Employee information security practices are pivotal to prevent, detect, and respond to security incidents. This article synthesizes insights from research on challenges related to employee information security practices and measures to address them. The challenges identified are associated to idiosyncratic aspects of communities and individuals within organizations (culture and personal characteristics) and to systemic aspects of organizations (procedural and structural arrangements). The measures aimed to enhance systemic capabilities and to adapt security mechanisms to the idiosyncratic characteristics and are categorized as: (a) measures of training and awareness; (b) measures of organizational support; and (c) measures of rewards and penalties. Further research is needed to explore the dynamics related to how challenges emerge, develop, and get addressed over time and also, to explore the interplay between systemic and idiosyncratic aspects. Additionally, research is needed on the role of security managers and how it can be reconfigured to suit flatter organizations.

ABSTRACT The Norwegian Green Tax Commission proposes inter alia cost-effective taxes on red meat and city traffic to reduce greenhouse gas emissions and local air pollution. Implementation requires public support, but the acceptance of and willingness to pay (WTP) such taxes are not known. We conducted a national survey of the public's acceptance of and WTP the two taxes. The survey instrument showed the reduction in emissions/pollution dynamically for each tax level chosen. Despite survey information about the purpose of the taxes, only 25%, on average, were in favour of their introduction, the rest did not know, had zero WTP, or opposed the taxes. In this respect, preferences for the two taxes are similar. However, on average people are WTP approximately 90% of the cost-effective tax level for red meat, but only about 25%–35% of the tax on city traffic, depending on fuel type. The most important concern in designing environmental policy was to avoid increased economic inequality. Earmarking the tax revenue for environmentally friendly technology increased acceptable tax level for red meat. Earmarking tax revenues for reduced income tax did not increase the acceptability of proposed taxes on neither red meat nor city traffic.”

In the past, many researchers have carried out water-hammer pressure analysis using Joukowsky equation. However, it has been observed that the computed pressure surge is no longer applicable based on the equation. The Joukowsky equation cannot be used even within the reflection time of the long pipeline. In such cases, the actual pressure rise due to the sudden closure of a quick acting valve will be several times more than that of the sudden increase in pressure as calculated by the Joukowsky equation. The phenomenon of rising pressure at the upstream of an instantaneously closed valve with the passage of time caused by the pipe friction is commonly called as linepacking. In this paper, various parameters affecting the linepack pressure have been thoroughly investigated. As the relative roughness increases, the resulting non-dimensional linepack pressure \( \left( {P_{LP} /P_{o} } \right) \) significantly increases and the proportionality constant was equal to 1.5. The linepack pressure was determined to be decreasing with increasing valve closure time. The dominant parameter that influences the linepack pressure is found to be the Reynolds number as compared to the Mach number, and the relative roughness. Furthermore, the linepack pressure is found to be proportional to frictional head loss \( \left( {h_{L} /D} \right) \), and inversely proportional to inlet pressure \( \left( {P_{o} /\left( {\gamma L_{o} } \right)} \right) \). Finally, a linear regression equation was developed in terms of non-dimensional variables to estimate the linepack pressure using hand calculations without undergoing numerical modeling procedures. The proposed equation was validated for sudden valve closure pressure histories available in the literature. The proposed method is applicable to long distance water supply pipelines where the linepack pressures are significant.

With the upcoming introduction of 5G networks for our daily usage and convenience and with the purpose of accommodating a countless amount of Internet of Things (IoT) devices and applications alongside the billion devices that already use the network (e.g. mobile phones), one of the key aspects for its success is to ensure to these upcoming devices enhanced but affordable security. With this paper, we present a solution that introduces an Identity Federation mechanism that reuses the SIM authentication for cellular IoT devices, enabling single sign-on features. This solution aims to relieve the responsibility of IoT providers for developing (proprietary) device identity management mechanisms while allowing to reduce operation costs overall.

