The advancement of technology has brought about massive change in the lives of people. These developments have greatly affected how they transact and behave online. Many of the activities that were conducted face-to-face have transformed in the virtual world. More and more people have built comprehensive online profiles for them to shop, bank, and connect with friends to the point that they have created a Virtual Identity or Persona of themselves.

An individual’s Virtual Persona allows them to access their credit status, bank balances, engage in gaming, socializing, dating, blogging, etc. This makes your Virtual Identity of immense value to organizations and people. Your online behaviour indicates your buying patterns; your social and financial status attracts certain people who want to befriend you.

Virtual Persona has real value and certain entities may want access it and impersonate in the virtual world. Data derived from the virtual persona has become a source of profiteering legally and illegally. The widespread proliferation of illegal and unrestricted use of private information necessitates the need for effective online Identity Management to create a safe online environment for ecommerce and Internet usage as a whole (Smedinghoff, 2011).

People need to understand that in the virtual world, their online identities have immense value. Earlier, people stored their identity cards in their wallets. Now these are stored online – whether it is your social, legal or financial profile. This means, your Virtual Identity can potentially be stolen electronically. Even something as harmless as online gaming is subject to the same threats. Games such as “World of Warcraft” are termed Massively Multiplayer Online Role-Playing Game (MMORPG) as it engages a huge number of users. The “World of Warcraft” holds the Guinness World Records for the largest monthly subscribers of 11.6 million (Mitchell, 2009). The other most played MMORPG include Final Fantasy, The Elder Scrolls Online, Guild Wars 2, Blade & Soul, Black Desert Online, RuneScape, EVE Online and Star Wars (IG Critic, 2016). Various Augmented Reality games, Pokémon Go for example, also are gaining popularity. Such virtual communities are not immune to cyber attacks.

This paper explores the subject of Virtual Identity, the risk and opportunities of losing them to cyber theft. It reports on how organizations, legally and illegally, are analysing your Virtual Persona and what it could mean to losing accessing your Virtual Identity. The paper focuses on Virtual Reality (VR), Augmented Reality (AR), Analytical Tools and services available to analyse Virtual Identities.


Virtual Reality (VR) describes the world that exists in our minds when we are interacting online. It is the computer-generated artificial environment that users can interact with (Biocca & Levy, 1995). This artificial environment can be experienced via stimuli as sounds and sights afforded by a computer. Virtual Identities are created in VR and represent users in the video games, chat rooms, virtual common space or any other similar environments. These identities aimed at complementing various virtual spaces and platforms are simply referred to as “Avatars” (Morgan, 2009). An Avatar includes a representative video content or image, a profile, a name, or a “handle” that offers more information about an individual’s Virtual Identities.

People create virtue identities by creating virtual representatives of themselves (Rheingold, 1991). In online games, the individual’s Virtual Identity may be part of their identity but may differ from their own identity. In other spaces such as Basecamp, Virtual Identities may be less creatively oriented and represent the user’s actual physical identity, where the user uses their own image or name for an Avatar (Witmer & Singer, 1998).

These virtual platforms pose special risks to users, as they are hubs for Cybercriminals. This occurs because VR technology is built upon existing platforms (Lanier, 1992). As such, it offers little new attack opportunity. At the highest level, VR is largely a new input and display mechanism added to the traditional devices. The technology is powered with underlying computers (whether a mobile, personal computer or console device) that have not really changed much. However, VR facilitates positional and orientation tracking. Physical body movements are tracked. The comprehensive behaviour tracking can be quantified to understand preferences, divert the user’s attention and even sell things (Rubin, 2016). Perhaps, the risk posed by it is not any greater than any other device or software that the user may add to his or her computer.

Today, the use of VR in gaming provides users with a fantasy world that is disconnected from reality. This way, it offers the opportunity to the identity thieves to attack VR and monetize such attacks via social engineering.

Finally, tracking data on online shopping facilitated through VR may allow Cybercriminals to make dangerous attacks. Online shopping provides users with an entirely different VR experience. It allows users to browse items online and even try these items on the Avatar. Unfortunately, the program used can identify a person’s debit card or credit card and Cybercriminals can capture and sell this information.

