Enhancing Cybersecurity through AI and ML: Strategies, Challenges, and Future Directions

The landscape of cybersecurity is rapidly evolving due to the advancement and integration of Artificial Intelligence (AI) and Machine Learning (ML). This paper explores the crucial role of AI and ML in enhancing cybersecurity defenses against increasingly sophisticated cyber threats, while also highlighting the new vulnerabilities introduced by these technologies. Through a comprehensive analysis that includes historical trends, technological evaluations, and predictive modeling, the dual-edged nature of AI and ML in cybersecurity is examined. Significant challenges such as data privacy, continuous training of AI models, manipulation risks, and ethical concerns are addressed. The paper emphasizes a balanced approach that leverages technological innovation alongside rigorous ethical standards and robust cybersecurity practices. This approach facilitates collaboration among various stakeholders to develop guidelines that ensure responsible and effective use of AI in cybersecurity, aiming to enhance system integrity and privacy without compromising security.

International Telecommunication Union Standardization for Trust Provisioning in Information, Communication and Technology Infrastructure toward Achieving United Nation’s Sustainable Development Goals

The advancement of the fourth industrial revolution has shaped the integration and interaction of different information, communication and technologies (ICTs) in the merging cyber, physical, and social infrastructures. The impact of ICT has accelerated the progress of the United Nation’s Sustainable Development Goals (UN SDGs) and influenced the evolution of smart, sustainable, stable society development. Making the trustworthy information and communication technologies infrastructure widely available will promote the community innovation needed to stimulate domestic economics, provide decent work, and reduce inequalities. This article attempts to outline a big picture about the International Telecommunication Union (ITU)’s trust provisioning framework, including its motivation, current status, and application for achieving the UN SDGs by 2030. This article first describes the purpose of the UN SDGs and the evolution of the industrial revolution, then demonstrates the challenges of global risks affecting the fourth industrial revolution and the need for trustworthy ICT infrastructures. Subsequently, the article evaluates the ITU trust provisioning framework and assesses its applications in the future knowledge society, trust provisioning ecosystem, and cyber, physical, and social infrastructure toward achieving UN SDGs. Use cases are also presented in this article to show the effectiveness of the ITU trust provisioning framework on achieving UN SDGs.

Control of GaN inverted pyramids growth on c-plane patterned sapphire substrates

Growth of gallium nitride(GaN)inverted pyramids on c-plane sapphire substrates is benefit for fabricating novel devices as it forms the semipolar facets.In this work,GaN inverted pyramids are directly grown on c-plane patterned sapphire substrates(PSS)by metal organic vapor phase epitaxy(MOVPE).The influences of growth conditions on the surface morphol-ogy are experimentally studied and explained by Wulff constructions.The competition of growth rate among{0001},{1011},and{1122}facets results in the various surface morphologies of GaN.A higher growth temperature of 985 ℃ and a lowerⅤ/Ⅲratio of 25 can expand the area of{}facets in GaN inverted pyramids.On the other hand,GaN inverted pyramids with almost pure{}facets are obtained by using a lower growth temperature of 930℃,a higherⅤ/Ⅲratio of 100,and PSS with pattern arrangement perpendicular to the substrate primary flat.

Cost-Efficient Medium Frequency Propagation Research with Software Defined Radio

Medium Frequency radio holds significance in modern society as it supports broadcasting and individual communications in the public, government, and military sectors. Enhancing the availability and quality of these communications is only possible by enhancing the understanding of medium frequency propagation. While traditional methods of radio wave propagation research can have a high material demand and cost, software defined radio presents itself as a versatile and low-cost platform for medium frequency signal reception and data acquisition. This paper details a research effort that utilizes software defined radio to help characterize medium frequency signal strength in relation to ionospheric and solar weather propagation determinants. Signal strength data from seven medium frequency stations of unique transmission locations and varying transmission powers were retrieved in 24-hour segments via a receiving loop antenna, Airspy HF+ Discovery software defined radio, and SDR Sharp software interface network. Retrieved data sets were visualized and analyzed in MATLAB for the identification of signal strength trends, which were subsequently compared to historical ionospheric and space weather indices in pursuit of a quantifiable correlation between such indices and medium frequency signal strengths. The results of the investigation prove that software defined radio, when used in conjunction with a receiving antenna and data analysis program, provides a versatile mechanism for cost-efficient propagation research.

