Crime and the Media

Cybercrime refers to illegal activity through the computer for illegal purposes. These cybercrime activities refer to any type of hacking and or criminal activities such as the creation of computer viruses to hack the details, online theft, bullying, terrorism, and so on. Cyber-crimes are executed by penetrating the computer safety and security. Cybercrime is a new phenomenon but is popular and has achieved attention globally (Marcum and Higgins 2019). Cybercrime promotes criminal activities which can be either cyber-dependent or cyber-enabled (McGuire and Dowling 2013). There are various types of malicious software and viruses that hack network resources, accounts, and so on. Mostly the cybercriminals commit cyber-crime to make money easily. It can be committed by an individual or any entity, for example, any company who runs a scam campaign or has access to deep web or dark web illegally. Other reason can be political or public. The trending types of cyber-crime are email fraud, financial theft, credit card data, demanding money by blackmailing through the internet, criminal activities or to promote terrorism. Cybercrime use malware to delete or steal data. After the adoption of computer technology, internet cyber-crime has become popular among the youth. New crimes and criminal opportunities have been created by the introduction of new technology. Cybercrime is the world of various activities which can breach or penetrate the personal and professional details or documents illegally to blackmail an individual or any group (Ajayi 2015). The effects of cybercrime are different on different identities. Cybercriminals generally work on the dark web which is the most popular in cyber-crime. It cannot be accessed through any normal browser but needs a special browser called tor browser (Almaatouq 2014). This essay aims to find out all the key problems faced by the researchers while studying the cybercrime and to conclude the research objectives.

Cybercrime researchers face several challenges when trying to study online. Intelligence gathering is the first challenge faced by the researchers (Chen 2012). Intelligence gathering involves the process in which data is collected by the public and private mediums and other intelligence purposes. The data can be collected through social media platforms like Facebook, E-mail, Twitter, Whatsapp, and so on. In this digital world, everything is connected digitally. Companies need to secure their important data. However, a lot of research has been done by the researchers in context to threats and vulnerabilities to minimize the illegal use of social media sites (Hunton 2012). The data collected by open-source intelligence is usually used for research purposes, but do not contain exact numbers. Today, the social media platforms such as Facebook and Twitter have become a platform from where the data can be gathered for intelligence testing. These open sources can help in gathering intelligence but may not be an accurate form of the details.

The second challenge is to analyse the cybercriminals as it is very an important element which helps in the analysis of the criminal activities to complete the research (Nykodym 2005). Every criminal has a different motive, perception, and behaviour. It is a complex task for the researchers to investigate between the email harvesters and other spammers. The analysis is based on the behaviour of the measurements which can be correct and also incorrect. Here, the limitation of work increases as there are no exact figures provided for the research. Due to this, the right figures cannot be calculated and researchers have to measure the incorrect values. As per Almaatouq et al. (2016), these values can be characterized by real accounts and fraud accounts. Researchers have to analyse the account properties along with their social interactions to get the correct numbers for this research (Yar and Steinmetz 2019). Data-mining is the first step taken by the researchers to identify criminal behaviour. However, this can be segmented into four types which are extraction, association, prediction, and visualization. It refers to the identity or the introduction of the personal details of any particular account like the person’s name and address which can be gathered by criminal records. The detected criminal details are matched by the database collected by the police to figure out the similarities between the two. As per Garg and Singh (2015), the communication used by these criminal communities is measured through various sources. The investigation or the research is the part of making the use of social network safe, to remove the criminal network from the sites and to provide medium to genuine users. However, the credit-card fraud list can be gathered by the hacker network and from other subgroups. The community detection technique helps in discovering the communities of the criminal network. Researchers have to manually calculate the details to figure out the criminal activities as they do not have any medium or software which can give them the exact figures. This is still not validated which means it is not sure if this discovery will be accurate to identify criminal networks or not. The Woolwich London attack was predicted through the reactions and comments on twitter which helped to measure the opinions related to the attack (Burnap et al. 2014).

