=Paper=
{{Paper
|id=Vol-1375/paper3
|storemode=property
|title=Data Driven Ecosystem - Perspectives and Problems
|pdfUrl=https://ceur-ws.org/Vol-1375/SQAMIA2015_Paper3.pdf
|volume=Vol-1375
|dblpUrl=https://dblp.org/rec/conf/sqamia/JaakkolaHS15
}}
==Data Driven Ecosystem - Perspectives and Problems==
https://ceur-ws.org/Vol-1375/SQAMIA2015_Paper3.pdf
3
Data Driven Ecosystem – Perspectives and Problems
HANNU JAAKKOLA, Tampere University of Technology, Pori Department
JAAK HENNO, Tallinn University of Technology
JARI SOINI, Tampere University of Technology, Pori Department
Our society and business ecosystem is becoming data driven. The value of data is becoming comparable to the value of physical
products and becoming an important source of business. Open data itself is seen as a meaningful source of new business, especially
for small and medium-sized companies. Open data is purposely aimed at being public. In addition, there is a lot of data used as if it
were public – more or less without permission. In addition, the ownership of data has become unclear – the data related to an
individual is no longer under the control of the persons themselves. However, declaring data sets to be open and/or allowing access to
qualified users does not yet make data useful in practice. On the contrary, this often creates opportunities for misuse and dangers
regarding personal security.
Categories and Subject Descriptors: E [Data]; H.3 [Information Storage and Retrieval]; H.5. [Information interfaces and
Presentation]; K.5 [Legal Aspects of Computing]; K.6 [K.6 Management of Computing and Information Systems]; H.1.2
[Models and Principles]; K.6.5 [Security and Protection] Invasive software, Unauthorized access - K.7.4 [Professional
Ethics]: Codes of ethics, Codes of good practice; K.8 [PERSONAL COMPUTING]: Games;
General Terms: Data, Open Data, Information, Authentication, Invasive software, Unauthorized access, Codes of ethics
1. INTRODUCTION
Our societal and economic ecosystem is becoming data driven at an accelerating speed. In this context, we
are not referring to the concept of the “information society” but the importance of data, or to be exact, the
cultivated form of it – knowledge based on intelligent data integration – as a key element in the growth of
business and welfare of societies. Data possesses business value and changes the traditions of earning
models; companies like Facebook and Twitter own huge amounts of user-related profiled and structured
data that is valuable in targeted marketing activities or in finding people filling the requirements of a
certain kind of profile. In addition, the discussion threads of these services are providing APIs that make
the data streams (of public user profiles) more or less open for data analytics; the connection networks
(who is connected to whom) are also reasonably easy to analyze as well. To conclude – your value in these
(social) networks is your data - not you as a person or contact.
Data is the driving force behind most (future) services and applications. The fast growth of certain
innovative businesses is based on data, network infrastructure, and mobility – even in the case of physical
products, they are the ultimate source of business. The beneficial use of (social) networks provides a
means for communication and availability of potential collaborating (business) partners. In physical
products certain properties are built-in and certified – e.g. safety, quality, suitability for use; this is not
always true with data. There is also a similarity between data and physical products – e.g. both can be
stolen or used in the wrong way or in an illegal / unexpected context. Databases, contact information, or
personal profiles are valuable for criminals. Every day we encounter news related to cyber attacks and
cyber threats, as well as problems caused by defects in information systems and hijacking of computing
resources for illegal or criminal use. New innovations, like IoT, will cause new types of problems:
autonomous devices interacting with each other without human control – stories about cyber attacks
caused by network-connected devices are already a reality. The global character of cloud services also
provides several sources of problems – some related to the safety of data repositories, some to the
ownership of the data, and some in processes used to solve disagreements in legal interpretations (e.g.
which law is used in globalized implementations). Insurance companies have also noticed new business
Author's address: H. Jaakkola, Tampere University of Technology, Pori Department, email: hannu.jaakkola@tut.fi; J. Henno,
Tallinn University of Technology, email: jaak@cc.ttu.ee; Jari Soini, Tampere University of Technology, Pori Department, email:
jari.o.soini@tut.fi.