A Cybercriminal can also use VR/ AR headsets tracker such as web-coding tricks to find valuable information of the user, monitor mouse clicks and movements and use this data in recreating the user actions in a similar way one could mimic the manual pin entry (Fox, Arena, & Bailenson, 2009).


Augmented Reality (AR) describes a series of technologies (i.e., Head-Mounted Displays (HMDs)) that makes it possible for the real-time mixing of content generated via computer with video display (Azuma R. T., 1997). It is used to integrate virtual information into the physical environment of a person making it possible for them to perceive it as existing in their environment (Janin, Mizell, & Caudell, 1993). Its functioning is based on the techniques that was developed in VR and interacts with the virtual world. AR technologies are defined by the following features: (1) interactive in real-time; (2) combining virtual and real; and (3) registered in 3D (Azuma, Baillot, Behringer, Feiner, Julier, & MacIntyre, 2001). This means that these technologies are registered in 3D and interact in real-time. This ensures accurate registration and tracking to ensure the user obtains a believable image. As such, the three key building blocks of AR systems are real-time rendering, display technology and tracking and registration (de Sa & Churchill, 2012).

New mobile wearable computing applications supporting AR functionality are increasingly become possible with the decrease in size and increase in the power of computers making it possible for users to access online services everywhere and always. This flexibility allows applications that enable users to exploit the surrounding context. This AR presents a powerful User Interface (UI) to context aware computing environments (Mekni & Lemieu, 2013). Currently, AR exists in consumer products including Microsoft’s HoloLens, Google Glass, Apple’s iPhone X, Samsung Pixie and games such as Pokémon Go.

AR devices may be prone to attacks and lead to identity theft. For instance, a Cybercriminal using Social Engineering and 3D models can alter and create fake videos and games. Computer scientists and animators have already succeeded in creating the techniques to take the voice recording of a person and make them say something they didn’t. They can give a person different lip movements and expressions by altering the person’s video. This can be achieved by way of tracking a history of movement of a person in VR. While these fake videos are yet to be perfected on, it demonstrates how accurate 3D models and VR tracking could change things. The individual’s unique identifiers could be their physical or verbal “ticks” or unique movements. If compromised, Cybercriminals can use these personal intricacies to digitally impersonate a user or to socially engineer one’s friends (Shatte, Holdsworth, & Lee, 2014).

AR technology was developed over forty years back. Pokémon Go just made AR mainstream. Cybercriminals see AR as an opportunity to execute their malicious intents, and have already seized the opportunity of the popularity of games and various other applications to execute their malicious intents (Zhou, Duh, & Billinghurst, 2008). They have succeeded in creating Windows ransomware, SMS spam, scareware apps, lockscreen apps and apps for purpose of executing their malicious intents. They use fake Windows-based Pokémon Go Bot to attack the users of Pokémon Go Bot. This Pokémon Go Bot application levels the account of the user with little effort by mimicking the role of a fake Pokémon trainer (Paz, 2016).

People are also exploiting Pokémon Go to spread malware to the AR game via bogus guides (Tynan, 2017). Augmented wearable technology pose a serious risk as images in the field of view of a person could be manipulated. These Cybercriminals essentially substitute real virtual objects with fake virtual objects. These AR Cybercriminals could also reinvent a new version of ransomware, which could be used for malicious purposes. By using this new breed of ransomware, these Cybercriminals could make a Doctor who is using Microsoft HoloLens to lose control of it or to pay ransoms. Cybercriminals can also use AR devices to collect personal health data and biometric data and use it for malicious intentions (Boyajian, 2017).


The online technology has generated huge amount of data from video streaming, social media activities, online game playing and browsing in the Internet. These data are accumulating day by day from various sources, through different methods of inputting via different technologies. These data accumulated are called as “Big Data” which is considered to be broad, fast and voluminous. It is either structured or unstructured, but still useful to derive data sets and subsets to sell and utilize by online and non-online companies for increasing market coverage and profits (Tiwarkhede & Kakde, 2015).

