Insider Threat is a significant and potentially dangerous security issue in corporate settings. It is difficult to mitigate because, unlike external threats, insiders have knowledge of an organization's access policies, access hierarchy, access protocols, and access scheduling. Several approaches to reducing insider threat have been proposed in the literature. However, the integration of access control and moving target defense (MTD) for deceiving insiders has not been adequately discussed. In this paper, we combine MTD, deception, and attribute-based access control to make it more difficult and expensive for an insider to gain unauthorized access. We introduce the concept of correlated attributes into ABAC and extend the ABAC model with MTD by generating mutated policy using the correlated attributes for insider threat mitigation. The evaluation results show that the proposed framework can effectively identify correlated attributes and produce adequate mutated policy without affecting the usability of the access control systems.
This article presents reflections from the perspective of a university librarian involved in the establishment and management of institutional repositories in Japan. It examines the historical evolution of scholarly communication, from the oral exchanges of ancient Greek philosophers, through the advent of printing and the rise of academic journals, to the contemporary digital era. The origins of the open access movement are emphasized as rooted in authors' desire to disseminate knowledge globally, rather than merely opening access for readers. The article critically discusses current practices in Japan, including institutional repositories, open access journals, and "read-and-publish" agreements, highlighting that many digital innovations still imitate the conventions of print-based scholarly communication. Furthermore, it explores the challenges and opportunities posed by electronic information dissemination, including the limitations of the Version of Record and the potential of diamond open access models. The article argues that genuine progress in scholarly communication requires rethinking publication practices, embracing the modifiability of digital content, and developing n
The Solar System Notification Alert Processing System, SNAPS, is a downstream broker that ingests moving object data from ZTF and LSST and serves these data and derived properties to the public. This document describes how users can access our SNAPS data and products. This is intended to be a living document that will be updated on the arXiv when significant improvements are made to our data access schemes, and will therefore always contain the most up to date information about interacting with our databases and infrastructure. This is version 1.0.
Access to finance is vital for improving food security, particularly in developing nations where agricultural production is crucial. Despite several financial interventions targeted at increasing agricultural production, smallholder farmers continue to lack access to reasonable, timely, and sufficient financing, limiting their ability to invest in improved technology and inputs, lowering productivity and food supply. This study examines the relationship between access to finance and food security among smallholder farmers in Ogun State, employing institutional theory as a theoretical framework. The study takes a quantitative method, with a survey for the research design and a population of 37,200 agricultural smallholder farmers. A sample size of 380 was chosen using probability sampling and simple random techniques. The data were analysed via Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings demonstrate a favourable relationship between access to finance and food security, with an R2-value of 0.615 indicating a robust link. These findings underline the need of improving financial institutions and implementing enabling policies to enable farmers have acces
This paper reviews research literature on Diamond Open Access (DOA) journals - sometimes also called Platinum Open Access - that was produced after this journal segment started to become a priority in European research policy around 2020. It contextualizes the current science policy debate, critically examines different understandings of DOA, and reviews studies on the role of such journals in scholarly communication. Most existing research consists of quantitative studies focusing on aspects such as the number of DOA journals, their publication output, the diversity of the landscape in terms of subject areas, languages, publishing entities, indexing in major databases, awareness and perception among scholars, cost analyses, as well as insights into the internal operations of DOA journals. The review shows that research on DOA journals is partly influenced by the science policy discourse in at least two ways: first, through the normativity inherent in that discourse, and second, through the temporality of policy-driven research of practical relevance, which leaves important aspects of the phenomenon understudied. Moreover, research on the DOA journal landscape has implications beyo
The development of the sixth generation of communication networks (6G) has been gaining momentum over the past years, with a target of being introduced by 2030. Several initiatives worldwide are developing innovative solutions and setting the direction for the key features of these networks. Some common emerging themes are the tight integration of AI, the convergence of multiple access technologies and sustainable operation, aiming to meet stringent performance and societal requirements. To that end, we are introducing REASON - Realising Enabling Architectures and Solutions for Open Networks. The REASON project aims to address technical challenges in future network deployments, such as E2E service orchestration, sustainability, security and trust management, and policy management, utilising AI-native principles, considering multiple access technologies and cloud-native solutions. This paper presents REASON's architecture and the identified requirements for future networks. The architecture is meticulously designed for modularity, interoperability, scalability, simplified troubleshooting, flexibility, and enhanced security, taking into consideration current and future standardisatio
