Protocol Suite Research Articles

Formal Security Analysis of the OpenID FAPI 2.0 Family of Protocols: Accompanying a Standardization Process

FAPI 2.0 is a suite of Web protocols developed by the OpenID Foundation’s FAPI Working Group (FAPI WG) for third-party data sharing and digital identity in high-risk environments. Even though the specifications are not completely finished, several important entities have started to adopt the FAPI 2.0 protocols, including Norway’s national HelseID, Australia’s Consumer Data Standards, as well as private companies like Authlete and Australia-based connectID; the predecessor FAPI 1.0 is in widespread use with millions of users. The FAPI WG asked us to accompany the standardization of the FAPI 2.0 protocols with a formal security analysis to proactively identify vulnerabilities before widespread deployment and to provide formal security guarantees for the standards. In this paper, we report on our analysis and findings. Our analysis is based on a detailed model of the Web infrastructure, the so-called Web Infrastructure Model (WIM), which we extend to be able to carry out our analysis of the FAPI 2.0 protocols including important extensions like FAPI-CIBA. Based on the (extended) WIM and formalizations of the security goals and attacker model laid out in the FAPI 2.0 specifications, we provide a formal model of the protocols and carry out a formal security analysis, revealing several attacks. We have worked with the FAPI WG to fix the protocols, resulting in several amendments to the specifications. With these changes in place, we have adjusted our protocol model and formally proved that the security properties hold true under the strong attacker model defined by the FAPI WG.

Mn(I)‐Catalyzed C−H Allylation of Indoles with 2‐Vinylaziridines

AbstractMn(CO)5Br‐catalyzed reaction of 1‐(2‐pyrimidyl)indoles with 1‐sulfonyl‐2‐vinylaziridines in THF in the presence of 0.25 equiv. of NaOAc affords 2‐allylated indoles in 31 % to 100 % yields. The protocol suits for 3‐, 4‐, 5‐, 6‐, and 7‐substituted indoles and N‐(2‐pyrimidyl)pyrroles as well as various 1‐(arylsulfonyl)‐2‐vinylaziridines such as 1‐(phenylsulfonyl)‐2‐vinylaziridine, 1‐(naphthalen‐2‐ylsulfon‐yl)‐2‐vinylaziridine, and 1‐(substituted phenylsulfonyl)‐2‐vinylazirid‐ines. Functional groups including alkyl, alkoxy, halogen, CHO, COOMe, CF3, CN, and NO2 groups are tolerated.

A Target Class Ligandability Evaluation of WD40 Repeat-Containing Proteins.

Target class-focused drug discovery has a strong track record in pharmaceutical research, yet public domain data indicate that many members of protein families remain unliganded. Here we present a systematic approach to scale up the discovery and characterization of small molecule ligands for the WD40 repeat (WDR) protein family. We developed a comprehensive suite of protocols for protein production, crystallography, and biophysical, biochemical, and cellular assays. A pilot hit-finding campaign using DNA-encoded chemical library selection followed by machine learning (DEL-ML) to predict ligands from virtual libraries yielded first-in-class, drug-like ligands for 7 of the 16 WDR domains screened, thus demonstrating the broader ligandability of WDRs. This study establishes a template for evaluation of protein family wide ligandability and provides an extensive resource of WDR protein biochemical and chemical tools, knowledge, and protocols to discover potential therapeutics for this highly disease-relevant, but underexplored target class.

Oblivious and distributed firewall policies for securing firewalls from malicious attacks

Firewalls are effective in preventing attacks initiated from outside of an organization’s network, but they are vulnerable to external threats, e.g. ransomware attacks may expose sensitive firewall data to malicious entities or disable network protection from the firewall. In this paper, we present Obliv-FW: a novel distributed architecture and a suite of protocols to obliviously manage and evaluate firewall rules and policies to prevent external attacks oriented to the firewall data. Obliv-FW alleviates this issue by obfuscating the blacklist or whitelist and distributing the function of evaluating these lists across multiple servers residing in different access control zones of the organization’s internal network. Thus, both accessing and altering the rules are considerably more difficult thereby providing better protection to the local network as well as greater security for the firewall itself. Obliv-FW is developed by leveraging the existing secure multi-party computation techniques. Our empirical results show that the overhead of Obliv-FW is small, and it can be a very valuable tool to mitigate the ever-increasing threats to a private network from external attacks including ransomware attacks.

