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Digital Transformation and the Cybersecurity of Infrastructure Systems in the Oil And Gas Sector
Published in Edward Ochieng, Tarila Zuofa, Sulafa Badi, Routledge Handbook of Planning and Management of Global Strategic Infrastructure Projects, 2020
Returning to the risk equation in Figure 16.3, the threat variable is widely considered to be extremely difficult to control by oil and gas organisations. Indeed, cybersecurity threats could be described as uncertain risks (Renn, 2008) given the inherent unreliability of the empirical data that can be employed in objective estimations of the probability of specific cyber risks. Thus, as Quigley et al. (2015) argue, “fuzzy” or subjective methods of risk estimation are often used in cybersecurity risk management processes. Hence, given the limited control over the threat variable, organisations often focus on the vulnerability and consequences variables (Henrie, 2013). Vulnerabilities are weaknesses in a company's communication infrastructure, network, or individual computers that can be exploited. These security holes can be defined, identified, and classified through a vulnerability analysis process or vulnerability assessment. Such evaluations include a series of systematic measures that are used to review and prioritise security weaknesses. The assessments help organisations to determine their security status and level of exposure to threats (Yaqoob et al., 2017). The definition of a vulnerability assessment is often confused with penetration testing (pen test). Both methods report the vulnerabilities in a system or network, but the difference is that penetration testing verifies the existence of vulnerabilities by attempting exploitation (Yaqoob et al., 2017). A penetration test is an authorised attack simulation on systems and networks. The purpose of compromising systems during penetration testing is to make an organisation aware of the security weaknesses in their systems and processes and subsequently to address these vulnerabilities to mitigate a real attack scenario (Denis et al., 2016). A system's vulnerability can be reduced through enhanced cybersecurity.
Influence of nanosilica particles on the high-temperature performance of waste denim fibre-modified bitumen
Published in International Journal of Pavement Engineering, 2022
Abdulnaser M. Al-Sabaeei, Madzlan B. Napiah, Muslich H. Sutanto, Wesam S. Alaloul, Salah E. Zoorob, Aliyu Usman
The penetration of the base bitumen and modified bitumen binders were tested using a penetrometer. The aim of the test was to evaluate the hardness and effects of the fibre and NS on the consistency of the bitumen before and after heating. The penetration test was conducted according to ASTM D5-13 standard specification.
Multi-scale geotechnical features of dredger fills and subsidence risk evaluation in reclaimed land using BN
Published in Marine Georesources & Geotechnology, 2020
Linbo Wu, Jianxiu Wang, Jie Zhou, Tianliang Yang, Xuexin Yan, Yu Zhao, Zhenhua Ye, Na Xu
Regional analysis of both reclaimed lands and the evolution of Shanghai’s coastline from 1984 to 2016 was conducted using Google Satellite Maps (n.d.; http://www.google.cn/maps). Field surveys in Shanghai’s typical reclaimed zones, i.e., Hengsha Island and Binhai Town (Figure 3) were conducted using drilling, drone (Phantom 4 Pro) aerial investigation, and cone penetration tests (CPTs) from 2016 to 2017. Both the borehole points and the CPT points were set homogeneous in the study regions (Figure 3(b) and (e)). Considering the study regions over 60 km2 and the weak land in the newly reclaimed fields, single-bridge CPT was conducted in 29 points, the friction cone is a stainless steel probe, 35.7 mm in diameter and tipped with a conical point with an apex angle of 60°. The CPT was done according to Technical Specification for Cone Penetration Test (SIGEID 2016). Twenty seven CPT points of the total twenty nine points were located in reclaimed fields of Hengsha Island, another two were in Binhai Town for comparison. Given borehole logs in the same fields, CPT tip resistance ps profiles were interpreted. To explore spatial heterogeneity of the dredger fill layer ①3-2, data point per 0.1 m downwards in vertical direction were obtained from the 27 ps profiles in Hengsha Island. To compare dredger fill with underlying sediments, ps data of layer ②3, ③1, ③2 and ④ (Table 1) were also analyzed. Statistic description of the ps was done for single CPT ps profiles and the total 27 CPT ps profiles in Hengsha Island. Vertical dispersion of ps within single layers of single CPT points can be characterized using vertical standard deviation (σv), horizontal dispersion of ps within single layers among the total 27 CPT points can be characterized using horizontal standard deviation (σh) of vertical mean values (). To show spatial heterogeneity of single layers among the 27 CPT points, standard deviation ratio (σv/σh) was calculated.