score, validating CyBERT’s robustness and accuracy as a cybersecurity feature claims classifier.

High Speed Railway (HSR) provides its customers not only safety, security, comfort and on-time commuting, but also a fast transportation alternative to air travel or regular passenger rail services. Providing these benefits would not be possible without the tremendous growth and prevalence of wireless communication technologies. Due to advances in wireless communication systems, both trains and passengers are connected through high speed wireless networks to the Internet, data centers and railroad control centers. Railroad communities, academia, related industries and standards bodies, even the European Space Agency, are involved in advancing developments of HSR for highly connected train communication systems. The goal of these efforts is to provide the capabilities for uninterrupted high-speed fault-tolerant communication networks for all possible geographic, structural and weather conditions. This survey provides an overview of the current state-of-the-art and future trends for wireless technologies aiming to realize the concept of HSR communication services. Our goal is to highlight the challenges for these technologies, including GSM-R, Wi-Fi, WIMAX, LTE-R, RoF, LCX & Cognitive Radio, the offered solutions, their performance, and other related issues. Currently, providing HSR services is the goal of many countries across the globe. Europe, Japan & Taiwan, China, as well as North & South America have increased their efforts to advance HSR technologies to monitor and control not only the operations but also to deliver extensive broadband solutions to passengers. This survey determined a trend of the industry to transition control plane operations towards narrowband frequencies, i.e. LTE400/700, and to utilize concurrently other technologies for broadband access for passengers such that services of both user and train control systems are supported. With traditional technologies, a tradeoff was required and often favored train control services over passenger amenities. However, with the advances in communication systems, such as LTE-R and cognitive radios, it is becoming possible for system designers to offer rich services to passengers while also providing support for enhanced train control operations such as Positive Train Control. S. Banerjee et al.