An analysis on security awareness of social networks users

Online social networking develops interactions and communication approaches. Online environment is the most beneficial approach for retention and inception of social relations. However, by developing facilities in online services the threats of privet security is increase. The information security vulnerability is an emerging problem in the online social networks social networks. The more users join, the more active they are, the more possible risk of personal information disclosure due to lack of self and social awareness on user behavior in the social networks. The main objective of the study is to investigate the components affecting information security behavior in enhancing awareness and design an information security behavior model in enhancing awareness. The quantitative research has been conducted on students studying at University Technology Malaysia. The study has found significant relationship between self-efficacy, security practice- care behavior, intention to practice privacy protection on information security awareness behavior. At the end, recommendations for future studies and limitations of the study were further established

Effect of heat treatment on hardness and wear resistance of high carbon-high chromium steel (FMU-11)

In the present study, microstructure, hardness, and abrasion resistance of a heat-treated high carbon-high chromium steel (FMU-11) used in the cement mills were investigated. To investigate the best heat-treating cycle for the FMU-11 steel, three sets of samples were heat treated. The first set was tempered two times, the second set was re-hardened, and the third set was cryogenically heat treated. These samples were then compared with the conventionally heat-treated samples. The samples' microstructure was studied using an optical microscope, where traditional black and white etching, as well as color etching, were used. Scanning electron microscopy (SEM) was applied for higher magnification studies and in-depth analysis of the chemical composition. The mechanical properties were investigated by measuring the hardness and the wear resistance for the samples heat-treated in different cycles. The results showed that the cryogenic treatment and double-tempered samples had the highest hardness and wear resistance. In addition, the results showed that the re-hardening operation caused the carbides to be finely separated and evenly distributed in the steel matrix. The wear test results illustrated that the wear mechanism could be the delamination wear and the abrasive wear combined

Anonymity and untraceability assessment of authentication protocols in proxy mobile IPv6

The Proxy Mobile IPv6 or the PMIPv6 is a protocol for mobile management as established by the Internet Engineering Task Force or IETF to assist in the intense usage of mobile devices and to lower the overhead of signaling. As the inclusion of the mobile node in the signaling related to mobility is not necessary, this type of solutions based on networks optimize the performance of the handover based on signaling overhead and handover latency. Nevertheless, the PMIPv6 has several disadvantages such as issues of privacy and security. The process of authentication of users is usually needed at the time of connecting to a wireless network. The mobile users might wander away from their home networks and be approached by other network services. These network services would usually require the users' credentials to authorize the usage of the service. In order to retain a level of anonymity, various degrees of information are required to be safe guarded including the Local Mobility Anchor ID, Media Access Gateway, and Mobile Node. Nevertheless, a few methods of authentication have been suggested to enhance the PMIPv6's performance since 2008 when this protocol was first established [1]; however, the issues of privacy are often ignored. This study attempts to evaluate the authentication methods of the PMIPv6 according to the anonymity of several network mechanisms. The findings of this study reveal that it is important to suggest an appropriate method of enhancing the protection and privacy of network mechanisms

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Security analysis method of recognition-based graphical password

One of the most important primitive security mechanisms is the authentication system. Authentication through the use of password is a commonly utilized mechanism for authentication of users. In general, users utilize characters as their password; however, passwords based on texts are hard to recall and if the passwords are too simple and predictable, then there is the danger of being susceptible to threats. In order to overcome the problems with authentication, an alternative and new approach has been introduced utilizing images for passwords. The idea gains support from the knowledge that the human's brain is highly capable of remembering many detailed images, however remembering texts are more difficult. Users who utilize the graphic authentication carry out certain functions on the images such as to click, drag, and movement of the mouse and so on. This research reviews several common Recognition-Based graphical password methods and analyzes their security based on the estimation criteria. Moreover, the research defines a metric that would make it possible for the analysis of the security level of the graphical passwords that are Recognition-Based. Finally, a table comparing the limits of each method based on the security level is presented

Multidimensional Modeling of Physical Fatigue using Soft Computing Intelligence

Introduction: Physical fatigue is one of the major risk factors for work-related musculoskeletal disorders and has many life and financial costs. The impact of physical/biomechanical, psychosocial, environmental, and individual risk factors on muscle fatigue is undeniable. The aim of this study is to model the phenomenon of muscle fatigue (as output) in the hand in work environments based on these risk factors (as input) using soft computing methods. Material and Methods: In the first step, associated risk factors of fatigue for 156 subjects (in three job categories) were assessed using Copenhagen environmental, psychosocial, demographic, and Man-TRA tools. Then, the Roman-Liu equation and mean square amplitude of acceleration waves were used to measure fatigue with a dynamometer and a three-axis accelerometer, respectively. Finally, according to the nature of risk factors and the phenomenon of fatigue, six categories (24 methods) of supervised machine learning (SML) based on classification were selected. MatLab software (MatLab R2017b, The Mathworks Inc., MA, U.S.A.) was used to fit the models using SML. Results: The best-fitted models in the first and second half of the work shift were obtained using support vector machine methods. Physical risk factors had a significant impact on physical fatigue. After filtering low-priority risk factors, in the first half of the work shift, the most optimal model had an accuracy of 71.8%, precision of 72.5%, sensitivity of 76.9%, specificity of 70.8%, and discrimination power equal to 73%. In the second half of the work shift, the accuracy, precision, sensitivity, and specificity of the optimized model were 60.3%, 57.5%, 50%, and 46.9%, respectively, and the discrimination power was obtained at about 62%. Conclusion: The fitted models for hand fatigue had acceptable performance in both sections of the shift but can still be optimized. Therefore, it is necessary for future studies to improve the quality of input and output data and include other dimensions affecting fatigue such as cognitive workload and type of work shift in future models