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The inclusion of grey literature (GL) is important to remove publication bias while gathering available evidence regarding a certain topic. The number of systematic literature reviews (SLRs) in Software Engineering (SE) is increasing but we do not know about the extent of GL usage in these SLRs. Moreover, Google Scholar is rapidly becoming a search engine of choice for many researchers but the extent to which it can find the primary studies is not known. Objective: This tertiary study is an attempt to i) measure the usage of GL in SLRs in SE. Furthermore this study proposes strategies for categorizing GL and a quality checklist to use for GL in future SLRs; ii) explore if it is feasible to use only Google Scholar for finding scholarly articles for academic research. Method: We have conducted a systematic mapping study to measure the extent of GL usage in SE SLRs as well as to measure the feasibility of finding primary studies using Google Scholar. Results and conclusions: a) Grey Literature: 76.09% SLRs (105 out of 138) in SE have included one or more GL studies as primary studies. Among total primary studies across all SLRs (6307), 582 are classified as GL, making the frequency of GL citing as 9.23%. The intensity of GL use indicate that each SLR contains 5 primary studies on average (total intensity of GL use being 5.54). The ranking of GL tells us that conference papers are the most used form 43.3% followed by technical reports 28.52%. Universities, research institutes, labs and scientific societies together make up 67.7% of GL used, indicating that these are useful sources for searching GL. We additionally propose strategies for categorizing GL and criteria for evaluating GL quality, which can become a basis for more detailed guidelines for including GL in future SLRs. b) Google Scholar Results: The results show that Google Scholar was able to retrieve 96% of primary studies of these SLRs. Most of the primary studies that were not found using Google Scholar were from grey sources.

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The previous year has seen an enormous increase in the studies related to social engineering. This increase is partly due to increasing number of social engineering attacks and partly due to people's inability to identify the attack. Thus, it is of great importance to find solutions which are helpful for human to understand the social engineering attacks and scenarios. To address this, we have performed a literature review of studies (on social engineering) in top-notch journals and conferences. In this paper, we have enlisted the types of attacks, and the persuasion techniques used by social engineers as listed in the literature. We also combined different theories which researchers tried to use to explain various activities of social engineers. Furthermore, we have mentioned that a better understanding of the social engineering attack scenarios can be done using thematic and game-based analysis techniques.Preliminary empirical evaluation of the proposed game based method shows overall neutral results. Future extension and evaluation is needed for the proposed methods. K E Y W O R D Scybercrime, cyber-security, human factors, human-centered, information security, review, social engineering

Protecting people from cyber threats imposes great challenges, not only technically, but also socially. To achieve the intended level of awareness, software security principles need to be shown with concrete examples during security education. This study aims to design a serious game integrating software security knowledge and concepts into the processes to make it more engaging to learn while playing. In this paper, we have: (i) designed a serious game to compensate the deficiencies in the literature; (ii) performed empirical evaluations including survey, brainstorming and observation to the proposed game. Results: Our study shows that: (i) Cyber Security-Requirements Awareness Game (CSRAG) has a positive effect on players security learning outcomes, level of engagement and participation; (ii) Game-based learning can be an effective way of teaching security related scenarios.

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In social media platforms, crowd-users extensively interact and contribute information related to software applications. Usually, crowd-users discuss software features or hot issues and record their opinions about the software applications under discussion either in textual form or via end-user votes. Such requirements-related information is considered a pivotal alternative source for requirements engineers to the already existing in-house stakeholders in order to illustrate decision-making. Also, requirements decision-making for Crowd requirements engineering is a difficult task, as it is always based on incomplete knowledge and requires trade-offs from multi-perspectives. However, existing requirements models and associated tools are still lacking, which enable requirements engineers to make informed decision-making and capture conflicting requirements knowledge. This paper elaborates the interaction among the crowd-users about the Google Map mobile application in the Reddit forum to recover conflicting requirements-related information using the goal modeling approach. For this purpose, we extracted critical arguments from a crowd-users conversation in user forums regarding a given design; built a graphical argumentation model based on the extracted information; aligned types of arguments with goal-oriented modeling constructs in the non-functional requirements framework; conducted exiting goal-model analysis to the requirements model to reach consensus based on argumentation and reasoning, such as supporting, attacking, undefined, and conflicting. The proposal is described with illustrative example models and the associated evaluation processes of design decision-making situation for Google Map interface design.