Deep Learning for Wireless Physical Layer: Opportunities and Challenges

Machine learning(ML) has been widely applied to the upper layers of wireless communication systems for various purposes, such as deployment of cognitive radio and communication network. However, its application to the physical layer is hampered by sophisticated channel environments and limited learning ability of conventional ML algorithms. Deep learning(DL) has been recently applied for many fields, such as computer vision and natural language processing, given its expressive capacity and convenient optimization capability. The potential application of DL to the physical layer has also been increasingly recognized because of the new features for future communications, such as complex scenarios with unknown channel models, high speed and accurate processing requirements; these features challenge conventional communication theories. This paper presents a comprehensive overview of the emerging studies on DL-based physical layer processing, including leveraging DL to redesign a module of the conventional communication system(for modulation recognition, channel decoding, and detection) and replace the communication system with a radically new architecture based on an autoencoder. These DL-based methods show promising performance improvements but have certain limitations, such as lack of solid analytical tools and use of architectures that are specifically designed for communication and implementation research, thereby motivating future research in this field.

Energy-Optimal and Delay-Bounded Computation Offloading in Mobile Edge Computing with Heterogeneous Clouds

By Mobile Edge Computing(MEC), computation-intensive tasks are offloaded from mobile devices to cloud servers, and thus the energy consumption of mobile devices can be notably reduced. In this paper, we study task offloading in multi-user MEC systems with heterogeneous clouds, including edge clouds and remote clouds. Tasks are forwarded from mobile devices to edge clouds via wireless channels, and they can be further forwarded to remote clouds via the Internet. Our objective is to minimize the total energy consumption of multiple mobile devices, subject to bounded-delay requirements of tasks. Based on dynamic programming, we propose an algorithm that minimizes the energy consumption, by jointly allocating bandwidth and computational resources to mobile devices. The algorithm is of pseudo-polynomial complexity. To further reduce the complexity, we propose an approximation algorithm with energy discretization, and its total energy consumption is proved to be within a bounded gap from the optimum. Simulation results show that, nearly 82.7% energy of mobile devices can be saved by task offloading compared with mobile device execution.

Metal–organic–vapor phase epitaxy of InGaN quantum dots and their applications in light-emitting diodes

InGaN quantum dot is a promising optoelectronic material, which combines the advantages of low-dimensional and wide-gap semiconductors. The growth of InGaN quantum dots is still not mature, especially the growth by metal--organic- vapor phase epitaxy （MOVPE）, which is challenge due to the lack of, itin-situ monitoring tool. In this paper, we reviewed the development of InGaN quantum dot growth by MOVPE, including our work on growth of near-UV, green, and red InGaN quantum dots. In addition, we also introduced the applications of InGaN quantum dots on visible light emitting diodes.

Consistency and Asymptotic Property of a Weighted Least Squares Method for Networked Control Systems

In this paper, we study the problems related to parameter estimation of a single-input and single-output networked control system, which contains possible network-induced delays and packet dropout in both of sensor-to-controller path and controller-to-actuator path. A weighted least squares(WLS) method is designed to estimate the parameters of plant, which could overcome the data uncertainty problem caused by delays and dropout. This WLS method is proved to be consistent and has a good asymptotic property. Simulation examples are given to validate the results.

All-Optical AND Logic Gate without Additional Input Beam by Utilizing Cross Polarization Modulation Effect

A novel design of all-optical AND gate is proposed by using cross polarization modulation effect in a semiconductor optical amplifier. In this scheme, an additional continuous-wave beam is not required as that in traditional scheme. AND output is obtained on either of two input signal wavelengths. The AND scheme is numerically simulated and experimentally demonstrated at a bit rate of 10 Gb/s successfully.

Inspection Models Considering the Overlapping of Inspection Span and Failure Downtime

In the literature, many works on determining inspection interval by the delay time concept generally assumed that the time of inspection span and the time of failure renewal are negligible. However, in realistic cases, the above time should not be neglected for both the time itself and its effect. In order to model the effect of the possible overlapping of inspection span with failure downtime on determining the optimal inspection interval, we propose a block-based inspection model for a single component-based on delay time concept. We further compare this model with the age-based model to show the practical sense. The developed models are also demonstrated by numerical examples.