Copyright © by the paper’s authors. Copying permitted only for private and academic purposes.
In: Z. Budimac, M. Heričko (eds.): Proceedings of the 4th Workshop of Software Quality, Analysis, Monitoring, Improvement, and
Applications (SQAMIA 2015), Maribor, Slovenia, 8.-10.6.2015. Also published online by CEUR Workshop Proceedings (CEUR-
WS.org, ISSN 1613-0073)
3:18 • H. Jaakkola, J. Henno and J. Soini
opportunities: different data-related insurances are available that cover loss of data, losses caused by
service attacks, etc; in a way, data has become concrete and a physical asset.
Our paper studies the essence of data from different points of view. Section 2 of this paper is focused on
data driven changes. We will approach this topic by considering the data driven ecosystem changes driven
by hyperscalability. Data-related trends are included in this discussion. Starting with the characteristics
of data (Section 3) and continuing with issues related to open data. Section 4 concentrates on problems
related to data driven changes. Section 5 concludes the paper.
2. DATA DRIVEN CHANGES
2.1. New ecosystems and hyperscalability
In his blog, Omar Mohaut [2015] has introduced the term “hyperscalable” to point out the importance of
data in the growth of business. The only way companies that create physical goods have to scale up their
business is increasing productivity (industrialization) and growth of the market. This kind of growth is
capital-intensive and the limits are reached quite fast. He lists a set of new- generation companies:
Spotify, Skype, Square, PayPal, Facebook, Snapchat, Instagram, Airbnb, Pintrest, Uber, Twitter, Netflix,
Kickstarter, Eventbrite, Dropbox, Evernote, BlaBlaCar, Whatsapp, and Booking.com. Their business is
based on scalable models and they serve millions of users with very small teams of employees. The growth
of their business is not dependent on people in a traditional way, but supported by someone else‟s assets
as a free lever. Skype has 1,600 employees to operate 40% of international telephone traffic; Airbnb has
600 employees to offer 500,000 rooms for rent without any investment (Hilton, as the biggest hotel chain
in the world, has 300,000 employees to operate a hotel business of 680,000 rooms). In Whatsapp, 30
engineers support the message delivery of 7.2 trillion of messages per year (the total amount of traditional
SMS messages is 7.5 trillion).
Regarding business based on physical goods, Mohaut compares traditional shopping and e-commerce.
E-commerce implements a scalable business model: the website that runs 24*7 all year round and can be
reached from all over the world is scalable (data-based). However, physical sales never reach such
coverage, because humans as salesmen are not scalable, nor are the buildings needed for stock and
shopping centers. A good example of an improved e-commerce model is Alibaba, which handles the data
related to goods in the role of broker. As a scalable business concept in real physical goods, Mohaut
mentions the concept of franchising: instead of delivering your goods everywhere, you rent out the
business concept and brand.
To summarize – what is a hyperscalable business?:
1. A hyperscalable business model is based on intangible assets
2. A hyperscalable business model requires (information) technology as a lever
3. A hyperscalable business model uses the Internet as a free distribution channel
A business is hyperscalable when it “offers value at a near zero cost simultaneously to millions of users
with a disproportionately small team.” This business model is not based on the traditional factors of
production in economics: land, labor, and capital but on the intelligent and beneficial use of free resources
(data, Internet, social networks).
2.2. Trend Analysis as an Evidence
The studies provided by several market analysis companies provide evidence for the progress discussed
above. The analysis results also point out the importance of data and (mobile) networking as the driving
forces of this progress. SDTimes [2015; 2015a] has analyzed the reports of two leading companies- IDC
and Gartner Group. The main trends listed confirm the growing importance of data and the Internet as
key factors in progress and changes. The items gathered and combined from these trend lists cover:
1. New technology will take over the market. Growth is focused in 3rd Platform Technologies -
mobile devices, cloud services, social technologies, and Big Data.
