Orbit Weighting Scheme in the Context of Vector Space Information Retrieval

This study introduces the Orbit Weighting Scheme(OWS),a novel approach aimed at enhancing the precision and efficiency of Vector Space information retrieval(IR)models,which have traditionally relied on weighting schemes like tf-idf and BM25.These conventional methods often struggle with accurately capturing document relevance,leading to inefficiencies in both retrieval performance and index size management.OWS proposes a dynamic weighting mechanism that evaluates the significance of terms based on their orbital position within the vector space,emphasizing term relationships and distribution patterns overlooked by existing models.Our research focuses on evaluating OWS’s impact on model accuracy using Information Retrieval metrics like Recall,Precision,InterpolatedAverage Precision(IAP),andMeanAverage Precision(MAP).Additionally,we assessOWS’s effectiveness in reducing the inverted index size,crucial for model efficiency.We compare OWS-based retrieval models against others using different schemes,including tf-idf variations and BM25Delta.Results reveal OWS’s superiority,achieving a 54%Recall and 81%MAP,and a notable 38%reduction in the inverted index size.This highlights OWS’s potential in optimizing retrieval processes and underscores the need for further research in this underrepresented area to fully leverage OWS’s capabilities in information retrieval methodologies.

Design of an Efficient and Provable Secure Key Exchange Protocol for HTTP Cookies

Cookies are considered a fundamental means of web application services for authenticating various Hypertext Transfer Protocol(HTTP)requests andmaintains the states of clients’information over the Internet.HTTP cookies are exploited to carry client patterns observed by a website.These client patterns facilitate the particular client’s future visit to the corresponding website.However,security and privacy are the primary concerns owing to the value of information over public channels and the storage of client information on the browser.Several protocols have been introduced that maintain HTTP cookies,but many of those fail to achieve the required security,or require a lot of resource overheads.In this article,we have introduced a lightweight Elliptic Curve Cryptographic(ECC)based protocol for authenticating client and server transactions to maintain the privacy and security of HTTP cookies.Our proposed protocol uses a secret key embedded within a cookie.The proposed protocol ismore efficient and lightweight than related protocols because of its reduced computation,storage,and communication costs.Moreover,the analysis presented in this paper confirms that proposed protocol resists various known attacks.

Enhancing Cybersecurity through Cloud Computing Solutions in the United States

This study investigates how cybersecurity can be enhanced through cloud computing solutions in the United States. The motive for this study is due to the rampant loss of data, breaches, and unauthorized access of internet criminals in the United States. The study adopted a survey research design, collecting data from 890 cloud professionals with relevant knowledge of cybersecurity and cloud computing. A machine learning approach was adopted, specifically a random forest classifier, an ensemble, and a decision tree model. Out of the features in the data, ten important features were selected using random forest feature importance, which helps to achieve the objective of the study. The study’s purpose is to enable organizations to develop suitable techniques to prevent cybercrime using random forest predictions as they relate to cloud services in the United States. The effectiveness of the models used is evaluated by utilizing validation matrices that include recall values, accuracy, and precision, in addition to F1 scores and confusion matrices. Based on evaluation scores (accuracy, precision, recall, and F1 scores) of 81.9%, 82.6%, and 82.1%, the results demonstrated the effectiveness of the random forest model. It showed the importance of machine learning algorithms in preventing cybercrime and boosting security in the cloud environment. It recommends that other machine learning models be adopted to see how to improve cybersecurity through cloud computing.

Cyberattack Ramifications, The Hidden Cost of a Security Breach

In this in-depth exploration, I delve into the complex implications and costs of cybersecurity breaches. Venturing beyond just the immediate repercussions, the research unearths both the overt and concealed long-term consequences that businesses encounter. This study integrates findings from various research, including quantitative reports, drawing upon real-world incidents faced by both small and large enterprises. This investigation emphasizes the profound intangible costs, such as trade name devaluation and potential damage to brand reputation, which can persist long after the breach. By collating insights from industry experts and a myriad of research, the study provides a comprehensive perspective on the profound, multi-dimensional impacts of cybersecurity incidents. The overarching aim is to underscore the often-underestimated scope and depth of these breaches, emphasizing the entire timeline post-incident and the urgent need for fortified preventative and reactive measures in the digital domain.

