Vulnerability Analysis - Science topic

We have worked on the technological package of crops (including electrical consumption) in these manuscripts that can serve you:

Dr. MOHAMMAD FAISAL currently working at the department of computer science and IT, University of Malakand Pakistan, received his M.S. degree in information security management from SZABIST, Pakistan, in 2012, and the Ph.D. degree in network security from the Department of Computer Science and Information Technology, University of Malakand in 2018. His research interests include ML and security of wireless ad hoc networks MANETs, VANETs, IoT, Cloud, Fog, Edge, Blockchain and digital forensics.

Hello Husen,

Standardizing typically means adjusting scores to have a specific distributional characteristic. This could include: (a) fixing the range (e.g., to fall between 0,1); (b) fixing the mean or median to some constant value; (c) fixing the variance or spread to some constant value; (d) some combination (as in the case of z-scores, which fix the values to have a mean of 0 and variance or SD of 1).

Normalizing has multiple meanings, which could include making the shape of a score distribution match that of a normal (Gaussian) distribution, transforming the values so that the sum of squared values = 1 (vector arithmetic), and others. In general, you'll never get a categorical variable to have a normal distribution.

For dichotomous variables, just code them as 0,1 (or 1,2). Any linear transformation of these values (e.g., to z-scores) will not change either the shape of the distribution or the correlation of scores on that variable with those of any other variable. For PCA based on correlations, rescaling via linear transforms will not impact the resultant structure or solution. For PCA based on covariances, yes, variables having larger variances will have larger initial communality estimates and other parts of the solution will differ. The fix for that is simple: Use correlation-based PCA (which automatically standardizes all variables).

For categorical variables with more than two levels, you'll have to re-express those as a set of k - 1 dummy variates (or similar), for a variable with k levels. So, there's really no standardizing that would make much sense for these for the same reason as that of a dichotomous variable.

Good luck with your work.

MATCASC is an open source MATLAB based tool to analyse cascading failures in power grids.

Try this link: https://github.com/trivikverma/MATCASC

Regards

The following articles will give you an idea on vulnerability analysis of Debris flow and its validation

DOI: 10.5194/nhess-13-869-2013

https://doi.org/10.1007/s12040-017-0899-link.springer.com/article/10.1007/s11707-019-0775-7

Hello, John Zhau

Usually the pentesters follow up the certain methodology (Framework), step by step test product and reflect results of the testing by creating mindmap. Summarized results of the testing are displayed after in the report for the customers.

The Penetration testing framework is here http://www.vulnerabilityassessment.co.uk/ . It provides very comprehensive hands-on penetration testing guide. It also lists the testing tools in each testing category. On the right side you can find Report template.

Examples of mindmapping are below or just google "mindmap for pentesters". In mindmap display both successful and failed test results.

More testing methodologies here https://www.owasp.org/index.php/Penetration_testing_methodologies

Dear Leônidas Luiz Volcato Descovi Filho ,

There is no method that can fit every case of study. DRASTIC request several factors that are not available in many countries; the spatial resolution of data is another problem. GOD is made for aquifers that have a large extension; it is not the best solution for small aquifers or where lateral and vertical lithological variations are frequent. SINTACS is the italian little brother of DRASTIS; it has thus the same shortcomings. AVI is based on permeability which is generally not available or the measurement points are poorly distributed...

Since geophysical data are mostly available or surveys could be done, we suggest a geophysical method for countries where data are lacking.

Please check this recent paper:

Regards

Try to look on security in communication protocols, LoRa and NB-IoT. These two protocols are widely used, so take a look at there security management. Security is so important especially when sending important data

Dear Hasanuzzaman,

As salamu alaikum. You can read our paper for getting idea about vulnerability assessment by using IPCC framework.

Best wishes,

Sarker

@Joseph Isabona. I have 10 nodes. Can I also calculate robustness, by calculating the size of largest component for few interested nodes and divide by the total number of nodes in the original network? Is it a right way to calculate robustness?

I believe the PAR model is the best we have now. It is not flawless though. But you can use it to identify social constructs in DRR.

You could also try NetSim - it has support for COAP protocol along with specialized frameworks for setting up attacks in IOT networks. You could look at https://tetcos.com/file-exchange.html for more information

Hi Johnson, this paper on research gate would provide some underpins to your research. https://www.researchgate.net/.../230504947_Soil_creep_Problems_raised_by_a_23_year...

I deal with the same point! Using ArcGIS ... which variables you will use

I have found in my own research in Tanzania that often mountain ecosystems can help people cope with drought easier because of the different microclimates around the mountains.  For example, while there may not be pasture in the lower dryland areas during drought, the higher elevations may still provide some pasture for livestock.

Thank you v.much Dr.Annes and Dr.Rajiv Pandey for providing your valuable comments and suggestions.

Brownly, 

I believe you need to define multiple parameters before you choose the proper tool to asses communities' post-disaster vulnerability.

First, which dimension are you looking at; physical infrastructure, social, economic, or environmental? All of the three dimensions are impacted by disasters, and in fact amplify the disaster impact on the community. 

Moreover, you should also determine if you are looking for vulnerability due to exposure to risk (proximity to hazards) or due to internal/inherent properties of the community. Even though some vulnerability assessment tools account for both in the same model (Environmental Vulnerability Index), I believe it is crucial to define your need. Exposure to risk vulnerability assessment is mostly beneficial for choosing where to rebuild. While inherent vulnerability helps in determining factors that needs to be enhanced to decrease future vulnerability to hazards. 

Furthermore, the level of analysis. Most tools focus on aggregated vulnerability assessment; countries and cities (Economic Resilience Index for OCED countries). However, there are tools that can calculate and assess vulnerability on the block level (Social Vulnerability Index by Cutter et. al 2003). 