2. Wireless data growth. Wireless data will balloon to 13% of telecommunications spending. The role
of mobile terminals is also changing from speech to data: according to (Finnish) statistics
Data Driven Ecosystem – Perspectives and Problems • 3:19
(Tekniikka & Talous, March 20th, 2015),the average mobile terminal transfer data is 169 MB per
day and 5 GB per month; the number of phone calls decreased by 3% in one year (2013-2014) and
the number of SMSs by 16%.
3. Cloud services. PaaS, SaaS and IaaS services will remain a hotbed of activity; the highest growth
(36%) is projected for IaaS adoption.
4. Big Data and analytics. In addition to the traditional structured and non-structured data, video,
audio and image analytics will have growing importance. Data-as-a-Service will forge new Big
Data supply chains focused on commercial and open data sets. The IDC (2012)study “Digital
Universe” reported fast growth in the amount of data applicable for open analytics (Big
Data),which is expected to grow from 130 EB (ExaBytes = 1018 Bytes) in 2005 to 40,000 EB in
2020.
5. The Internet of Things (IoT). The predictions identified IoT as one of the most important factors
for growth of the 3rd Platform. IoT is also based on mobile communication technologies to an
increasing extent. According to the current (Finnish) statistics, (Tekniikka & Talous, March 20th,
2015), 9.5% of all mobile devices are used by autonomous collaborating devices (other than mobile
terminals). The IDC [2012] study “Digital Universe” predicted/ forecast?? the growth of data
produced by autonomous devices: the percentage of such data is expected to grow from 11% to 20%
between 2005 and 2020, indicating the breakthrough of the Internet of Things (IoT) technology.
6. Cloud services will become the new data center. Data centers are undergoing a fundamental
transformation, with computing and storage capacity moving to cloud, mobile and Big Data-
optimized hyperscaled data centers operated by cloud service providers.
7. Security. IDC approaches this important issue with reference to 3rd Platform-optimized security
solutions for cloud, mobile and Big Data. It covers mechanisms including biometrics on mobile
devices and encryption in the cloud, as well as threat intelligence emerging as an essential Data-
as-a-Service category of enterprise-specific threat information. Gartner points out the importance
of risk-based security and self-protection. All roads to the digital future lead through security.
Because it is impossible to provide a 100% secured environment, there is a need for more
sophisticated risk assessment and mitigation tools. Every app will need to be self-aware and self-
protecting.
8. Ubiquitous Computing: The growth of importance of mobile devices will continue; organizations
have to focus their services and applications on diverse contexts and environments.
9. Advanced, Pervasive and Invisible Analytics: There is a need to manage how best to filter the
huge amounts of data coming from the IoT, social media, and wearable devices. Analytics will
become deeply but invisibly embedded everywhere.
10. Context-Rich Systems: Applications are able to understand their users and are aware of their
surroundings.
The trends point out the importance of mobility, cloud-based solutions and Big Data analytics. An
additional factor that has an impact on future life is the easy reachability of the masses – (social)
networking and its beneficial use in diverse activities. The 3rd Platform covers millions of apps, billions of
users and trillions of autonomous things. Innovative accelerators are robotics, natural interfaces to
services, Internet of Things, cognitive systems, and advanced security. Networks, mobile and wireless
data transfer and the increasing importance of cloud services are potential sources for increasing security
problems – theft of data, stealing of identity, cyber attacks, etc. The use of integrated data (as knowledge)
uses diverse sources of data – open and closed. The availability, easy access, quality, and reliability of
data will have increasing importance. (OR are growing in importance)
3. DATA CHARACTERISTICS – OPEN DATA AS AN OPPORTUNITY
Open Data is “data that are freely available to everyone to use and republish without restrictions from
copyright, patents or other mechanisms of control” [European Union 2014]. This refers to such data
sources that are open to the public by the “owner‟s” will. “Freely available” is implemented by providing a
published interface (API) as access to the data, which is “raw” and needs further processing into useful
3:20 • H. Jaakkola, J. Henno and J. Soini
form. “Without restrictions” indicates fully free use of the data. In practice, there are restrictions defined
by different levels of licensing.