The Role of AI in Cyber Security: Safeguarding Digital Identity

This article signals the use of Artificial Intelligence (AI) in information security where its merits, downsides as well as unanticipated negative outcomes are noted. It considers AI based models that can strengthen or undermine infrastructural functions and organize the networks. In addition, the essay delves into AI’s role in Cyber security software development and the need for AI-resilient strategies that could anticipate and thwart AI-created vulnerabilities. The document also touched on the socioeconomic ramifications of the emergence of AI in Cyber security as well. Looking into AI and security literature, the report outlines benefits including made threat detection precision, extended security ops efficiency, and preventive security tasks. At the same time, it emphasizes the positive side of AI, but it also shows potential limitations such as data bias, lack of interpretability, ethical concerns, and security flaws. The work similarly focuses on the characterized of misuse and sophisticated cyberattacks. The research suggests ways to diminish AI-generating maleficence which comprise ethical AI development, robust safety measures and constant audits and updates. With regard to the AI application in Cyber security, there are both pros and cons in terms of socio-economic issues, for example, job displacement, economic growth and the change in the required workforce skills.

AssessITS: Integrating Procedural Guidelines and Practical Evaluation Metrics for Organizational IT and Cybersecurity Risk Assessment

In today’s digitally driven landscape, robust Information Technology (IT) risk assessment practices are essential for safeguarding systems, digital communication, and data. This paper introduces “AssessITS,” an actionable method designed to provide organizations with comprehensive guidelines for conducting IT and cybersecurity risk assessments. Drawing extensively from NIST 800-30 Rev 1, COBIT 5, and ISO 31000, “AssessITS” bridges the gap between high-level theoretical standards and practical implementation challenges. The paper outlines a step-by-step methodology that organizations can simply adopt to systematically identify, analyze, and mitigate IT risks. By simplifying complex principles into actionable procedures, this framework equips practitioners with the tools needed to perform risk assessments independently, without too much reliance on external vendors. The guidelines are developed to be straightforward, integrating practical evaluation metrics that allow for the precise quantification of asset values, threat levels, vulnerabilities, and impacts on confidentiality, integrity, and availability. This approach ensures that the risk assessment process is not only comprehensive but also accessible, enabling decision-makers to implement effective risk mitigation strategies customized to their unique operational contexts. “AssessITS” aims to enable organizations to enhance their IT security strength through practical, actionable guidance based on internationally recognized standards.

Optimization of the Physical Aperture of the Parabolic Reflector Antenna

In fields like astronomy and radar technology, high-gain antennas are required for long-distance communication. Due to its relatively large gain, the use of parabolic antennas has become very popular over time, because they can easily achieve gains of above 30 dB at microwave and higher frequencies. Today, most systems’ success depends on how well the antennas perform. These antennas are available in different types and sizes. Each antenna’s effective area usually has less than the actual physical area of the antenna surface. This means that the unused area of the antenna is massive, and a waste. The aim of the research is to show that the actual physical aperture of a parabolic antenna can be reduced as much as possible to equal the effective area, as given by the antenna formula, thereby saving manufacturing costs, improve the aesthetics. In other words, the focus of this work is to experimentally show that reflector antenna can be made of smaller sizes but better performance. Measurements were taken from different positions from a parabolic antenna, the signal level measured and compared with signal levels for optimal performance.

Developing a platform to evaluate and assess the security of wearable devices

Operating in a body area network around a smartphone user, wearables serve a variety of commercial, medical and personal uses. Depending on a certain smartphone application, a wearable can capture sensitive data about the user and provide critical, possibly life-or-death, functionality. When using wearables, security problems might occur on hardware/software of wearables, connected phone apps or web services devices, or Bluetooth channels used for communication. This paper develops an open source platform called SecuWear for identifying vulnerabilities in these areas and facilitating wearable security research to mitigate them. SecuWear supports the creation, evaluation, and analysis of security vulnerability tests on actual hardwares. Extending earlier results, this paper includes an empirical evaluation that demonstrates proof of concept attacks on commercial wearable devices and shows how SecuWear captures the information necessary for identifying such attacks. Also included is a process for releasing attack and mitigation information to the security community.