Companies engaging in analytic services record and then sell online profiles like user/ screen names, email addresses, web site addresses, interests, preferences, home addresses, professional history, and the number of friends or followers an online user has. There are also companies who gather and synthesize data on the tweets, posts, comments, likes, shares, and recommendations of the user in his social media accounts (Beckett, 2012).

Analytic service and online data industry is reported to be a $300 billion-a-year industry, employing around 3 million people in the United States alone (Morris & Lavandera, 2012). There are a lot of successful companies that provide analytical services and data brokering. These companies, supposedly, know more about you than Google. The list includes Acxiom, Corelogic, Datalogix, eBureau, ID Analytics, Intelius, PeekYou, Rapleaf, and Recorded Future (Mirani & Nisen, 2014). What they do is look into online personal profiles of the users, gathering information like names, friends, activities and interests of those personal profiles and selling them to end users for advertising, marketing and other legitimate economic activities. Basically, it collects information like contact detail, interests, preferences and demographics, then aggregating those information gathered based on a subset needed or applicable to its clients. Acxiom alone has recorded over a billion dollar in revenue for its analytical services involving 144 million US households (Morris & Lavandera, 2012).

Data brokers are intelligent in gathering data and know how to use it. They take advantage of the vast data available online in order to deliver relevant services to users, suggest products and services that the users might need or subliminally suggesting that they need it. These companies claim that all the information gathered and sold is legal, secure and suitable for the users. Data brokers cater to different customers that can range from small enterprises to large Fortune 500 companies (Morris & Lavandera, 2012).

Data brokers source their information from a variety of places. For example, Facebook, Google and other free apps are collecting your data and selling it to those who are willing to pay for it. And then there are Cybercriminals who steal this information and sell on the dark net.

It is scary to think what damage a cyber attack on data aggregators could do. In September 2017, Equifax reported a massive data breach. Initially reported as affective 143 million people, the estimate was revised to 145.5 million later. Cybercriminals accessed consumer’s highly sensitive personal and financial information including names, birthdates, addresses and credit card numbers (Hackett, 2017).


The cost of virtual persona of a user is priced depending on its legality, usage and the purpose of its application. Bank details, credit history and the availability of personal documents like driver’s license are seen as high value. Financial Times has presented a calculator to show what each bit of your personal information is worth (Steel, Locke, Cadman, & Freese, 2013). The more is revealed about your real and virtual behaviour, the more valuable your information is. And consider the fact that this information is constantly traded and resold to multiple buyers. It is not difficult to imagine that over the course of your lifetime (or afterlife) your persona may be worth 500 million Euros.

In almost all of the cases the owner of such personal information does not receive the income, or even a tiny share of it, from the revenues generated by the analytics service providers who sell this to willing buyers. The owner themselves are facing risk of breach in security when their information is leaked to undesirable elements who will use their identity to commit fraudulent and criminal activities, leaving them liable for credit fraud or for the unpaid loan that they did not apply for in the first place. The real owner of the personal data faces the burden of proving his/ her innocence.

AR and VR devices are highly complex and relatively new. They are vulnerable and attractive to Cybercriminals looking for the weakest link. Some argue that Cybersecurity’s weakest link are the organization’s own employees (Banham, 2017). Social engineering, as it is also known, is where Cybercriminals deceive their victims and gain their trust. Once the Cybercriminal gains entry, the best protective software turns useless. Therefore, organizations need to invest in on-going Cybersecurity awareness for their employees.

Does it make sense to blame people who are the value creators in organizations? Shouldn’t technical systems be built for normal people rather than techies building systems for techies?


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The Profile Of A Cybercriminal