Study of tetracycline removal and saturated resin regenerated by dielectric barrier discharge plasma

The wastewater produced by the large-scale usage of antibiotics worldwide was more harmful to the ecological environment and human health.In the research,the coupling technology of‘adsorption-plasma regeneration'was taken to treat tetracycline in aqueous solution.The pollutants were adsorbed by the resins firstly and then regenerated ectopically by dielectric barrier discharge plasma.The discharge parameters,such as discharge voltage and frequency were researched to achieve the optimal regeneration efficiency and energy efficiency.Meanwhile,the analyses of the surface functional groups and microstructure were also investigated.After the five‘adsorption-regeneration'processes,the results showed that the optimal discharge parameters of voltage and frequency were 20 k V and 1 k Hz,respectively.The regeneration efficiency and energy efficiency were above 80%and 115 g k W^(-1)·h^(-1),respectively.The tetracycline adsorption by virgin resin and regenerated resin nearly followed pseudo-second order kinetics,and there was no fatal damage to the surface characteristics and physicochemical properties of the resins through the multiple plasma regeneration processes.Finally,according to the intra-particle diffusion model and the degradation products detected by GC-MS,the adsorption and degradation mechanisms of tetracycline were deduced.

Phase Noise of Optically Generated Microwave Using Sideband Injection Locking

Optically generated 20-GHz microwave carriers with phase noise lower than -75 dBc/Hz at 10 kHz offset and lower than -90 dBc/Hz at 100 kHz offset are obtained using single- and double-sideband injection locking. Within the locking range, the effect of sideband injection locking can be regarded as narrow-band amplification of the modulation sidebands. Increasing the current of slave laser will increase the power of beat signal and reduce the phase noise to a certain extent. Double-sideband injection locking can increase the power of the generated microwave carrier while keeping the phase noise at a low level. It is also revealed that partially destruction of coherence between the two beating lights in the course of sideband injection locking would impair the phase noise performance.

Ultra broadband flat dispersion tailoring on reversed-rib chalcogenide glass waveguide

In this paper,we introduce a horizontal slot in the reversed-rib chalcogenide glass waveguide to tailor its dispersion characteristics.The waveguide exhibits a flat and low dispersion over a wavelength range of 1080 nm,in which the dispersion fluctuates between-10.6 ps·nm-1·km-1 and ＋11.14 ps·nm-1·km-1.The dispersion tailoring effect is due to the mode field transfer from the reversed-rib waveguide to the slot with the increase of wavelength,which results in the extension of the low dispersion band.Moreover,the nonlinear coefficient and the phase-matching condition of the fourwave mixing process in this waveguide are studied,showing that the waveguide has great potential in nonlinear optical applications over a wide wavelength range.

True Random Number Generator Realized by Extracting Entropy from a Negative-Inductance Superconducting Quantum Interference Device

A new type of superconductive true random number generator (TRNG) based on a negative-inductance superconducting quantum interference device (nSQUID) is proposed. The entropy harnessed to generate random numbers comes from the phenomenon of symmetry breaking in the nSQUID. The experimental circuit is fabricated by the Nb-based lift-off process. Low-temperature tests of the circuit verify the basic function of the proposed TRNG. The frequency characteristics of the TRNG have been analyzed by simulation. The generation rate of random numbers is expected to achieve hundreds of megahertz to tens of gigahertz.

Resilience at the Core: Critical Infrastructure Protection Challenges, Priorities and Cybersecurity Assessment Strategies

The importance of a nation’s infrastructure is a vital core for economic growth, development, and innovation. Health, wealth, access to education, public safety, and helping prepare for global crises like pandemics are all dependent on functioning and reliable infrastructures. In decades, the substantial threats affecting infrastructures globally whether in the form of extreme weather, Covid-19 pandemic, or the threats of state and non-state actors’ hackers, demanded urgency in building resilience infrastructures both during crises and in more stable conditions. At the same time, the adoption of emerging and innovative technologies boosts the development of the infrastructures using information, communication, and technology (ICT) platform. This shift accelerated its evolution toward digitization where interdependent and interconnected cyberspace demands collaborative and holistic strategies in protecting critical and high risks infrastructure assets from a growing number of disruptive cyberattacks. These ever-evolving cyber threats are creating increasingly dangerous and targeted cyberattacks to damage or disrupt the critical infrastructures delivering vital services to government, energy, healthcare, transportation, telecommunication, and other critical sectors. The infrastructure’s high risks assets present serious challenges and are crucial to safety, efficiency, and reliability. Any nation must recognize and determine how to cope with any type of threats to their critical infrastructure as well as the strategies to remain resilient. This article first describes the challenges and the need for critical infrastructure protection including the related global risks challenges. It then reviews the United Nations, the European Union, and the United States’ strategies, priorities, and urgencies of critical infrastructure protection. Subsequently, it surveys the critical infrastructure protection resilience strategies including ISO, IEC, ISA, NIST, CAF and CMM frameworks.