Architecting the Metaverse: Blockchain and the Financial and Legal Regulatory Challenges of Virtual Real Estate

There has been disagreement over the value of purchasing space in the metaverse, but many businesses including Nike, The Wendy’s Company, and McDonald’s have jumped in headfirst. While the metaverse land rush has been called an “illusion” given underdeveloped infrastructure, including inadequate software and servers, and the potential opportunities for economic and legal abuse, the “real estate of the future” shows no signs of slowing. While the current virtual space of the metaverse is worth $6.30 billion, that is expected to grow to $84.09 billion by the end of 2028. But the long-term legal and regulatory considerations of capitalizing on the investment, as well as the manner in which blockchain technology can secure users’ data and digital assets, has yet to be properly investigated. With the metaverse still in a conceptual phase, building a new 3D social environment capable of digital transactions will represent most of the initial investment in time in human capital. Digital twin technologies, already well-established in industry, will be ported to support the need to architect and furnish the new digital world. The return on and viability of investing in the “real estate of the future” raises questions fundamental to the success or failure of the enterprise. As such this paper proposes a novel framing of the issue and looks at the intersection where finance, technology, and law are converging to prevent another Dot-com bubble of the late 1990s in metaverse-based virtual real estate transactions. Furthermore, the paper will argue that these domains are technologically feasible, but the main challenges for commercial users remain in the legal and regulatory arenas. As has been the case with the emergence of online commerce, a legal assessment of the metaverse indicates that courts will look to traditional and established legal principles when addressing issues until the enactment of federal and/or state statutes and accompanying regulations. Lastly, whereas traditional regulation of real estate would involve property law, the current legal framing of ownership of metaverse assets is governed by contract law.

MBB-IoT:Construction and Evaluation of IoT DDoS Traffic Dataset from a New Perspective

Distributed Denial of Service(DDoS)attacks have always been a major concern in the security field.With the release of malware source codes such as BASHLITE and Mirai,Internet of Things(IoT)devices have become the new source of DDoS attacks against many Internet applications.Although there are many datasets in the field of IoT intrusion detection,such as Bot-IoT,ConstrainedApplication Protocol–Denial of Service(CoAPDoS),and LATAM-DDoS-IoT(some of the names of DDoS datasets),which mainly focus on DDoS attacks,the datasets describing new IoT DDoS attack scenarios are extremely rare,and only N-BaIoT and IoT-23 datasets used IoT devices as DDoS attackers in the construction process,while they did not use Internet applications as victims either.To supplement the description of the new trend of DDoS attacks in the dataset,we built an IoT environment with mainstream DDoS attack tools such as Mirai and BASHLITE being used to infect IoT devices and implement DDoS attacks against WEB servers.Then,data aggregated into a dataset namedMBB-IoTwere captured atWEBservers and IoT nodes.After the MBB-IoT dataset was split into a training set and a test set,it was applied to the training and testing of the Random Forests classification algorithm.The multi-class classification metrics were good and all above 90%.Secondly,in a cross-evaluation experiment based on Support Vector Machine(SVM),Light Gradient Boosting Machine(LightGBM),and Long Short Term Memory networks(LSTM)classification algorithms,the training set and test set were derived from different datasets(MBB-IoT or IoT-23),and the test performance is better when MBB-IoT is used as the training set.

Design of Automated Opinion Mining Model Using Optimized Fuzzy Neural Network

Sentiment analysis or Opinion Mining (OM) has gained significant interest among research communities and entrepreneurs in the recentyears. Likewise, Machine Learning (ML) approaches is one of the interestingresearch domains that are highly helpful and are increasingly applied in severalbusiness domains. In this background, the current research paper focuses onthe design of automated opinion mining model using Deer Hunting Optimization Algorithm (DHOA) with Fuzzy Neural Network (FNN) abbreviatedas DHOA-FNN model. The proposed DHOA-FNN technique involves fourdifferent stages namely, preprocessing, feature extraction, classification, andparameter tuning. In addition to the above, the proposed DHOA-FNN modelhas two stages of feature extraction namely, Glove and N-gram approach.Moreover, FNN model is utilized as a classification model whereas GTOA isused for the optimization of parameters. The novelty of current work is thatthe GTOA is designed to tune the parameters of FNN model. An extensiverange of simulations was carried out on the benchmark dataset and the resultswere examined under diverse measures. The experimental results highlightedthe promising performance of DHOA-FNN model over recent state-of-the-arttechniques with a maximum accuracy of 0.9928.

