A Review on the Security of the Internet of Things: Challenges and Solutions

The Internet of Things (IoT) has emerged as a modern wave of Internet technologies that promises great transformation of life in areas such as smart health, smart cities, smart homes, intelligent transport, amongst others. However, security often serves as a critical reason for the widespread adoption of any innovation. While the IoT has increased business productivity and enriched diverse areas of life over the years, the world is yet to see a methodical revolution of its humongous application and transformation given its ubiquity and highly interconnected global network structure. The main culprit for such lapses is principally attributed to security and privacy issues which have been widely discussed in research articles and reviews but remain largely unaddressed in the literature. Hence, this paper provides a state-of-the-art review of IoT security and its challenges. It overviews technical and legal solutions that are useful to private, organizational, and governmental enterprises. The study encompasses the review and security analysis of IoT’s evolution and revolution, IoT security assessments, requirements, current research challenges in security and much more. Consequently, it offers potential solutions to address the security challenges discussed and further present open research issues, research gaps, opportunities, future development, and recommendations. This overview is intended to serve as a knowledgebase that will proffer novel foresight to guide users and administrators in positioning themselves and their organizations in a manner that is consistent with their overall objectives, mission, and vision for remarkable outcomes. Likewise, interested scholars and researchers can explore topics and directions from the study in providing better solutions to the numerous problems in IoT security.

     

Experimental study on bond behavior between corrosion-cracked reinforced concrete and CFRP sheets

Bond behavior between corrosion damaged reinforced concrete and carbon fiber reinforced concrete polymer (CFRP) sheets was experimentally investigated. Forty ordinary strength concrete blocks (150 × 150 × 200 mm) were reinforced at one side across the 200-mm-dimension using three conventional ?12 mm steel bars at a spacing of (30, 40, and 50 mm) at a concrete clear cover of 15 mm. Thirty blocks were subjected to a cyclic treatment in 3% chloride solution until corrosion initiated and resulted in three different global cracking widths of up to 0.90 mm. Both control and corrosion damaged blocks were attached to CFRP sheets over their steel reinforced zone at bond lengths and widths ranging from (90 to 150 mm) and (50 to 150 mm), respectively, with CFRP bond length-to-bar spacing ratio kept constant at 1/3. Near-end pull-off tests were carried out using a special setup, mounted on a Universal Testing machine. Corrosion cracking caused significant reductions in bond strength, and slippage at ultimate stress at (41 and 68%), respectively. Other bond characteristics such as stress at first slippage, and bond stiffness and toughness were reduced, as well, by as high as (83, 44 and 67%) of those of control specimens, respectively. Corrosion cracks were more detrimental for smaller bond length and width values; especially after first and second corrosion stages, where bond failure was categorized by concrete skin peeling-off.     

Stress–strain curve for concrete in circular columns based on elastoplastic analysis

This paper presents a stress–strain curve that describes the axial behavior of concrete in circular columns with lateral reinforcement. As opposed to most studies on this subject, which used semiempirical methods, the proposed stress–strain relations are based on a theoretical derivation. They have been derived from analysis of the problem’s full range according to the theories of elasticity and plasticity. Based on these theories, the current study analytically examines the influence of the main variables, such as the volumetric lateral reinforcement ratio and the material properties, on the behavior of circular confined concrete columns and proposes theoretical expressions that describe their stress–strain relations. Application of the proposed curve shows good agreement with published test results. Since these expressions were derived from a theoretical analysis, they can be considered as an analytical verification of existing empirical curves, yet they are also simple enough for practical applications.     

A bilinear programming model and a modified branch-and-bound algorithm for production planning in steel rolling mills with substitutable demand

In this paper, we address an instance of the dynamic capacitated multi-item lot-sizing problem (CMILSP) typically encountered in steel rolling mills. Production planning is carried out at the master production schedule level, where the various end items lot sizes are determined such that the total cost is minimised. Through incorporating the various technological constraints associated with the manufacturing process, the integrated production–inventory problem is formulated as a mixed integer bilinear program (MIBLP). Typically, such class of mathematical models is solved via linearisation techniques which transform the model to an equivalent MILP (mixed integer linear program) at the expense of increased model dimensionality. This paper presents an alternative branch-and-bound based algorithm that exploits the special structure of the mathematical model to minimise the number of branches and obtain the bound at each node. The performance of our algorithm is benchmarked against that of a classical linearisation technique for several problem instances and the obtained results are reported.     

Tolerance-based process plan evaluation using Monte Carlo simulation

In the discrete part manufacturing industry, engineers develop process plans by selecting appropriate machining processes and production equipment to ensure the quality of finished components. The decisions in process planning are usually made based on personal experience and the verification of process plans is based on physical trial-and-error runs, which is costly and time-consuming. This paper proposes to verify process plans by predicting machining tolerances via Monte Carlo simulation. The basic idea is to use a set of discrete sample points to represent workpiece geometry. The changes of their spatial position are simulated and tracked as the workpiece undergoes a series of machining processes. Virtual inspections are then conducted to determine the dimensional and geometric tolerances of the machined component. Machining tolerance prediction is completed through: (1) manufacturing error synthesis, and (2) error propagation in multiple operations. In this way, engineers can quickly screen alternative process plans, spot the root error causes, and improve their decisions. Therefore, physical trial-and-error runs can be reduced, if not eliminated, resulting in significant savings in both time and costs.     