Profiling is a technique or approach for solving crime. Some scientist define it as a forensic technique used by forensic investigators and law enforcement agencies to understand why criminals are committing crime, to classify criminal behavior and to solve crimes that have already been committed (Saroha, 2014). Others view it as a tool used by forensic experts to identify the offender’s behavioral tendencies, personality traits, demographic variables, and geographical variables based on the information and characteristics of the crime (Lickiewicz, 2011). However, the general consensus is that criminal profiling involves collecting inferences about the traits of the individual responsible for the series of crime or for a particular crime. It involves understanding what a particular crime says about the perpetrator (Kirwan, & Power, 2013). It is used by forensic investigators and law enforcement agencies to understand and apprehend criminal offenders. As a forensic technique, criminal profiling enables investigative agencies to use the specific information to focus their attention on people with personality traits that parallel those of other offenders who have committed other similar offences (Kirwan, & Power, 2013). Integrating the sciences and the arts, criminal profiling allows investigators to analyze victims and crime scene and comparing them to similar crimes committed by known offenders’ personalities and traits. From this, the criminal profiler can predict the unknown offender’s characteristics including sex, age, and level of mental stability, geographical location and motivation (Lickiewicz, 2011). The investigators can also link other offences committed by the offender from the offender’s signature and modus operandi identified from the physical evidence collected at the setting where the crime occurred and scene of crime (Saroha, 2014). As such, criminal profiling contains information about the perpetrators (Kirwan, 2011):

  • Likely demographics (i.e., gender and age)
  • Legal history including history of prior criminal convictions/offenses and any antecedence
  • Vocational backgrounds that is the work the perpetrator is likely to be involved in, if any
  • Social interests and habits (hobbies, sports, and other interests in which the perpetrator may have)
  • Family characteristics including the offender’s family background
  • Various personality characteristics including the offender’s appearance, demeanor etc
  • Mode of transport (i.e., type of vehicle that they offender may have)

In essence, criminal profiling is primarily based on the assertion that the format in which the offender committed the offence reflects his or her behavior and personality.

Modern criminal profiling takes two forms: the deductive and inductive approaches. He former is evidence-based involving analyzing the evidence found from the case in order to construct the offender’s behavioral profile. This way, the offender’s profile is constructed based on the evidences and information found at the crime scene (Kirwan, 2011). Professionals use this approach to get into the mind of the criminal. They try to think in the same way the offender may have thought whiling committing the crime. This type of criminal profiling is largely based on human intelligence rather than on statistical data. The later type of profiling uses the statistical analysis of the previous offender’s characteristics to generate a generalized behavioral pattern of the perpetrator. Comparative and statistical analyses are used to create the profile of the criminal. Information comes from results of studies of previously convicted criminals, their interviews, observation, data from official databases, and the usage of clinical methods. The profiler analyzes all these information and constructs a possible profile of the likely offender of the type of crime basing on the traits of criminals that committed similar types of crimes. The inductive technique is basically based on the inductive logic, which forms the basis of narrowing down and predicting who will commit specific types of crimes (Halder, & Jaishankar, 2011).

In addition to the offender’s biological information; it is worth noting that criminal profiles include information about the perpetrator’s residence and approximate location. This information is the product of geographic profiling. Regardless of the type of criminal profiling approach employed, criminal profiling alone can never solve crimes alone (Long, 2012).

Discerning the motivations for committing a particular cyber-crime is important as it helps the forensic expert to build a useful profile for the offender. It is suggested that people may be motivated by different factors to break the law. Based on the perpetrator’s motives, criminals can be categorized into two: criminals whose act of using the internet to commit crime is incidental; and criminals who intentionally and knowingly use the internet to commit crime. Criminals who knowingly use the internet to commit crime include white-collar criminals, hackers, computer con artists, network attackers and crackers (Long, 2012). The second type of criminals use the computer to keep record, use the network to identify and find victims, and those who use e-mail and other services to communicate with their accomplices. The motivations offered by cyber-criminal for their activity seems to be largely influenced by their sensitivity towards agendas raised by various groups to oppose hacking. For example, the computer security industry has been accused of over-emphasizing the pathological aspect of hacking and vandal-oriented motivations. The motivation behind the hacker participation in hacking can be categorized into six: peer recognition, enjoying feelings of power, the urge of curiosity, the feelings of addiction, boredom with education system, and political acts (Long, 2012). For some criminals, they are motivated to do the forbidden act while for others, crime offers them the opportunity to manipulate and control others. Most criminals committing crime in the cyber space are strongly motivated with their motivation ranging from simply want to have fun to the desire or need for emotional or sexual impulse, money, political motives, or compulsions caused by psychiatric conditions of mental illness (Long, 2012). On the other hand, some cybercriminals are driven by less noble motives such as lust, desperation, anger, or plain boredom. It is important to discern motives and motivations for committing a particular crime as forms an important part of creating a useful profile (Schinder, 2010).