Figure 1 (left side) illustrates the different data categories. In our classification, the term „Small Data‟
is used to cover all possible data repositories – closed and open. The term „Big Data‟ illustrates the part of
all data that is available for analytics and which provides access for intelligent analysis tools. Openly
Available Data covers such data sources that are available in networks and provide a means for
monitoring its content. Part of this availability is due to a lack of or insufficient security and part is on
purpose. Data sources in this category cover e.g. road cameras, weather stations, technical devices
connected to the Internet, www pages, data streams, and the content of social media services. The
interpretation of Open Data is explained above. An additional item in this figure is “My Data.” It
describes data that is in someway related to a person. By default its ownership is expected to belong to a
private person, because it handles his / her private property. However, an increasing amount of this is
collected by such information systems that are no longer under the control of an individual: social media
services, client and membership cards, location services, etc.
Fig. 1. Data Categories
The left side of Figure 1 approaches the classification from a different point of view. It points out the
existence of data that is not open on purpose (by the data owner). This gray area data belongs mainly to
the category of openly available data. It would also include such data sources that are available because of
insufficient security (by accident) or used against the expectations of the data owner (e.g. www page
contents).
The authors of this paper have handled the role of Open Data as a source of future business in their
paper [Jaakkola et al. 2014; 2014a]. These findings are summarized below. The starting point is the
Digital Agenda of the European Commission [European Union 2014]. The potential of Open Data in the
EU area delivers the following benefits:
Public data has significant potential for re-use in new products and services. Overall economic
gains from opening up this resource could amount to € 40 billion a year in EU direct business
volume (and € 140 billion indirectly).
Addressing societal challenges – having more data openly available will help us discover new and
innovative solutions;
Achieving efficiency gains through sharing data inside and between public administrations;
Fostering participation of citizens in political and social life and increasing transparency of
government.
According to our studies, most of the business cases are related to marketing, better understanding of
the business environment, availability of economic data related to clients and competitors, and the
opportunity to develop context-sensitive services (context is based on the results of open data analysis).
Weather and map data were seen as important sources. A lot of potential is also built in MOOCs
(Massively Open Online Courses) in education and industrial training.
However, there are also problems. Deloitte Analytics [2014] analyzed 37,500 datasets opened in the
UK (data.gov.uk; www.ons.gov.uk; data.london.gov.uk). The study shows the contradiction between the
supply and demand of open data. Governmental data are usually collected for official purposes, not for
pre-planned business use. The motivation to collect it comes from legal issues. This easily leads to a
Data Driven Ecosystem – Perspectives and Problems • 3:21
situation where the interface (API) to the data becomes complex and the structure of the data is not
suitable for effective and beneficiary reuse.
It is also a fact that Open Data is not open without restrictions. The most commonly applied licensing
systems in open data are Creative Commons (CC) Licences (http://www.creativecommons.org). The other
licensing systems, Open Data Commons (ODC) Licences (http://www.opendatacommons.org/) and Open
Government Licences (http://www.nationalarchives.gov.uk/doc/open-government-licence/version/2/) are
identical to CC. Common to all of the above-mentioned licences is that they expect the user to
acknowledge the source of the information by including an attribution statement specifying the
information provider.
4. PROBLEMS
4.1. Malware
Along with the growth of the Internet (currently approx. 40% of the world population already has an
Internet connection [Internet Users (2014)]), the misuse of data available on the Internet has also grown.
The Independent IT Security Institute AV-TEST registers over 390,000 new malicious programs every
day; in 2014, 140000000 new malware items were discovered [Malware Statistics 2015]. The annual
damage to the global economy from cyber crime in 2014 is estimated to be 445 USD [Net Losses:
Estimating the Global Cost of Cybercrime]. This is already a measurable part of the GDP of many
developed countries, e.g. 1.6% of the GDP of Germany, 1.5% of the GDP of the Netherlands and greater
than the GDP of many other countries. The actual damage may be substantially higher, since online
crime costs are hard to measure - companies, banks, and governments often do not report hacking or the
reports are rather ambiguous.