This survey uncovers the tension between AI techniques designed for energy saving in mobile networks and the energy demands those same techniques create. We compare modeling approaches that estimate power usage cost of current commercial terrestrial next-generation radio access network deployments. We then categorize emerging methods for reducing power usage by domain: time, frequency, power, and spatial. Next, we conduct a timely review of studies that attempt to estimate the power usage of the AI techniques themselves. We identify several gaps in the literature. Notably, real-world data for the power consumption is difficult to source due to commercial sensitivity. Comparing methods to reduce energy consumption is beyond challenging because of the diversity of system models and metrics. Crucially, the energy cost of AI techniques is often overlooked, though some studies provide estimates of algorithmic complexity or run-time. We find that extracting even rough estimates of the operational energy cost of AI models and data processing pipelines is complex. Overall, we find the current literature hinders a meaningful comparison between the energy savings from AI techniques and their
The MIS data is critical to an organization and should be protected from misuse by wrong persons. Although The MIS data is typically meant for the senior managers each MIS report may not be required by every manager. The access to MIS data is determined by the role of an individual in the organization and controlled by the MIS administrator accordingly. The access is generally determined by the following parameters, (a) the type of user (such as staff or manager etc.), (b) the type of data (whether general data or managerial data), (c) level of access (read/ write/ admin access) and (d) special access allocated by MIS admin. By combining all the above four parameters, each individual user can be allocated exact specific rights required to access the MIS.
Spatial division multiple access (SDMA) is essential to improve the spectrum efficiency for multi-user multiple-input multiple-output (MIMO) communications. The classical SDMA for massive MIMO with hybrid precoding heavily relies on the angular orthogonality in the far field to distinguish multiple users at different angles, which fails to fully exploit spatial resources in the distance domain. With dramatically increasing number of antennas, extremely large-scale antenna array (ELAA) introduces additional resolution in the distance domain in the near field. In this paper, we propose the concept of location division multiple access (LDMA) to provide a new possibility to enhance spectrum efficiency. The key idea is to exploit extra spatial resources in the distance domain to serve different users at different locations (determined by angles and distances) in the near field. Specifically, the asymptotic orthogonality of beam focusing vectors in the distance domain is proved, which reveals that near-field beam focusing is able to focus signals on specific locations to mitigate inter-user interferences. Simulation results verify the superiority of the proposed LDMA over classical SDMA
5G New Radio (NR) is expected to support new ultra-reliable low-latency communication (URLLC) service targeting at supporting the small packets transmissions with very stringent latency and reliability requirements. Current Long Term Evolution (LTE) system has been designed based on grantbased (GB) (i.e., dynamic grant) random access, which can hardly support the URLLC requirements. Grant-free (GF) (i.e., configured grant) access is proposed as a feasible and promising technology to meet such requirements, especially for uplink transmissions, which effectively saves the time of requesting/waiting for a grant. While some basic GF access features have been proposed and standardized in NR Release-15, there is still much space to improve. Being proposed as 3GPP study items, three GF access schemes with Hybrid Automatic Repeat reQuest (HARQ) retransmissions including Reactive, K-repetition, and Proactive, are analyzed in this paper. Specifically, we present a spatiotemporal analytical framework for the contention-based GF access analysis. Based on this framework, we define the latent access failure probability to characterize URLLC reliability and latency performances. We propose a trac
The integration of intelligent reflecting surface (IRS) to multiple access networks is a cost-effective solution for boosting spectrum/energy efficiency and enlarging network coverage/connections. However, due to the new capability of IRS in reconfiguring the wireless propagation channels, it is fundamentally unknown which multiple access scheme is superior in the IRS-assisted wireless network. In this letter, we pursue a theoretical performance comparison between non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) in the IRS-assisted downlink communication, for which the transmit power minimization problems are formulated under the discrete unit-modulus reflection constraint on each IRS element. We analyze the minimum transmit powers required by different multiple access schemes and compare them numerically, which turn out to not fully comply with the stereotyped superiority of NOMA over OMA in conventional systems without IRS. Moreover, to avoid the exponential complexity of the brute-force search for the optimal discrete IRS phase shifts, we propose a low-complexity solution to achieve near-optimal performance.