Topological Evaluation of Certain Computer Networks by Contraharmonic-Quadratic Indices

In various fields,different networks are used,most of the time not of a single kind;but rather a mix of at least two networks.These kinds of networks are called bridge networks which are utilized in interconnection networks of PC,portable networks,spine of internet,networks engaged with advanced mechanics,power generation interconnection,bio-informatics and substance intensify structures.Any number that can be entirely calculated by a graph is called graph invariants.Countless mathematical graph invariants have been portrayed and utilized for connection investigation during the latest twenty years.Nevertheless,no trustworthy evaluation has been embraced to pick,how much these invariants are associated with a network graph or subatomic graph.In this paper,it will discuss three unmistakable varieties of bridge networks with an incredible capacity of assumption in the field of computer science,chemistry,physics,drug industry,informatics and arithmetic in setting with physical and manufactured developments and networks,since Contraharmonic-quadratic invariants(CQIs)are recently presented and have different figure qualities for different varieties of bridge graphs or networks.The study settled the geography of bridge graphs/networks of three novel sorts with two kinds of CQI and Quadratic-Contraharmonic Indices(QCIs).The deduced results can be used for the modeling of the above-mentioned networks.

Application of Physical Unclonable Function for Lightweight Authentication in Internet of Things

IoT devices rely on authentication mechanisms to render secure message exchange.During data transmission,scalability,data integrity,and processing time have been considered challenging aspects for a system constituted by IoT devices.The application of physical unclonable functions(PUFs)ensures secure data transmission among the internet of things(IoT)devices in a simplified network with an efficient time-stamped agreement.This paper proposes a secure,lightweight,cost-efficient reinforcement machine learning framework(SLCR-MLF)to achieve decentralization and security,thus enabling scalability,data integrity,and optimized processing time in IoT devices.PUF has been integrated into SLCR-MLF to improve the security of the cluster head node in the IoT platform during transmission by providing the authentication service for device-to-device communication.An IoT network gathers information of interest from multiple cluster members selected by the proposed framework.In addition,the software-defined secured(SDS)technique is integrated with SLCR-MLF to improve data integrity and optimize processing time in the IoT platform.Simulation analysis shows that the proposed framework outperforms conventional methods regarding the network’s lifetime,energy,secured data retrieval rate,and performance ratio.By enabling the proposed framework,number of residual nodes is reduced to 16%,energy consumption is reduced by up to 50%,almost 30%improvement in data retrieval rate,and network lifetime is improved by up to 1000 msec.

Enhancing Bandwidth Utilization of IP Telephony Over IPv6 Networks

The demand for the telecommunication services,such as IP telephony,has increased dramatically during the COVID-19 pandemic lockdown.IP tele-phony should be enhanced to provide the expected quality.One of the issues that should be investigated in IP telephony is bandwidth utilization.IP telephony pro-duces very small speech samples attached to a large packet header.The header of the IP telephony consumes a considerable share of the bandwidth allotted to the IP telephony.This wastes the network's bandwidth and influences the IP telephony quality.This paper proposes a mechanism(called Smallerize)that reduces the bandwidth consumed by both the speech sample and the header.This is achieved by assembling numerous IP telephony packets in one header and use the header'sfields to carry the speech sample.Several metrics have been used to measure the achievement Smallerize mechanism.The number of calls has been increased by 245.1%compared to the typical mechanism.The bandwidth saving has also reached 68%with the G.28 codec.Therefore,Smallerize is a possible mechanism to enhance bandwidth utilization of the IP telephony.

The Impact of Satellite Communications on Environmental Hazard Control: Tool for the Realization of African Union Agenda 2063 Aspirations

Africa is a developing economy and as such, emphasis has been placed on the achievement of revolutionary goals that will place her on a similar rank as the developed economies. Pertaining to this objective, Heads of States and government all over Africa instigated the African Union (AU) Agenda 2063, which is a framework put in place to achieve a continental transformation over the next 40 years. The use of satellites has been proven to be a major influence on economic growth since it facilitates the exchange of information. Environmental hazards such as climate changes, pollution, and inefficient waste management can be classified as one of the drawbacks to achieving this economic growth we hope to accomplish. The purpose of this paper is to analyze and examine satellite communication as a tool for the attainment of an integrated, prosperous and peaceful Africa by means of combatting environmental hazards in the continent.