Malware growth is far more rapid than change in any other Internet statistics. According to the
McAffe Labs report, 387 new threats appear every minute [McAffee 2015]. And this is only the visible part
of the iceberg - the established anti-virus (AV) products are rather weak protection against constant and
rapidly increasing threats. According to a recent report from the threat protection company Damballa
[Damballa 2014], only 4% of the almost 17,000 weekly malware alerts are investigated. Inside the first
hour of submission, AV products missed nearly 70% of malware, only 66% were identified after 24 hours,
72% after a full week, and it took more than six months for AV products to create signatures for 100% of
the malicious files used in the study.
3
Internet Users (10⁹)
Malware detected (10⁸)
2
1
0
2004 2009 2014
Fig 2. Growth of number of Internet users and detected malware. The exponential growth of new malware guarantees that soon
there will be something for every Internet user.
3:22 • H. Jaakkola, J. Henno and J. Soini
Fig. 3. Percentage of detected malware after hours of discovery. Malware completes the main part of its malicious action in the first
thirty minutes after the beginning of the infection [Filiol2005], but probability of its detection in this time is less than 10%.
4.2. Personal Privacy
When you visit some Internet site to get some information, the site also gains some information about
you: which web page you came from, which type of browser you are using, and your geographic location.
But people often voluntarily expose themselves in some sites much more – who their friends are, what
they like, where they have been recently, etc. They assume that this data remains just with this site and
often even forget what personal data items they have exposed and where.
However, these items of personal data are valuable for advertisers and spammers and have created a
whole new industry of collecting and marketing personal data. As a result, it has become very easy to
compile presentations about privacy and security on the Internet. Just declare “there is no such thing
anymore.”
There are many examples. For instance, Twitter is currently planning to put trillions of tweets up for
sale to data miners [The Guardian, March 2015]; nobody knows what will be revealed from this big bag of
data.
Big international companies often consider that they own every piece of data they get and can handle
the data just how they like, e.g. expose everything to the United States National Security Agency (NSA)
surveillance program PRISM [PRISM], which collects the Internet communications of foreign nationals at
several major US companies operating in other countries: Facebook, Apple, Google, Yahoo, Skype,
Microsoft. When subsidiaries of these companies are registered in Europe they should also obey European
laws. Under EU law, such data export to a third country is legal only if the exporting company can ensure
adequate protection for such data, but NSA‟s PRISM program and other forms of US surveillance are the
exact opposite of adequate protection. In April 2015, Facebook will be challenged by 25000 users in a
Viennese Court on violation of European privacy laws [European Court of Justice 2015].
All data will sometimes become obsolete, but even obsolete data can sometimes present a threat to
privacy. Facebook ended its e-mail service at the beginning of 2014 [BBC News 2014], thus currently
Facebook e-mail addresses are obsolete. However, on March 20, 2015,a list containing 1642 Facebook
users‟ e-mail addresses was released on an open Internet site. All of them are in standard form
Firstname.Lastname@facebook.com or use some very similar syntax (FirstnameLastname@...), which
totally exposes the real name. Unfortunately, this syntax is currently the mandatory standard in many
organizations; gone are the days when you could use the address jaak@... – far more homely and revealing
far less information about your real identity – where the family name is not present.
Taking at random some names from this list and making a Google query returned several websites
(Instant PeopleFinders, Whitepages, Spokeoetc) where additional and often very detailed information
(even without logging in and paying) were presented, e.g.
Report Includes Available Information on:*****
2 matches for *****
Data Driven Ecosystem – Perspectives and Problems • 3:23
Current Address:…
Friends / Family:…
Phone Numbers:…
Online Sellers:…
Email Address:…
Internet Dates:…
Marital Status:…
Old Classmates:…
Location History:…
Scammers:…
Family Members:…
New Roommates:…
This information was free, but for $0.85, the site promised to reveal much more.