Analysing TCP Traffic Congestion Algorithms for Wired Links Based on NS3

An essential component of the Internet Protocol Suite is Transmission Control Protocol (TCP). In this article, the effectiveness of three distinct TCP congestion control algorithms, namely Reno, NewReno, and Cubic, in the context of wired lines has been examined. In a series of simulations, we changed the congestion control technique while maintaining the other parameters constantly using Network Simulator (NS3). With its distinctive fast recovery mechanism, TCP Reno has shown a strong ability to recover from packet losses quickly, cutting down on the time needed to go back to the highest attainable throughput. The TCP congestion control technique selected can have a big impact on a network's performance, notably in terms of throughput and stability. While our findings demonstrate major differences between the examined algorithms.

Integrating Dynamic Network Analysis with AI for Enhanced Epitope Prediction in PD-L1:Affibody Interactions.

Understanding binding epitopes involved in protein-protein interactions and accurately determining their structure are long-standing goals with broad applicability in industry and biomedicine. Although various experimental methods for binding epitope determination exist, these approaches are typically low throughput and cost-intensive. Computational methods have potential to accelerate epitope predictions; however, recently developed artificial intelligence (AI)-based methods frequently fail to predict epitopes of synthetic binding domains with few natural homologues. Here we have developed an integrated method employing generalized-correlation-based dynamic network analysis on multiple molecular dynamics (MD) trajectories, initiated from AlphaFold2Multimer structures, to unravel the structure and binding epitope of the therapeutic PD-L1:Affibody complex. Both AlphaFold2 and conventional molecular dynamics trajectory analysis were ineffective in distinguishing between two proposed binding models, parallel and perpendicular. However, our integrated approach, utilizing dynamic network analysis, demonstrated that the perpendicular mode was significantly more stable. These predictions were validated using a suite of experimental epitope mapping protocols, including cross-linking mass spectrometry and next-generation sequencing-based deep mutational scanning. Conversely, AlphaFold3 failed to predict a structure bound in the perpendicular pose, highlighting the necessity for exploratory research in the search for binding epitopes and challenging the notion that AI-generated protein structures can be accepted without scrutiny. Our research underscores the potential of employing dynamic network analysis to enhance AI-based structure predictions for more accurate identification of protein-protein interaction interfaces.

Pincer Nickel-Catalyzed Olefination of Alcohols with Benzylphosphine Oxides.

N,N,P-Pincer nickel complexes effectively catalyze reaction of alcohols with benzylphosphine oxides to form alkenes in good yields. The protocol suits for a wide scope of substrates and generates only E-configurated alkenes. The method also shows good compatibility of functional groups. Methoxy, methylthio, trifluoromethyl, ketal, fluoro, chloro, bromo, thienyl, and furyl groups are tolerated. The mechanism studies support that the reaction proceeds through catalytic dehydrogenation of alcohols to aldehydes or ketones followed by condensation with benzyldiphenylphosphine oxides in the presence of KOtBu.

Comprehensive analysis of dynamic topology sensor linkage for the internet of things

In today’s developing IoT world, wireless sensor interactions are critical. To ensure full system IP compatibility, industry efforts are focused on standardizing the WSN protocol suite and enabling the second generation of IoT devices to be produced. As a result of their robust communications and conformance to less verbose WSN features such as sleep cycles required to keep end nodes’ total energy consumption low, the WSN protocols are strong contenders for use as a highly useable implementation layer for the IoT. Existing smart systems make use of system assets for critical IoT functions. Compared to a wired configuration, wireless sensors are easier to install and provide more device flexibility. As sensor technology advances, WSNs will become a critical component of the IoT and an essential tool for achieving the IoT paradigm’s goal. It’s also crucial to think about whether or not a WSN’s sensors should be fully linked into the IoT’s. For WSNs, a multi-objective optimization technique for selecting the most energy-efficient CH is described. The CHs for each lattice were first selected using a candidate CH selection method. Energy waste and data redundancy were also decreased by using multi-hop networking. An inventive new method has also been devised to ensure perfect implementation. The Evolutionary Algorithm (EA) model and optimization techniques used in this work provided an energy-efficient Machine Learning (ML) strategy for selecting WSN CH. First, the CH of each lattice was calculated using a candidate CH selection method. According to the results of the simulation, the suggested model’s performance is superior to traditional approaches in terms of network lifespan, energy efficiency, and reduced consumption.

Suillus: an emerging model for the study of ectomycorrhizal ecology and evolution.