Design of an E-Administration Platform and Its Cryptography-Based Security Model

E-administration is performing administrative works via computer and its associated technologies such as the Internet. It is administrative efforts that center on the exchange of information and providing services to people and the business sector at high speed and low cost through computers and networks with the assurance of maintaining information security. It is based on the positive investment in information technology and communication in administrative practices. This paper presents the design of the e-administration platform that adopts the concept of cryptography for identity management. The architectural framework of the platform comprises subcomponents for service and forms identification, business process redesign, service architecture, amalgamation, and deployment. The cryptography model for securing the platform was designed based on the combination of authentication criteria presented in the Rijndael-Advanced Encryption Standard (AES), Lattice-based cryptography (LBC), and Secure Hash Algorithm (SHA512). It is required that a record be encrypted prior to its commitment to the database via a double encryption method. The AES algorithm-based encryption’s output will form the input to the LBC algorithm to obtain the final output.

Cybersecurity and Domestic Terrorism: Purpose and Future

The increasing utilization of digital technologies presents risks to critical systems due to exploitation by terrorists. Cybersecurity entails proactive and reactive measures designed to protect software and electronic devices from any threats. However, the rising cases of cyber threats are carried out by domestic terrorists who share particular ideologies or grievances. This paper analyzes the increasing cyber-attack instances and mechanisms to counter these threats. Additionally, it addresses the growing concern of domestic terrorism and its impact on national security. Finally, it provides an overview of gaps and possible areas of future research to promote cybersecurity.

Increasing Threats to United States of America Infrastructure Based on Cyber-Attacks

The United States of America faces an increasing number of threats to its critical infrastructure due to cyber-attacks. With the constant advancement of technology and the interconnectedness of various systems, the vulnerabilities in the nation’s infrastructure have become more pronounced. Cyber-attacks on critical infrastructure, such as power grids, transportation networks, and financial systems, pose a significant risk to national security and public safety. These attacks can disrupt essential services, cause economic losses, and potentially have severe consequences for the well-being of individuals and communities. The rise of cyber-terrorism is also a concern. Cyber-terrorists can exploit vulnerabilities in cyberspace to compromise infrastructure systems, causing chaos and panic among the population. The potential for destructive attacks on critical infrastructure is a pressing issue requiring constant attention and proactive measures.

Development of Recovery and Redundancy Model for Real Time Wireless Networks

The growth in wireless technologies applications makes the necessity of providing a reliable communication over wireless networks become obvious.Guaranteeing real time communication in wireless medium poses a significant challenge due to its poor delivery reliability.In this study,a recovery and redundancy model based on sequential time division multiple access(S-TDMA)for wireless communication is developed.The media access control(MAC)layer of the S-TDMA determines which station should transmit at a given time slot based on channel state of the station.Simulations of the system models were carried out using MATLAB SIMULINK software.SIMULINK blocks from the signal processing and communication block sets were used to model the communication system.The S-TDMA performance is evaluated with total link reliability,system throughput,average probability of correct delivery before deadline and system latency.The evaluation results displayed in graphs when compared with instant retry and drop of frame were found to be reliable in recovering loss packets.

A Review on Security and Privacy Issues Pertaining to Cyber-Physical Systems in the Industry 5.0 Era

The advent of Industry 5.0 marks a transformative era where Cyber-Physical Systems(CPSs)seamlessly integrate physical processes with advanced digital technologies.However,as industries become increasingly interconnected and reliant on smart digital technologies,the intersection of physical and cyber domains introduces novel security considerations,endangering the entire industrial ecosystem.The transition towards a more cooperative setting,including humans and machines in Industry 5.0,together with the growing intricacy and interconnection of CPSs,presents distinct and diverse security and privacy challenges.In this regard,this study provides a comprehensive review of security and privacy concerns pertaining to CPSs in the context of Industry 5.0.The review commences by providing an outline of the role of CPSs in Industry 5.0 and then proceeds to conduct a thorough review of the different security risks associated with CPSs in the context of Industry 5.0.Afterward,the study also presents the privacy implications inherent in these systems,particularly in light of the massive data collection and processing required.In addition,the paper delineates potential avenues for future research and provides countermeasures to surmount these challenges.Overall,the study underscores the imperative of adopting comprehensive security and privacy strategies within the context of Industry 5.0.