SCARS Institute’s Encyclopedia of Scams™ Published Continuously for 25 Years
SCARS™ Guide: What Is Big Data?
Big Data – Big Scams Databases
If the pile of manure is big enough, you will find a gold coin in it eventually. This saying is used often to explain why anyone would use big data. Needless to say, in this day and age, the piles of data are so big, you might end up finding a pirate’s treasure. In our case we look for scammers – the real scammers in the noise of all the reports filed.
How Big Is The Pile?
But when is the pile big enough to consider it big data? Per Wikipedia:
“Big data is data sets that are so big and complex that traditional data-processing application software is inadequate to deal with them.”
As a consequence, we can say that it’s not just the size that matters, but the complexity of a dataset. The draw of big data to researchers and scientists, however, is not in its size or complexity, but in how it may be computationally analyzed to reveal patterns, trends, and associations.
When it comes to big data, no mountain is high enough or too difficult to climb. The more data we have to analyze, the more relevant conclusions we may be able to derive. If a dataset is large enough, we can start making predictions about how certain relationships will develop in the future and even find relationships we never suspected to exist. For example, we might find a financial manager in Malaysia that is managing the proceeds from scams in the Ivory Coast!
The Treasure
We mentioned predicting the future or finding advantageous correlations as possible reasons for using big data analysis. Just to name a few examples, big data could be used to set up profiles and processes for the following:
- Stop terrorist attacks by creating profiles of likely attackers and their methods.
- More accurately target customers for marketing initiatives using individual personas.
- Calculate insurance rates by building risk profiles.
- Optimize website user experiences by creating and monitoring visitor behavior profiles.
- Analyze workflow charts and processes to improve business efficiency.
- Improve city planning by analyzing and understanding traffic patterns.
- Discover how a local African University has been co-opted by scammers, or how a new corporate scammer group has begun operations in Mauritius.
Beware of Apophenia
Apophenia is the tendency to perceive connections and meaning between unrelated things. What statistical analysis might show to be a correlation between two facts or data streams could simply be a coincidence. There could be a third factor at play that was missed, or the data set might be skewed. This can lead to false conclusions and to actions being undertaken for the wrong reasons.
For example, analysis of data collected about medical patients could lead to the conclusion that those with arthritis also tend to have high blood pressure. When in reality, the most popular medication to treat arthritis lists high blood pressure as a side effect. Remember the old research edict: correlation does not equal causation.
In statistics, we call this a type I error, and it’s the feeding ground for many myths, superstitions, and fallacies.
This is a word most victims should remember since the tendency to make false assumptions is profound.
The Researchers
As more and more data becomes digitized and stored, the need for big data analysts grows. A recent study showed that 53 percent of the companies interviewed were using big data in one way or another. Some examples of use cases for big data include:
- Data warehouse optimization (considered the top use case for big data) (such as for scam reports numbering in the millions)
- Analyzing patterns in scammer language used to identify scriptwriters
- Sports statistics and analysis; sometimes the difference between being the champion or coming in second comes down to the tiniest detail
- Prognosis statistics or success rates of particular medications can influence a doctor’s recommended course of treatment; an accurate assessment of which could be the difference between life and death
- Selecting stocks for purchase and trade; quick decision-making based on analytical algorithms gives traders the edge
We use big data in the form of anonymous data gathered from reports to monitor active threats. Viewing these data sets allows us to see trends in scams development, from the types of scams that are being used in the wild to the geographic locations of attacks.
From these data, we’re able to draw conclusions and share valuable information with the public and our data feed recipients in government and law enforcement or website operators, in report forms, such as our annual Cybercrime & Scam Tactics and Techniques report, and even in heat maps showing where scammers receive money or operate.
The Tools
Technologically, the tools you will need to analyze big data depend on a few variables:
- How is the data organized?
- How big is big?
- How complex is the data?
When we are looking at the organization of data, we are not just focusing on the structure and uniformity of the data, but the location of the data as well. Are they spread over several servers, completely or partially in the cloud, or are they all in one place?
Obviously, uniformity makes data easier to compare and manipulate, but we don’t always have that luxury. And it takes powerful and smart statistical tools to make sense out of polymorphous or differently-structured datasets.
As we have seen before, the complexity of the data can be another reason why we need special big data tools, even if the sheer number is not that large.
As big data tools are made available, they are still in the early stages of development and not all of them are ready for intuitive use. It requires knowledge and familiarity to use them most effectively.
Your Personal Data
When we go online, we leave a trail of data behind that can be used by marketers (and criminals) to profile us and our environment. This makes us predictable to a certain extent. Marketers love this type of predictability, as it enables them to figure out what they can sell us, how much of it, and at which price. If you’ve ever wondered how you saw an ad for vintage sunglasses on Facebook when you were only searching on Google, the answer is big data.
Scammers are also beginning to understand the value of big data as they are developing automated tools to scan social media profiles and predict who will make the best targets.
Imagine a virtual assistant that retrieves travel arrangement information at your first whim of considering a vacation. Hotels, flights, activities, food and drink—all could be listed to your liking, in your favorite locations, and in your price range at the blink of an eye. Some may find this scary, others would consider it convenient. However you feel, the virtual assistant is able to do this because of the big data it collects on you and your behavior online.
Scammers are testing this kind of data that they are buying from legitimate sources (though the sources do not know it will be used by scammers).