Research on mycorrhizal symbiosis has been slowed by a lack of established study systems. To address this challenge, we have been developing Suillus, a widespread ecologically and economically relevant fungal genus primarily associated with the plant family Pinaceae, into a model system for studying ectomycorrhizal (ECM) associations. Over the last decade, we have compiled extensive genomic resources, culture libraries, a phenotype database, and protocols for manipulating Suillus fungi with and without their tree partners. Our efforts have already resulted in a large number of publicly available genomes, transcriptomes, and respective annotations, as well as advances in our understanding of mycorrhizal partner specificity and host communication, fungal and plant nutrition, environmental adaptation, soil nutrient cycling, interspecific competition, and biological invasions. Here, we highlight the most significant recent findings enabled by Suillus, present a suite of protocols for working with the genus, and discuss how Suillus is emerging as an important model to elucidate the ecology and evolution of ECM interactions.

Performance, privacy, and security issues of TCP/IP at the application layer: A comprehensive survey

TCP/IP is the backbone of modern network communication, connecting devices across the world. TCP/IP at its core is a suite of protocols that enables the transmission of data between computers, facilitating the foundation of the interconnected global network. At the Application Layer of TCP/IP is where the interaction between software applications and the network occurs. The user-centric protocols such as HTTP, SMTP, FTP, POP3, IMAP and DNS facilitate various tasks at this layer such as web browsing, email communication, and file transfer. This comprehensive survey conducted an exploration of the performance, security and privacy issues at the application layer of the TCP/IP. It initiated by providing a background of TCP/IP model, it’s architecture and the core characteristics, with major focus on the application layer. This paper aimed to discuss the state-of-the-art of performance, privacy and security concerns in TCP/IP application layer. It also proposed future research areas to equip researchers, practitioners, policy makers and the decision makers with tangible knowledge, offering guidance in navigating the performance, privacy and security concerns in TCP/IP Application Layer. It aimed to discuss the current performance, privacy and security research gaps at the Application Layer of the TCP/IP Model. The findings of this research sheds light on the performance, privacy and security issues while suggesting the countermeasures to strengthen and optimize the overall performance, security and privacy of TCP/IP model at the application layer. The paper finally suggests future directions and research areas at the TCP/IP application layer.

A comprehensive survey of performance, security and privacy issues in the network interface layer of the TCP/IP

The network interface layer of the TCP/IP protocol suite, primarily comprised of the Internet Protocol (IP), serves as the backbone of modern internet communication. With its efficient data delivery, The network interface layer, presents key challenges in terms of performance, security, and privacy. This comprehensive survey delves into these three crucial aspects, analyzing the inherent vulnerabilities, limitations of the interface layer, and provide solutions of the related problems. The performance analysis explores throughput, latency, and bandwidth constraints, along with solutions such as bandwidth allocation and optimization techniques. Vulnerabilities within Network Interface Layer, including denial-of-service attacks and MAC address spoofing, are discussed, along with a review of existing security mechanisms. Privacy flaws are examined, covering MAC address tracking, profiling risks, and anonymization techniques, while also addressing privacy considerations on the Internet of Things. The survey analyzes several case studies providing comparative analysis of the network interface layer protocols, with support of the real world scenarios including performance analysis in high density environment, and security and privacy risks in smart homes networks. The findings provide a comprehensive understanding of the complexities surrounding performance, security, and privacy issues future directions and potential solutions.

Recommendations for Uniform Variant Calling of SARS-CoV-2 Genome Sequence across Bioinformatic Workflows.

Genomic sequencing of clinical samples to identify emerging variants of SARS-CoV-2 has been a key public health tool for curbing the spread of the virus. As a result, an unprecedented number of SARS-CoV-2 genomes were sequenced during the COVID-19 pandemic, which allowed for rapid identification of genetic variants, enabling the timely design and testing of therapies and deployment of new vaccine formulations to combat the new variants. However, despite the technological advances of deep sequencing, the analysis of the raw sequence data generated globally is neither standardized nor consistent, leading to vastly disparate sequences that may impact identification of variants. Here, we show that for both Illumina and Oxford Nanopore sequencing platforms, downstream bioinformatic protocols used by industry, government, and academic groups resulted in different virus sequences from same sample. These bioinformatic workflows produced consensus genomes with differences in single nucleotide polymorphisms, inclusion and exclusion of insertions, and/or deletions, despite using the same raw sequence as input datasets. Here, we compared and characterized such discrepancies and propose a specific suite of parameters and protocols that should be adopted across the field. Consistent results from bioinformatic workflows are fundamental to SARS-CoV-2 and future pathogen surveillance efforts, including pandemic preparation, to allow for a data-driven and timely public health response.