"Open access" has become a central theme of journal reform in academic publishing. In this article, I examine the relationship between open access publishing and an important infrastructural element of a modern research enterprise, scientific literature text mining, or the use of data analytic techniques to conduct meta-analyses and investigations into the scientific corpus. I give a brief history of the open access movement, discuss novel journalistic practices, and an overview of data-driven investigation of the scientific corpus. I argue that particularly in an era where the veracity of many research studies has been called into question, scientific literature text mining should be one of the key motivations for open access publishing, not only in the basic sciences, but in the engineering and applied sciences as well. The enormous benefits of unrestricted access to the research literature should prompt scholars from all disciplines to lend their vocal support to enabling legal, wholesale access to the scientific literature as part of a data science pipeline.
In this paper, we apply the Non-Orthogonal Multiple Access (NOMA) technique to improve the massive channel access of a wireless IoT network where solar-powered Unmanned Aerial Vehicles (UAVs) relay data from IoT devices to remote servers. Specifically, IoT devices contend for accessing the shared wireless channel using an adaptive $p$-persistent slotted Aloha protocol; and the solar-powered UAVs adopt Successive Interference Cancellation (SIC) to decode multiple received data from IoT devices to improve access efficiency. To enable an energy-sustainable capacity-optimal network, we study the joint problem of dynamic multi-UAV altitude control and multi-cell wireless channel access management of IoT devices as a stochastic control problem with multiple energy constraints. To learn an optimal control policy, we first formulate this problem as a Constrained Markov Decision Process (CMDP), and propose an online model-free Constrained Deep Reinforcement Learning (CDRL) algorithm based on Lagrangian primal-dual policy optimization to solve the CMDP. Extensive simulations demonstrate that our proposed algorithm learns a cooperative policy among UAVs in which the altitude of UAVs and chann
The COVID-19 crisis has demonstrated the potential of cutting-edge genomics research. However, privacy of these sensitive pieces of information is an area of significant concern for genomics researchers. The current security models makes it difficult to create flexible and automated data sharing frameworks. These models also increases the complexity of adding or revoking access without contacting the data publisher. In this work, we investigate an automated attribute-based access control (AABAC) model for genomics data over Named Data Networking (NDN). AABAC secures the data itself rather than the storage location or transmission channel, provides automated data invalidation, and automates key retrieval and data validation while maintaining the ability to control access. We show that AABC when combined with NDN provide a secure and flexible combination for work with genomics research.
Efficient dynamic spectrum access mechanism is crucial for improving the spectrum utilization. In this paper, we consider the dynamic spectrum access mechanism design with both complete and incomplete network information. When the network information is available, we propose an evolutionary spectrum access mechanism. We use the replicator dynamics to study the dynamics of channel selections, and show that the mechanism achieves an equilibrium that is an evolutionarily stable strategy and is also max-min fair. With incomplete network information, we propose a distributed reinforcement learning mechanism for dynamic spectrum access. Each secondary user applies the maximum likelihood estimation method to estimate its expected payoff based on the local observations, and learns to adjust its mixed strategy for channel selections adaptively over time. We study the convergence of the learning mechanism based on the theory of stochastic approximation, and show that it globally converges to an approximate Nash equilibrium. Numerical results show that the proposed evolutionary spectrum access and distributed reinforcement learning mechanisms achieve up to 82% and 70% performance improvement
This paper proposes Concurrent-Access Obfuscated Store (CAOS), a construction for remote data storage that provides access-pattern obfuscation in a honest-but-curious adversarial model, while allowing for low bandwidth overhead and client storage. Compared to the state of the art, the main advantage of CAOS is that it supports concurrent access without a proxy, for multiple read-only clients and a single read-write client. Concurrent access is achieved by letting clients maintain independent maps that describe how the data is stored. These maps might diverge from client to client, but it is guaranteed that no client will ever lose track of current data. We achieve efficiency and concurrency at the expense of perfect obfuscation: in CAOS the extent to which access patterns are hidden is determined by the resources allocated to its built-in obfuscation mechanism. To assess this trade-off we provide both a security and a performance analysis of our protocol instance. We additionally provide a proof-of-concept implementation.