The first line of the posting containing the list of Facebook addresses was:
“Use for Spam and if you want more msg me....”
Thus this individual knew exactly what s/he was doing - this was just a demonstration of hacking
skills in order to get new customers.
Lists of e-mails are published on some sites almost daily, and it is very easy to find more such lists of e-
mail addresses – just set up a crawler (using tutorials like [makeuseof 2015]) to search for some properly
formatted regular expression, e.g.
[ \t:=”„]+4[0-9]{12}(?:[0-9]{3})?
There are sites [e.g. LeakedIn] which provide such lists “just for lulz” (the plural of lol – “laugh out
loud" [The Urban Dictionary 2015]).
4.3. New customs
The old generation of digital immigrants [Prensky 2001]watched cinema pictures. How very „out‟! The
new brave generation of digital natives, „internauts‟, instead play videogames 24/7 [WorldStar 2015] or
stream their playing to others to watch on Twitch [Twitch 2015] – the modern incarnation of cinema and
TV.
The old generation celebrate birthdays, marriages, births – events which have for us a deep emotional
meaning. The new brave generation also have emotional events, but different. For instance, it is very
important to increase the number of followers, collect „likes‟ (who clicked ‟like‟ or did something similar on
your webpage) and sub/resubs (the analog of likes on Twitch). And if the number of followers/likes/resubs
hits some round number, it is cause for celebration. On March 21, the following was pasted on Pastebin:
“Hello everyone and welcome to my 100k Special stream. Hitting 100k Followers is not a small
milestone and I wanted to do something crazy for it as thanks for all the support you all have shown me
during my time here on Twitch/Youtube.
… I will be streaming for 1 second for every single follower which is 100,000 seconds or 27.7 hours …
every single Sub/Re-sub that happens will add 30 seconds to the total remaining time”
This is followed by the list of games (8) which will be streamed.
4.4. Who has will be given more
The Bible is a wise book – a collection of human experience from many centuries. It emphasizes some
principles which are considered important for several occasions:
Matthew 13:12. Whoever has will be given more, and they will have an abundance. Whoever does not
have, even what they have will be taken from them.
Matthew 25:29: For whoever has will be given more, and they will have an abundance. Whoever does not
have, even what they have will be taken from them. …
Mark 4:25:For he that has, to him shall be given:
Luke 8:18: …. Whoever has will be given more; whoever does not have, even what they think they have
will be taken from them."
etc.
3:24 • H. Jaakkola, J. Henno and J. Soini
While the creators/authors of the Bible had to introduce these truths from the historical experience of
mankind, nowadays they can be proved.
Consider two computers (black boxes – nothing is known about their structure/functioning), which are
connected.
Fig. 4. Connected black boxes; one of them has far more memory.
The boxes exchange messages and store the received responses.
Since they are finite, their number of states is finite and sometimes they go into cycle, start repeating
states; repeating states also occurs if some mechanism resets one/both of boxes to some initial state.
Obviously, cycling happens first with the box that has less memory. Thus the box with more memory can
successfully store all the responses from its little brother and when the little one starts repeating itself, it
is concurred? - the big one knows exactly what the responses from the little one will be, so it can use its
little brother however it likes. Instead of two black boxes, there is now only one - but with more
capabilities, as the big one has the little one as a slave. To quote from Matthew, „Whoever has will be
given more, and they will have an abundance.‟ „Whoever does not have, even what they have will be taken
from them.‟ This situation has been considered by mathematicians in several papers. As long ago as 1973
the following result was proven [Trakhtenbrot & Bardzdin 1973]:
If the size of the input alphabet of an automaton (black box) W is m and the size of the output
alphabet - n , then for any natural number k one can effectively construct an input word d ( k ) of length
| d(k) |]4k 2 (ln nk )m2 k [ which residually distinguishes all automata with k states, i.e. any two
automata with k states after getting this input either produce different outputs (they are recognized to be
different) or the automata will afterwards act the same way. Since there is only a small number (length is
small-power polynomial) of such words, it follows that if automaton W is connected to another
automaton M1 with more memory and encoded to search the distinguishing word for M (with number of
states c1*| d (k ) | c2 , where constant c1 depends on the encoding of words of length | d(k) | , constant c2 -
encoding of search algorithm), automaton M1 can analyze the behavior of automaton M , i.e. make M
do everything that M1 wants. For the case where an upper boundary on the number of states is not
known, a polynomial-time probabilistic inference procedure is described in [Rivest & Shappiro 1994].