Review of the OSI Model and TCP/IP Protocol Suite on Modern Network Communication

Layered approaches to networking are possible. Network architects categorize protocols in order to simplify their designs. Each layer has its own protocol for talking to the outside world. Every component of the network implements some of the nth layer. Messages are sent back and forth between these parts. Layer n protocol data units [n-PDU] are the official name for these transmissions. All the steps necessary for efficient conversation are covered and these steps are organized into layers for easy comprehension. Layered architecture describes this kind of planning for a communications system. The OSI model is a framework for developing and implementing network-based software applications. It also serves as a basis for the development of new networking protocol hardware, and architectures. This document compares and contrasts the OSI Reference Model seven layers with those of the TCP/IP Model four. There are distinct roles at each successive level. All Internet communication duties may be traced back to the TCP/IP reference model.

Use of QUIC for Mobile-Oriented Future Internet (Q-MOFI)

With the proliferation of mobile devices and various mobile services, ensuring smooth mobility for users has become a major challenge. The future internet is expected to be more mobile-friendly, with advancing technologies that will transform internet management in the coming decades. These technological advancements will help address mobility issues and provide a better internet experience for mobile devices and users. The transport layer plays a crucial role in the internet protocol suite by enabling communication between applications running on different servers. However, the widely used protocols, TCP and UDP, have several limitations, such as unreliability and slow performance due to three-way handshakes. To tackle these issues, Google introduced quick UDP internet connections (QUIC). QUIC aims to enhance latency, delay, and data transmission reliability. Q-MOFI, a future internet architecture focused on mobile devices and based on QUIC, strives to achieve these goals. Moreover, it enhances throughput by implementing multiplexing. Q-MOFI outperforms traditional UDP-based MOFI in terms of throughput gains, minimizing packet loss, and reducing binding operation latency, even when the number of hosts increases. The efficiency of this model has been validated through experimental testing.

Paramedic Education and Training for the Management of Patients Presenting with Low-Acuity Clinical Conditions: A Scoping Review.

Ambulance services around the world are increasingly attending to calls for non-emergency conditions. These lower-acuity conditions do not always require patients to be transported to the emergency department. Consequently, over the past two decades, ambulance services have implemented strategies to support paramedics in diverting non-urgent patients to alternative care pathways. However, assessing and managing low-acuity conditions can be challenging for paramedics, especially when education and training has traditionally focussed on emergency care. This scoping review explores the education and training provided to paramedics on low-acuity clinical conditions and the use of alternative care pathways. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews was applied. The databases searched included Scopus, CINAHL, Embase, Emcare, and MEDLINE (PubMed). The search identified one-hundred sixty-six records, with a total of nine articles reviewed after the removal of duplicates and the screening process. The articles were diverse, with education and training ranging from university degrees for extended care practitioners to short in-service-based training for a suite of protocols or assessment tools. However, the literature addressing education and training on low-acuity conditions and alternative care pathways is limited, with the type and length of education programs appearing to influence practice. There is a need for further research to establish a low acuity education model.

A Wireless Voting System Using Wi-Fi-Based Microcontrollers and Face Verification

Voting systems nowadays are highly interesting due to their importance in expressing opinions. The proposed work aims to design a cost-effective and reliable Electronic Voting System (EVS) that can tackle the issues faced by manual election. The system uses small and lowcost microcontrollers with Wi-Fi network connectivity to avoid the issues of installing wire connections. Eligible voters are authenticated by recognizing their faces using deep neural networks (VGG-16 model). The Wi-Fi connections between the server and the clients are carried out through the Internet Protocol suite (TCP/IP) transmission method to ensure data arrival without loss. The client’s side comprises four small and cheap microcontrollers known as ESP8266-01, whereas the server side contains one NodeMCU ESP8266-12E microcontroller connected to a program computer. The voting results are displayed using the Visual Basic programming language. The system is specifically designed to facilitate voting on a particular opinion by providing two options: (Yes) and (No). Besides, it can be utilized for electing a committee manager or group leader and can be expanded to accommodate more options. The VGG model’s robustness is demonstrated through experiments, achieving 99.12% accuracy on Faces96 images and 98.61% on our database. Moreover, the practical implementation of the election process demonstrates that the system is highly reliable, secure and cost-effective.