Due to its high strength and acceptable corrosion resistance, Alloy 718 is a viable material for the use in subsea applications. The alloy's susceptibility to hydrogen embrittlement is however limiting its viability. In this work the effect of microstructure on the hydrogen embrittlement susceptibility of Alloy 718 was examined by the use of slow strain rate testing on three different heat treatments. Cathodic pre-charging and polarization during testing were used to introduce hydrogen into the samples. A severe reduction in the ductility of the alloy due to the precipitation phases γ″ and γ′ were found. In addition, one of the heats had a continuous film of a Nb and C rich phase on the grain boundary giving an intergranular fracture mechanism. This intergranular fracture mode was further enhanced by the presence of hydrogen. In the solution annealed condition, the presence of hydrogen reduced the dimple size on the fracture surface.

Although the vision of 5G is to accommodate billions IoT devices and applications, its success depends very much on its ability to provide enhanced and affordable security. This paper introduces an Identity Federation solution which reuses the SIM authentication for cellular IoT devices enabling single-sign-on. The proposed solution alleviates the IoT provider's burden of device identity management at the same time as the operational costs are reduced considerably. The proposed solution is realized by open source software for LTE, identity management and IoT.

A submerged floating tube bridge (SFTB) concept is one of the three alternatives for the Bjørnafjord crossing in Norway. Two SFTB designs have been developed: one pontoon-stabilized and one tether-stabilized. There are no submerged floating tube bridges yet built and installed. Consequently there is no direct practical experience with assembly and installation of such massive string-like structures. The purpose of this article is to describe possible means of fabrication, assembling, jointing and installation of SFTB elements and the tube-bridge itself. All major project activities have been divided into stages. Further, these stages have been subdivided into factual steps to demonstrate feasibility based on various criteria. The major construction challenge is to assembly fabricated SFTB elements into one 4580 m string in a floating condition and then to tow and install it in the fjord. The focus was to utilize existing technologies and experiences available from offshore industry to the fullest extent, so that conventional tools and methods could be applied to this new application. Possible solutions both for the tether-stabilized and pontoon-stabilized alternatives — with differences in the foundation/tether and pontoon installations and associated SFTB interfaces — have been developed.

In situ electrochemical nanoindentation has been used to study the effect of hydrogen on the nanomechanical response of Alloy 718. Observations show that hardness increase as a result of hydrogen charging. Also, the hydrogen charging gives a reduced pop-in load and pop-in width. This is related to a reduction in the energy needed for dislocation nucleation and the mobility of the dislocations in the presence of hydrogen. Two grains with different orientations has been tested here. The pop-in load and width obtained in the (101) orientation was more affected by the presence of hydrogen than those achieved in the (111) oriented grain.

Lately, mobile operators experience threats from SMS grey routes which are used by fraudsters to evade SMS fees and to deny them millions in revenues. But more serious are the threats to the user's security and privacy and consequently the operator's reputation. Therefore, it is crucial for operators to have adequate solutions to protect both their network and their customers against this kind of fraud. Unfortunately, so far there is no sufficiently efficient countermeasure against grey routes. This paper proposes a near real time SMS grey traffic detection which makes use of Counting Bloom Filters combined with blacklist and whitelist to detect SMS grey traffic on the fly and to block them. The proposed detection has been implemented and proved to be quite efficient. The paper provides also comprehensive explanation of SMS grey routes and the challenges in their detection. The implementation and verification are also described thoroughly.

Lately, costly and threatening DNS tunnels on the mobile networks bypassing the mobile operator’s Policy and Charging Enforcement Function (PCEF), has shown the vulnerability of the mobile networks caused by the Domain Name System (DNS) which calls for protection solutions. Unfortunately there is currently no really adequate solution. This paper proposes to use machine learning techniques in the detection and mitigation of a DNS tunneling in mobile networks. Two machine learning techniques, namely One Class Support Vector Machine (OCSVM) and K-Means are experimented and the results prove that machine learning techniques could yield quite efficient detection solutions. The paper starts with a comprehensive introduction to DNS tunneling in mobile networks. Next the challenges in DNS tunneling detections are reviewed. The main part of the paper is the description of proposed DNS tunneling detection using machine learning.