The Data-Driven Society
One of the major contributions of big data to our society will be through the Internet of Things (IoT). IoT represents the most direct link between the physical world and the cyber world we’ve experienced yet. These cyber-physical systems will, of course, be shaped by the objects and software we create for them, but their biggest influence will be the result of algorithms applied to the data they collect.
With the evolution of these systems, we can expect to evolve into a data-driven society, where big data plays a major role in adjusting the production to meet our expected needs. This is an area where we will need safeguards in the future to prevent big data from turning into Big Brother.
Imagine for example if your scammer had had access to your IoT devices and not just your Facebook profile. The scammer could have watched you on your security camera or listened to you on your Amazon Echo. These fears are not so far away or unrealistic!
Big Data, Big Breaches
The obvious warning is that gathering and manipulating big data require extra attention paid to security and privacy, especially when the data are worth stealing. While raw datasets may seem like a low-risk asset, those who know how to find the gold (cyber) coin in the pile of manure will see otherwise. With the advent of the European GDPR in May 2018, any form of personally identifiable information (PII) will be sought after with great urgency, as the safeguards put in place to protect PII place endanger the lively black market trade set up around it.
The lesson, then, is to take seriously big data’s impact, both for good and for evil. Perhaps the whole pile should be considered the treasure.
We certainly treat every bit of data we have about scammers and victims in this way!
SCARS™ Team
A SCARS Division
Miami Florida U.S.A.
TAGS: Big Data, Bigdata, Databases, Scammer Data, Report Data, Scammer Reports, Data Feeds, Data Breaches, Data Risk, personally identifiable information, PII, GDPR, Privacy, Cybersecurity,
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FAQ: How Do You Properly Report Scammers?
It is essential that law enforcement knows about scams & scammers, even though there is nothing (in most cases) that they can do.
Always report scams involving money lost or where you received money to:
- Local Police – ask them to take an “informational” police report – say you need it for your insurance
- Your National Police or FBI (www.IC3.gov »)
- The SCARS|CDN™ Cybercriminal Data Network – Worldwide Reporting Network HERE » or on www.Anyscam.com »
This helps your government understand the problem, and allows law enforcement to add scammers on watch lists worldwide.
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Visit our NEW Main SCARS Facebook page for much more information about scams and online crime: www.facebook.com/SCARS.News.And.Information »
To learn more about SCARS visit www.AgainstScams.org
Please be sure to report all scammers HERE » or on www.Anyscam.com »
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SCARS, RSN, Romance Scams Now, SCARS|WORLDWIDE, SCARS|GLOBAL, SCARS, Society of Citizens Against Relationship Scams, Society of Citizens Against Romance Scams, SCARS|ANYSCAM, Project Anyscam, Anyscam, SCARS|GOFCH, GOFCH, SCARS|CHINA, SCARS|CDN, SCARS|UK, SCARS Cybercriminal Data Network, Cobalt Alert, Scam Victims Support Group, are all trademarks of Society of Citizens Against Relationship Scams Incorporated.
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A Note About Labeling!
We often use the term ‘scam victim’ in our articles, but this is a convenience to help those searching for information in search engines like Google. It is just a convenience and has no deeper meaning. If you have come through such an experience, YOU are a Survivor! It was not your fault. You are not alone! Axios!
A Question of Trust
At the SCARS Institute, we invite you to do your own research on the topics we speak about and publish, Our team investigates the subject being discussed, especially when it comes to understanding the scam victims-survivors experience. You can do Google searches but in many cases, you will have to wade through scientific papers and studies. However, remember that biases and perspectives matter and influence the outcome. Regardless, we encourage you to explore these topics as thoroughly as you can for your own awareness.
Statement About Victim Blaming
Some of our articles discuss various aspects of victims. This is both about better understanding victims (the science of victimology) and their behaviors and psychology. This helps us to educate victims/survivors about why these crimes happened and to not blame themselves, better develop recovery programs, and to help victims avoid scams in the future. At times this may sound like blaming the victim, but it does not blame scam victims, we are simply explaining the hows and whys of the experience victims have.
These articles, about the Psychology of Scams or Victim Psychology – meaning that all humans have psychological or cognitive characteristics in common that can either be exploited or work against us – help us all to understand the unique challenges victims face before, during, and after scams, fraud, or cybercrimes. These sometimes talk about some of the vulnerabilities the scammers exploit. Victims rarely have control of them or are even aware of them, until something like a scam happens and then they can learn how their mind works and how to overcome these mechanisms.
Articles like these help victims and others understand these processes and how to help prevent them from being exploited again or to help them recover more easily by understanding their post-scam behaviors. Learn more about the Psychology of Scams at www.ScamPsychology.org
Psychology Disclaimer:
All articles about psychology and the human brain on this website are for information & education only
The information provided in this article is intended for educational and self-help purposes only and should not be construed as a substitute for professional therapy or counseling.
While any self-help techniques outlined herein may be beneficial for scam victims seeking to recover from their experience and move towards recovery, it is important to consult with a qualified mental health professional before initiating any course of action. Each individual’s experience and needs are unique, and what works for one person may not be suitable for another.
Additionally, any approach may not be appropriate for individuals with certain pre-existing mental health conditions or trauma histories. It is advisable to seek guidance from a licensed therapist or counselor who can provide personalized support, guidance, and treatment tailored to your specific needs.
If you are experiencing significant distress or emotional difficulties related to a scam or other traumatic event, please consult your doctor or mental health provider for appropriate care and support.
Also read our SCARS Institute Statement about Professional Care for Scam Victims – click here to go to our ScamsNOW.com website.
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