CheckShake: Passively Detecting Anomaly in Wi-Fi Security Handshake Using Gradient Boosting Based Ensemble Learning

Recently, a number of attacks have been demonstrated (like key reinstallation attack, called KRACK) on WPA2 protocol suite in Wi-Fi WLAN, for which a patching is often challenging. In this paper, we design and implement a system, called CheckShake, to passively detect anomalies in the handshake of Wi-Fi security protocols, in particular WPA2, between a client and an AP using COTS radios. Our proposed system works without decrypting any traffic and sniffing on multiple channels in parallel. It uses a state machine model for grouping Wi-Fi handshake packets and then perform deep packet inspection to identify the symptoms of the anomaly in specific stages of a handshake session. Our implementation of CheckShake does not require any modification to the firmware of the client or the AP or the COTS devices, it only requires to be physically placed within the range of the AP and its clients. We use both the publicly available dataset and our own data set for performance analysis of CheckShake. Using gradient boosting-based supervised machine learning (ML) models, we show that an accuracy around 98.50% with no false positive can be achieved using CheckShake in open sourced data that has non-zero probability of missing packets per group of packets.

Potrzeba nowych protokolow transportowych w Internecie

TThe TCP/IP protocol suite is widely used in IP networks, regardless of diverse environments and usage scenarios. Due to the fact of being the basic concept of organizing the work of the Internet, it is the subject of interest and constant analysis of operators, users, network researchers, and designers. The Internet is a "living" organism in which new needs appear all the time. This is particularly important due to the emerging new application requirements - at the highest level of network architecture, and at the same time, completely new ways of transmitting messages related to new technologies and reception techniques, allowing for parallelization of messages transfer and lossless switching/handover between several interfaces. The paper highlights the expectations and requirements related, in particular, to new "multi-object" applications, as well as the limitations resulting from the high inertia observed on the side of the IP network transport infrastructure. Taking into account both the limitations and the formulated requirements, the selected end-to-end transport protocols have been characterized. More attention was paid to two protocols implementing multi-stream transfers, namely SCTP and QUIC.

Introduction of machine learning with applications to communication system

<p>This research paper presents a brief introduction to the key point of Machine Learning (ML) with the application to communication systems. Due to the exceptional accessibility of software and data abilities, there is a great deal of interest in using digital information machine learning thinking to solve issues in a variety of fields. Regarding the phenomenal amount of information and computer facilities, there is a lot more interest in using content-supervised learning methods to resolve obstacles where engineering course techniques are restricted by theoretical or methodological problems. This study starts by clarifying when and why comparable strategies may well be effective. It then goes into the fundamentals of supervised and unsupervised at a high level. Where traditional engineering solutions are being developed Modelling or algorithmic flaws are posing a problem. This paper begins by answering the why and when of these questions. Such methods can be beneficial to resolve real-time problems. It then goes into the fundamentals of classification and regression problems at a world-class level. Exemplifying software to communications infrastructure is presented both for the structured and unstructured interviews by identifying roles performed first at the network’s perimeter and cloud bits at multiple levels of the internet protocol suite, with a concentration on the application layer. The core contributions of this research study are as follows: (a) this research study explores the machine learning applications in communication system and networks optimization; (b) it offers an analysis of contributions of machine learning-based anomaly detection approaches to mitigate the security threat and maintains the integrity of entire communication network; (c) additionally, this research study provides further directions for research, future trends as well as challenges including the requirement for intelligent methods for network optimization, signal processing, etc.</p>

Towards Efficient and Privacy-Preserving High-Dimensional Range Query in Cloud

The Internet of Things (IoT) boom has enabled Internet Service Providers (ISPs) to collect an enormous amount of high-dimensional data. Performing range queries on such data can effectively reuse them to help ISPs offer better services. Owing to the low cost and high resource utilization of cloud computing, an increasing number of ISPs are inclined to outsource data and services to it. However, as the cloud is not fully trusted, data need to be encrypted before being outsourced, which inevitably hinders many query services, e.g., range queries. Various schemes were proposed for privacy-preserving range queries, yet they struggled to extend to high-dimensional scenarios and did not support dimension selection. Aiming at this challenge, in this paper, we propose an efficient and privacy-preserving high-dimensional range query scheme (PHRQ) based on an iMinMax tree while supporting dimension selection. Specifically, we first build an iMinMax tree for high-dimensional data and utilize a symmetric homomorphic encryption technique to design a suite of privacy-preserving protocols to achieve secure high-dimensional range queries. Then, we design a sub-dimensional range determination protocol to support dimension selection. Further, based on the iMinMax tree and our privacy-preserving protocols, we propose our PHRQ scheme. Finally, security analysis shows that our scheme is privacy-preserving, and performance evaluation demonstrates that our scheme is efficient in high-dimensional range query processing.