Augmented and virtual reality (AR/VR) hold significant potential to transform how we communicate, collaborate, and interact with others. However, there has been a lack of work to date investigating accessibility barriers in relation to immersive technologies for people with disabilities. To address current gaps in knowledge, we led two multidisciplinary Sandpits with key stakeholders (including academic researchers, AR/VR industry specialists, people with lived experience of disability, assistive technologists, and representatives from national charities and special needs colleges) to collaboratively explore and identify existing challenges with AR and VR experiences. We present key themes that emerged from Sandpit activities and map out the interaction barriers identified across a spectrum of impairments (including physical, cognitive, visual, and auditory disabilities). We conclude with recommendations for future work addressing the challenges highlighted to support the development of more inclusive AR and VR experiences.
It is a challenging task to design a random access protocol that achieves the optimal throughput in multi-cell random access with decentralized transmission due to the difficulty of coordination. In this paper, we present a decentralized interference-aware opportunistic random access (IA-ORA) protocol that enables us to obtain the optimal throughput scaling in an ultra-dense multi-cell random access network with one access point (AP) and a number of users. In sharp contrast to opportunistic scheduling for cellular multiple access where users are selected by base stations, under the IA-ORA protocol, each user opportunistically transmits with a predefined physical layer (PHY) data rate in a decentralized manner if not only the desired signal power to the serving AP is sufficiently large but also the generating interference leakage power to the other APs is sufficiently small (i.e., two threshold conditions are fulfilled). As a main result, it is shown that the optimal aggregate throughput scaling (i.e., the MAC throughput of $\frac{1}{e}$ in a cell and the power gain) is achieved in a high signal-to-noise ratio regime if the number of per-cell users exceeds some level. Additionally,
Future wireless networks need to offer orders of magnitude more capacity to address the predicted growth in mobile traffic demand. Operators to enhance the capacity of cellular networks are increasingly using WiFi to offload traffic from their core networks. This paper deals with the efficient and flexible management of a heterogeneous networking environment offering wireless access to multimode terminals. This wireless access is evaluated under disruptive usage scenarios, such as flash crowds, which can mean unwanted severe congestion on a specific operator network whilst the remaining available capacity from other access technologies is not being used. To address these issues, we propose a scalable network assisted distributed solution that is administered by centralized policies, and an embedded reputation system, by which initially selfish operators are encouraged to cooperate under the threat of churn. Our solution after detecting a congested technology, including within its wired backhaul, automatically offloads and balances the flows amongst the access resources from all the existing technologies, following some quality metrics. Our results show that the smart integration of
We present a flexible public transit network design model which optimizes a social access objective while guaranteeing that the system's costs and transit times remain within a preset margin of their current levels. The purpose of the model is to find a set of minor, immediate modifications to an existing bus network that can give more communities access to the chosen services while having a minimal impact on the current network's operator costs and user costs. Design decisions consist of reallocation of existing resources in order to adjust line frequencies and capacities. We present a hybrid tabu search/simulated annealing algorithm for the solution of this optimization-based model. As a case study we apply the model to the problem of improving equity of access to primary health care facilities in the Chicago metropolitan area. The results of the model suggest that it is possible to achieve better primary care access equity through reassignment of existing buses and implementation of express runs, while leaving overall service levels relatively unaffected.