Carbonic anhydrase inhibitors: design of membrane-impermeant copper(II) complexes of DTPA-, DOTA-, and TETA-tailed sulfonamides targeting the tumor-associated transmembrane isoform IX

The synthesis and carbonic anhydrase (CA, EC 4.2.1.1) inhibitory activity of two series of aromatic sulfonamides and their Cu(II) derivatives, incorporating metal-complexing moieties of the DTPA, DOTA, and TETA type are reported. The new compounds were designed in such a way as to possess high affinity for Cu(II) ions, exploiting four pendant carboxylate moieties in the DTPA derivatives, as well as the cyclen/cyclam macrocyles, and three pendant acetate moieties in the DOTA and TETA derivatives. The new derivatives showed modest inhibition of the cytosolic isoform CA I (K(I) values in the range of 66-2130 nM), were better CA II inhibitors (K(I) values in the range of 21-360 nM), and excellent inhibitors of the tumor-associated isoform CA IX (K(I) values in the range of 4.1-110 nM), with selectivity ratios for the inhibition of the tumor (CA IX) over the cytosolic (CA II) isozyme in the range of 10.74-20.88 for the best derivatives. Copper complexes were more inhibitory than the corresponding ligand sulfonamides, and showed membrane impermeability, thus, having the possibility to specifically target the transmembrane CA IX that has an extracellular active site. Incorporation of radioactive copper isotopes in this type of CA inhibitor may lead to interesting diagnostic/therapeutic applications for such compounds.     

Role of membrane pore size in tertiary flocculation/adsorption/ultrafiltration treatment of municipal wastewater

Flocculation, adsorption onto powered activated carbon (PAC), and ultrafiltration (UF), alone and in combination, were tested for tertiary treatment of the secondary effluent from municipal wastewater treatment at the Ashkelon plant (in southern Israel). Encouraging and reliable results of total organic carbon (TOC) of <3 mg/l were achieved with a combination of 130 mg/l FeCl₃, 0.6 g/l PAC and UF. The relative contribution of the UF membrane to the reduction of TOC changed with the molecular weight cut-off (MWCO) of the membrane, from a negligible 2.9% for a 100-kDa-MWCO membrane to 17% for 10- and 2-kDa membranes. The latter membranes, however, developed significant fouling, with a 35% drop in flux during first 30 min of the filtration cycle. The flux drop for the 50- and 100-kDa membranes was in the low range of 3%. The optimal MWCO interval of 20- to 50-kDa in combination with flocculation/PAC pretreatment gave a significant reduction in organic content with minimal membrane fouling. Detailed GC–MS analysis showed that the combined treatment gave very efficient retention of organic compounds with molecular weights below 800 Da, with the consequent absence of harmful compounds in the tertiary effluent. It was therefore concluded that the recommended flocculation/adsorption protocol constitutes an effective pretreatment for UF and that the obtained tertiary effluent can be used for unrestricted irrigation.     

Robust nonlinear model predictive control for nuclear power plants in load following operations with bounded xenon oscillations

One of the important operations in nuclear power plants is load-following in which imbalance of axial power distribution induces xenon oscillations. These oscillations must be maintained within acceptable limits otherwise the nuclear power plant could become unstable. Therefore, bounded xenon oscillation considered to be a constraint for the load-following operation. In this paper, a robust nonlinear model predictive control for the load-following operation problem is proposed that ensures xenon oscillations are kept bounded within acceptable limits. The proposed controller uses constant axial offset (AO) strategy to maintain xenon oscillations to be bounded. The constant AO is a robust state constraint for load-following problem. The controller imposes restricted state constraints on the predicted trajectory during optimization which guarantees robust satisfaction of state constraints without restoring to a min-max optimization problem. Simulation results show that the proposed controller for the load-following operation is so effective so that the xenon oscillations kept bounded in the given region.     

Polymer electrolyte membrane fuel cell contamination: Testing and diagnosis of toluene-induced cathode degradation

The effects of toluene contamination on the performance of polymer electrolyte membrane (PEM) fuel cells were investigated, using various levels of toluene concentration in the air streams, under different operational conditions and with different catalyst loadings. Constant-current polarization and electrochemical impedance spectroscopy (EIS) were conducted to analyze the poisoning behaviour of toluene. The severity of the contamination effect increased with an increase in both the current density and the toluene concentration, but decreased with an increase in both the relative humidity (RH) and the cathode-side Pt loading. The toluene-poisoned fuel cell could not be fully recovered by replacing toluene-contaminated air with pure air. EIS measurements revealed that both kinetic resistance and mass transfer resistance increased as a result of toluene contamination, while membrane resistance remained unchanged. However, the increase in kinetic resistance was a major contributor to cell performance degradation.     

Simulated Micromechanical Models Using Artificial Neural Networks

A new method, termed simulated micromechanical models using artificial neural networks (MMANN), is proposed to generate micromechanical material models for nonlinear and damage behavior of heterogeneous materials. Artificial neural networks (ANN) are trained with results from detailed nonlinear finite-element (FE) analyses of a repeating unit cell (UC), with and without induced damage, e.g., voids or cracks between the fiber and matrix phases. The FE simulations are used to form the effective stress-strain response for a unit cell with different geometry and damage parameters. The FE analyses are performed for a relatively small number of applied strain paths and damage parameters. It is shown that MMANN material models of this type exhibit many interesting features, including different tension and compression response, that are usually difficult to model by conventional micromechanical approaches. MMANN material models can be easily applied in a displacement-based FE for nonlinear analysis of composite structures. Application examples are shown where micromodels are generated to represent the homogenized nonlinear multiaxial response of a unidirectional composite with and without damage. In the case of analysis with damage growth, thermodynamics with irreversible processes (TIP) is used to derive the response of an equivalent homogenized damage medium with evolution equations for damage. The proposed damage formulation incorporates the generalizations generated by the MMANN method for stresses and other possible responses from analysis results of unit cells with fixed levels of damage.