The coming age of 'Internet of Devices' will be characterized by an increasing number of Internet
connected devices with rather little memory - perfect targets which are already being exploited [Goodman
2015].In 'real' C&C (Conquer and Command) in order to perform an attack, instead of one big computer, a
botnet is used - a network of Internet-connected communicating computers. Bots spread themselves from
computer to computer searching for vulnerable, unprotected computers to infect and when they find an
exposed computer, the machine is infected and then they report back to their master, staying invisible
themselves and waiting for further commands. There are always some unprotected computers, e.g.
gamers sometimes deliberately disable virus control in order to speed up gameplay. A hacker test in 2012
[Internet Census 2012] found over a million routers that were accessible worldwide. Botnets may have a
few hundred or hundreds of thousands of “zombies” infected without their owners' knowledge at their
disposal. Botnet creation is 'ridiculously easy' [readwrite 2013, darkreading 2014], but if you do not bother
with such activity, you can rent the services of many businesses that operate almost openly or buy an
executable program. And if you search, you may find somewhere a code for building a botnet or virus, e.g.
code for one of the most sophisticated pieces of malware - Stuxnet - is now freely available in GitHub
[Laboratory B 2014].
Data Driven Ecosystem – Perspectives and Problems • 3:25
Fig. 5. Example product from Web store (free to download): flooder - a trojan that allows an attacker to send a massive amount of
data to a specific target; user has to specify the victim‟s IP address, an open port, number of packets and click 'Start'. The web store
offers dozens of types of malware - viruses, trojans, scanners, keyloggers, botnets, etc.
4.5. Manage your technological identity
Our identity is determined by our relations with others. Previously, relationships with other members of
society were first of all physical. Gradually these physical relations have become replaced with relations
based on communication technologies: mail, newspapers, radio/TV; nowadays our most important
communication channel/media is the Internet. For many, increasingly their computer/laptop/iPad etc. has
become an essential part of their identity – they stare at the screens hoping to get some new
like/message/tweet/.. and some cannot even sleep without a mobile in their hand. And yet all the problems
with this increasingly important part of our identity are acknowledged painfully. The Internet already
influences the psychology of many people, who are constantly checking all their accounts, constantly
uploading selfies, constantly sending SMSs. They already live in this virtual world, not in our physical
world. When looking at the steady growth of Facebook, Twitter, Pinterest, etc.- the process is escalating.
Google has enough memory in its servers to „pwn‟ (to conquer to gain ownership [Urban Dictionary
2015a]) every single human memory. Google already understands (somewhat) natural language (queries
with full sentences provide better answers than queries containing only keywords) and is rapidly
improving its engine. Will we soon get all our truths from Google [ZDNet 2015], and is the whole Internet
a Botnet to C&C humanity?
5. CONCLUSIONS
The paper analyzed the essence of a data driven society and ecosystem. The starting point is the
phenomenon called hyperscalability. It points out the business value of data and its importance as a
source of new business and activities. Open data is seen as a meaningful source of business; in addition,
data that is not intended to be open is used for the same purposes. The challenges and threats related to it
were discussed.
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Damballa (2014) State of Infections Report Q4 2014. https://www.damballa.com/state-infections-report-q4-2014. Retrieved March
30th, 2015.
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