Because of the influence of Hollywood and the untypical nature of crime today; there are many stereotypes on how cybercriminals appear. Some of the stereotypes include that all cybercriminals (1) are socially inept but bright; (2) have a great technical skills and knowledge and very high IQs; (3) are males and usually boys; (4) teenage boys with computers and dangerous criminals, and (5) all cybercriminals are never violent. According to Lickiewicz (2011) when creating a profile for cybercriminals, a law enforcement official should always begin with generalities that are identified and typical of cybercriminals. According to Lickiewicz (2011) for an individual to commit a cyber-crime, he or she should have the ability to perform basic tasks on the internet. Some crimes also require greater computer skill and knowledge. These types of criminals are same as those who commit crime in the physical world. They do not believe and respect the law. They believe that some laws should be broken because they are unreasonable. Many of these criminals use the internet to fulfill their fantasies. They use it to build new identities and to play other people’s role. Cybercriminals often use more energy than they get in return (Kirwan, 2011).

Understanding the motives of the criminals is also important because in many jurisdictions, one of the elements of providing that an accused individual is guilt is by showing that he or she posses each of the crime triangle: motive, the opportunity, and the means. The motive is the perpetrator’s reason for committing a crime (Atkinson, & Walker, 2015). The means is the perpetrator’s way of committing a crime. The opportunity is the offender being at the scene at the right time to enable him commits a crime. Therefore, understating the motive of the criminal in an investigation is useful for two reasons: (1) when creating the offender’s profile to help in the identification of the correct perpetrator; and (2) when presenting a case against the suspect. Common motives for criminals committing cybercrimes include: sexual impulses, political motives, monetary profit, just for fun, revenge, anger, and other emotional needs, and serious psychiatric illness (Atkinson, & Walker, 2015). These characteristics should be used when profiling cybercriminals. Every message, every word and every trace is important when creating criminal profile.


It is clear from this paper, that criminal profiling means a lot to the investigators. It allows investigators to link motive, character, act and behavior of the offender. Although it primarily focuses on serial violent offenses such as sexual assaults and murders, the changes in technology has increased the emphasis and interest on applying it to cybercrime. Most cybercrimes are by nature serial in that the offender habituates their behavior and commit multiple offenses. From this, signature and modus operandi can be drawn. For example, analysis of indicators of the attack’s “digital crime scene” can determine the computer hacker’s intrusion activity and provide them with an insight. As such, it is an important method when it comes to classifying criminal investigations.

When an investigator uses profiling as the method to solve a criminal case; it is always important to see the scene of crime, find traces, and evidence that a criminal leaves at the crime scene. This way, the profiler can make good profiler of the offender.


Atkinson, S., & Walker, C. (2015). Psychology and the hacker – Psychological Incident. SANS Institute InfoSec Reading Room.

Halder, D., & Jaishankar, K. (2011), Cyber crime and the victimization of women: laws, rights and regulations, Information Science Reference.

Kirwan G (2011). The Psychology of Cyber Crime: Concepts and Principles. IGI Global.

Kirwan, G., & Power, A. (2013). Cybercrime: Psychology of cybercrime. Dublin: Dun Laoghaire Institute of Art, Design and Technology.

Lickiewicz, J. (2011). Cyber Crime psychology-proposal of an offender psychological profile. Problems of forensic sciences, 2(3): 239-252.

Long, L. (2012). Profiling Hackers. SANS Institute. Retrieved on 8th July 2016 from

Saroha, R. (2014). Profiling a Cyber Criminal. International Journal of Information and Computation Technology, 4(3): 253-258.

Schinder, D. (2010). Profiling and categorizing cybercriminals. Tech Republic Retrieved on 8 th July 2016 from

Tompsett, E.C., Marshall, A.M., & Semmens, C.N. (2005). Cyberprofiling: Offender Profiling and Geographic Profiling of Crime on the Internet. Computer Network Forensics Research Workshop.

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