Improvement of A1N Film Quality by Controlling the Coalescence of Nucleation Islands in Plasma-Assisted Molecular Beam Epitaxy

The influence of nucleation coalescence on the crystalline quality of A1N films grown on sapphire by plasma- assisted molecular beam epitaxy is investigated. The coalescence speed is controlled by the V/Ⅲ ratio chosen for the growth after nucleation. A slightly Al-rich condition, corresponding to slow coalescence, can significantly reduce the density of edge threading dislocation （TD）, which is found to be dominant in AIN epilayers. The cross-sectional TEM image of the AIN epilayer grown under this condition clearly reveals an automatically formed boundary where an abrupt decrease of edge TD density occurs.

Enabling technology and core theory of synthetic biology

Synthetic biology provides a new paradigm for life science research(“build to learn”)and opens the future journey of biotechnology(“build to use”).Here,we discuss advances of various principles and technologies in the mainstream of the enabling technology of synthetic biology,including synthesis and assembly of a genome,DNA storage,gene editing,molecular evolution and de novo design of function proteins,cell and gene circuit engineering,cell-free synthetic biology,artificial intelligence(AI)-aided synthetic biology,as well as biofoundries.We also introduce the concept of quantitative synthetic biology,which is guiding synthetic biology towards increased accuracy and predictability or the real rational design.We conclude that synthetic biology will establish its disciplinary system with the iterative development of enabling technologies and the maturity of the core theory.

DIProT:A deep learning based interactive toolkit for efficient and effective Protein design

The protein inverse folding problem,designing amino acid sequences that fold into desired protein structures,is a critical challenge in biological sciences.Despite numerous data-driven and knowledge-driven methods,there remains a need for a user-friendly toolkit that effectively integrates these approaches for in-silico protein design.In this paper,we present DIProT,an interactive protein design toolkit.DIProT leverages a non-autoregressive deep generative model to solve the inverse folding problem,combined with a protein structure prediction model.This integration allows users to incorporate prior knowledge into the design process,evaluate designs in silico,and form a virtual design loop with human feedback.Our inverse folding model demonstrates competitive performance in terms of effectiveness and efficiency on TS50 and CATH4.2 datasets,with promising sequence recovery and inference time.Case studies further illustrate how DIProT can facilitate user-guided protein design.

Suppression of intervalley scattering and enhanced phonon anharmonic interactions in 2D Bi_(2)TeSe_(2):Crystal-field symmetry and band convergence

The electron-phonon(el-ph)and phonon-phonon interactions play a key role in determining electronic and thermal transport properties,respectively,in promising two-dimensional(2D)semiconductor de-vices.In this study,we investigated el-ph interactions using Wannier-Fourier interpolation method and renormalized phonon scattering considering finite-temperature effects in Bi_(2)TeSe_(2)monolayer.The re-sults show that the optical phonon modes dominate the carrier scattering,where level repulsion induced by crystal field splitting and spin-orbit coupling(SOC)effect effectively suppresses intervalley scattering,leading to high hole mobility.Moreover,the strong anharmonicity in Bi_(2)TeSe_(2)monolayer results in the temperature-dependent softening of its optical phonons,along with a corresponding variation in interatomic force constants(IFCs).As a result,the lattice thermal conductivity is remarkably low and exhibits weak temperature dependence.Finally,the predicted dimensionless thermoelectric figure of merit exceeds unity in the range of 200-800 K,indicating the potential of Bi_(2)TeSe_(2)monolayer for thermoelectric applications.This work provides new insights into the elimination of intervalley scat-tering by crystal field splitting and SOC effects,and paves the way for the evaluation of thermoelectric properties of materials with complex scattering mechanisms and strong anharmonicity.