Below are a list of some of the tools that I would recommend for such assessment: 

Environmental:

Social: 

Economic: 

If the word danger refers to threat, the equation that relates the threat, risk and vulnerability is:

R = T * V

-R = risk index

-T = threat index

-V = vulnerability index

Therefore, if the vulnerability is very low, the risk will be very low (if the vulnerability or threat is 0 the risk will be 0). If the vulnerability or threat is high, the risk is also high. If the vulnerability is low, and the threat is high or vice versa, the risk will be high or low depending on what values have the threat and vulnerability.

The equation of the disaster is: 

Disaster = threat * vulnerability / social preparation

Dear Mukesh,

The attached papers may be helpful to you.

Best Wishes,

P

In addition to the above great feedbacks, you should also take in consideration all dependencies(1st, 2nd, etc... Order Levels) that each asset leverages and how many assets may share common dependencies. 

Many are now calling it resilience research used in different context - veterans health, mass disasters, children and women's health i nthe context of early trauma, aging, HIV, etc

What you are looking for is very specific to a particular product . There is no way but to build it . You could identify an open source project like Firefox, OpenSSL, Linux Kernel etc for which the bugs (and vulnerabilities) are tracked publicly on their bug tracking systems. So you can pull the locations and build models around that. It is very specific to the project and may not be generic. 

We did similar work some time back not specifically on vulnerabilities but bugs in general , feel free to check out here . https://ece.uwaterloo.ca/~lintan/publications/imbalanced-icse15.pdf

Check this interesting paper in similar lines

I do not work with social modelling, but I would use old data and analyse them against the predictor variables (environmental and others). And based on this statistic I would create a predictive models and then used a second old dataset to validate, or rather evaluate, the predictive model. But that requires that the data used for happening is within the range of the data used for creating the model, if not you can not trust the predictive model if you  do not fully trust the interpolation that is made.

Hi Asimina

In case you are interested in the vulnerability of communities which highly depend on natural resources, I can recommend the following two documents:

Hi

Take a look to my paper entitled: ''Modelling nonpoint source pollution by nitrate of soil in the Mateur plain, northeast of Tunisia". 

There are no reliable data about disasters, as all sources have both (avoidable and unavoidable) technical problems, scope, and not least self interest in manipulating the information (political, financial or otherwise). In addition, you have serious problem of aggregation across events, countries and over time when, especially but not only, using panel data. As long as you are aware of these deep failures, you can entertain some loose thought experiments. But my recommendation would be that you should be extremely careful from reading, let alone interpreting, too much from available data. Have a look at my 2013 book (Routledge) “Disasters and the Networked Economy” (especially Chapter 1: The Problem with Quantitative Studies).

I agree with Fabiola. Resilience and vulnerability are not opposites. One can be vulnerability yet resilient at the same time. For example it's well known that social cohesion in informal settlements are much higher than in well off areas. This cohesion contributes greatly to resilience. In the same vain someone which we might perceive to be not vulnerable at all (e.g. rich urban dwellers) might not be able to cope at all if they are faced by a significant event (i.e. losing everything). Although I am not an ecologist I also believe we should be looking at socio-ecological resilience because these two domains are so inextricably linked. Resilience is thus not only a human attribute but rather a collective characteristic. Some interesting reading on the subject:

 Frerks, G., Warner, J., & Weijs, B. 2011. The politics of vulnerability and resilience. Ambiente & Sociedade. SciELO Brasil. 14(2):105–122.

Cannon, T. & Müller-Mahn, D. 2010. Vulnerability, resilience and development discourses in context of climate change. Nat Hazards. 55(3):621–635.

Folke, C., Carpenter, S.R., Walker, B., Scheffer, M., Chapin, T., & Rockström, J. 2010. Resilience thinking: integrating resilience, adaptability and transformability. E&S. HarperCollins Publishers. 15(4):20.

O'Brien, G., O'Keefe, P., Rose, J., & Wisner, B. 2006. Climate change and disaster management. Disasters. Blackwell Science Ltd. 30(1):64–80.

Klein, R.J.T., Nicholls, R.J., & Thomalla, F. 2003. Resilience to natural hazards: How useful is this concept? Environmental Hazards. 5(1):35–45.

Keck, M. & Sakdapolrak, P. 2013. What is social resilience? Lessons learned and ways forward. Erdkunde. 67(1):5–19.

Penetration testing tools are used to automate several tasks in order to improve testing performance and identify those security issues, which are harder to discover with manual testing analysis approaches. There are two general types of penetration testing tools: static and dynamic analysis. These both kind of tools are used with veracode to determine security susceptibilities. In addition, veracode’s binary scanning methodology is more accurate and result oriented that controls the false positive. The veracode can help small to large types of organization for handling the security risk. The penetration testing should be set in such a way to control the weak and vulnerable points of environment within the organization. The goal of incorporating penetration testing is the only way to secure the cyber-attacks and hacking.

So, the appropriate option is to make suitable change with Firewall and incorporate the penetration test features that can automate the testing process for security enhancement. The second option for automation of penetration testing is to employ with intrusion detection system (IDS) for handling the false positive. But I think Veracode-Platform does this function automatically.

Ok, I agree with Mr Holand's answer; however the answer to the question becomes more tricky if we are concerned with technological hazards (probably as Na-tech hazard. In this case exposure is not only a geographical property and there can be a confusion between exposure and vulnerability. Think for instance a young driver who is obsessed with high speeds and driving dangerously. He is of course exposed to a high probability of a car accident, i.e. exposed to a specific case of technical hazard. However, the factors of his exposure are intermingled with those of his vulnerability (he is in a sense an unconscious driver, susceptible to car accidents.