A comprehensive survey of AI-enabled phishing attacks detection techniques

In recent times, a phishing attack has become one of the most prominent attacks faced by internet users, governments, and service-providing organizations. In a phishing attack, the attacker(s) collects the client’s sensitive data (i.e., user account login details, credit/debit card numbers, etc.) by using spoofed emails or fake websites. Phishing websites are common entry points of online social engineering attacks, including numerous frauds on the websites. In such types of attacks, the attacker(s) create website pages by copying the behavior of legitimate websites and sends URL(s) to the targeted victims through spam messages, texts, or social networking. To provide a thorough understanding of phishing attack(s), this paper provides a literature review of Artificial Intelligence (AI) techniques: Machine Learning, Deep Learning, Hybrid Learning, and Scenario-based techniques for phishing attack detection. This paper also presents the comparison of different studies detecting the phishing attack for each AI technique and examines the qualities and shortcomings of these methodologies. Furthermore, this paper provides a comprehensive set of current challenges of phishing attacks and future research direction in this domain.

     

Phase Engineering of Nickel Sulfides to Boost Sodium- and Potassium-Ion Storage Performance

Sulfides are promising anode candidates because of their relatively large theoretical discharge/charge specific capacity and pretty small volume changes, but suffers from sluggish kinetics and structural instability upon cycling. Phase engineering can be designed to overcome the weakness of the electrochemical performance of sulfide anodes. By choosing nickel sulfides (α-NiS, β-NiS, and NiS₂) supported by reduced graphene oxide (rGO) as model systems, it is demonstrated that the nickel sulfides with different crystal structures show different performances in both sodium-ion and potassium-ion batteries. In particular, the α-NiS/rGO display superior stable capacity (≈426 mAh g⁻¹ for 500 cycles at 500 mA g⁻¹) and exceptional rate capability (315 mAh g⁻¹ at 2000 mA g⁻¹). The combined density functional theory calculations and experimental studies reveal that the hexagonal structure is more conducive to ion absorption and conduction, a higher pseudocapacitive contribution, and higher mechanical ability to relieve the stress caused by the volume changes. Correspondingly, the phase engineered nickel sulfide coupled with the conducting rGO network synergistically boosts the electrochemical performance of batteries. This work sheds light on the use of phase engineering as an essential strategy for exploring materials with satisfactory electrochemical performance for sodium-ion and potassium-ion batteries.     

Biosynthesis of essential oils in aromatic plants: A review

In aromatic plants species, biosynthesis of essential oils occurs through two complex natural biochemical pathways involving different enzymatic reactions. Isopentenyl diphosphate (IPP) and its isomer dimethylallyl diphosphate (DMAPP) are the universal precursors of essential oil biosynthesis and are produced by the cytosolic enzymatic MVA (mevalonic acid) pathway or by plastidic and enzymatic 1-deoxy-d-xylolose-5-phosphate (DXP) pathway, also called the 2-C-methylerythritol-4-phosphate (MEP) pathway. In the particular plant cell part, prenyl diphosphate synthases condense isopentenyl diphosphate (IPP) and dimethylallyl diphosphate (DMAPP) further to form prenyl diphosphates, which are used as substrates for geranyl diphosphate (GPP; C₁₀) or for fernesyl diphosphate (FPP; C₁₅). Essential oils are final terpenoid products and are formed by a huge group of enzymes known as terpene synthases (TPS). Essential oils are important secondary metabolites of plants and have been used not only in different industries but also in ethnobotanical medicines for centuries. Hence, considerable research has been undertaken to understand the essential oil biosynthetic pathways. This review will be a valuable source of information in the field of natural products, as we give detailed insights about biosynthesis of essential oils in plants and thus indicate also new unexplored horizons for further research.     

Design and Realization of a Novel Header Compression Scheme for Ad Hoc Networks

IP header compression schemes offer a valuable measure for bandwidth preservation. Such schemes have been practically implemented in infrastructure‐based IP networks for point‐to‐point links. However, minimal research and practical implementation efforts have been conducted in the direction of an IP header compression strategy that can meet the peculiar requirements of multi‐hop ad hoc wireless networks. In this paper, we present a practically implemented multi‐hop IP header compression scheme using the Robust Header Compression (ROHC) protocol suite. The scheme runs on a novel identifier (ID) based networking architecture, known as an ID‐based ad hoc network (IDHOCNET). IDHOCNET additionally solves a number of bottlenecks of pure IP‐based ad hoc networks that have emerged owing to IP address auto‐configuration service, distributed naming and name resolution, and the role of an IP address as an identifier at the application layer. The proposed scheme was tested on a multi‐hop test bed. The results show that the implemented scheme has better gain and requires only O (1) ROHC contexts.     

Solar radiation over Saudi Arabia and comparisons with empirical models

We present a comparison between models developed by the present authors and 16 other models for different geographical and varied meteorological conditions. The comparisons are made using the mean bias error (MBE), root mean square error (RMSE), mean percentage error (MPE), and mean absolute bias error (MABE). These errors are calculated using monthly-mean, measured daily and estimated values of total solar radiation for 41 locations in Saudi Arabia. We find that our latitude, longitude, altitude, and sunshine-duration-dependent model given in Eq. (1)produced the best estimates for global solar radiation. The second- and third-best estimates were obtained from our linear model and other models given in Eq. (2)and Eq. (11), respectively.     

Empirical model development and comparison with existing correlations

This study utilized monthly mean daily values of global solar-radiation and sunshine duration at 41 locations in Saudi Arabia and developed an empirical correlation for the estimation of global solar radiation at locations where it is not measured. The paper also presents the comparison between the present correlation and other models developed under different geographical and varied meteorological conditions. The comparisons are made using standard statistical tests, namely mean bias error (MBE), root mean square error (RMSE), mean percentage error (MPE), and mean absolute bias error (MABE) tests. The errors are calculated using monthly mean daily measured and estimated values of global solar radiation at all 41 locations. The study found that the present correlation produced the best estimates of global solar radiation.     

Confinement-Induced Phonon Softening and Hardening in Sb2Te3 Thin Films

Scaling effects in Sesqui-chalcogenides are of major interest to understand and optimize their performance in heavily scaled applications, including topological insulators and phase-change devices. A combined experimental and theoretical study is presented for molecular beam epitaxy-grown films of antimony-telluride  (Sb₂Te₃). Structural,vibrational, optical, and bonding properties upon varying confinement are studied for thicknesses ranging from 1.3 to 56 nm. In ultrathin films, the low-frequency coherent phonons of A_1g¹ symmetry are softened compared to the bulk (64.5 cm⁻¹ at 1.3 nm compared to 68 cm⁻¹ at 55.8 nm). A concomitant increase of the high-frequency A_1g² Raman mode is seen. X-ray diffraction analyses unravel an accompanying out of plane stretch by 5%, mainly stemming from an increase in the Te-Te gap. This conclusion is supported by density functional theory slab models, which reveal a significant dependency of chemical bonding on film thickness. Changes in atomic arrangement, vibrational frequencies, and bonding extend over a thickness range much larger than observed for other material classes. The finding of these unexpectedly pronounced thickness-dependent effects in quasi-2D material Sb₂Te₃ allows tuning of the film properties with thickness. The results are discussed in the context of a novel bond-type, characterized by a competition between electron localization and delocalization.