The third challenge faced by the researcher is to gather the tools of intelligence that are used to analyse online crime and to have awareness (Nouh et al. 2019). These tools help to support law enforcement. A lot of discoveries and efforts has been made to develop the framework for the tools which can help to collect the web content. The first version of the dark web forum is released on the portal (Zhang et al. 2010). This Deep Web Forum Portal (DWFP) supports the functioning of the site and is also responsible to collect data through various online forums, browsing histories, multiple language selection, and visualization of different networks (Zhang et al. 2010). This data can be collected through the analysis of sentiments collected by the web-crawler to gather the content. Through this portal, several web pages can be generated through tagging and sentiment analysis. The content is segmented into two parts neutral and sentimental. For example, news sources can be referred as neutral content and on the other hand, the content related to terrorism and other weak sentiments can be referred as sentimental content (Burnap et al. 2014). The Terrorism and Extremism Network Extractor (TENE) is a source through which the information and details of the extremist activities are collected by using online portals which also helps to differentiate between the specific website dedicated to extremist activities and other related websites (Akhgar 2016). The hacker always starts with penetrating the webpage and then analyse the content through different links available in the page. These data-mining techniques help to identify the entities and the objects related to the social network analysis which helps to study the relation for the research. The data can also be retrieved from the crime incident reports or to discover the criminal-networks that helps in analysing and visualizing. The research is limited to the analysis of the criminals and not the people or entities, for example, certain places or weapon names which should be visible while research as through finding these names many unknown and unidentified activities of criminals can be released. Many of the tool kits provide access to analyse the digital personas in cybercrime investigations whose work is to create the network first and then to analyse the criminals.

The fourth challenge faced by the researcher is the increased quantity of the work as the reports related to cybercrime is increasing day by day (Ashcroft 2015). It is very tough to identify the exact number of reports and crime. The online reporting network receives a lot of complaints every day regarding cybercrime. The imbalance between the reports and the exact numbers are almost impossible to match with each other. Due to this the workload of cyber experts has also increased. Thus, it is also very tough for the researcher to find out the exact numbers to prepare the research (Al-Khaleel 2014). The public is reporting the complaints related to cybercrime in hundreds and thousands daily (Sarvari et al. 2014). Therefore, the pressure of maintaining the records has also increased. While communicating with cyber experts, the researchers came to know that the workload of cyber experts has increased as compared to the past 10 or 20 years (Early 2010). A different department and a complete office or specialised cell have been formed for the cyber experts so that they can do their work without any disturbance. These experts are responsible to analyse the cybercrime data and to investigate the victim's complaint but due to the fewer details, available researchers do not have any exact details that could reduce the cybercrime rates. The complaints are increasing but we do not have resources through which we could analyse it. To find out the resources is a great challenge for the researchers as they do not have any genuine resource which can help them to investigate the number of crimes (Senjo 2014). There are techniques and equipments related to cybercrime which are still new for the investigators. The investigators for the cybercrime are very less as compared to the rising cases. Due to this they have a lot of work and do not have time to help the researchers to find their answers. The cybercrime cases are increasing day by day and the authorities are handling other crime cases as they do not have any proper training to handle cybercrime (Edward, Rashid, and Rayson 2015).

The fifth challenge faced by the researcher is a short supply of skills (Hunton 2011). As cybercrime has been given low importance to investigate because the resources are not sufficient which can help in controlling the increased cybercrime in the nation. Many times the researcher's data does not match with the data of cyber-police due to rapidly changing numbers of cybercrime incidents witnessed daily. The challenges faced by cybercrime experts are increasing day by day as there are many new techniques introduced by the criminals to pursue crime. The staff must be trained by cyber experts who could help them to analyse criminals and their activities (Hunton 2011). They should also be given a good salary package as their working hours are more than other police authorities who handle other criminal cases. Better salary package and complete training will help the authorities to have good resources to reduce cybercrime (Ashcroft et al. 2015). The courses related to computer science, coding, criminality, and the internet can help to detect criminal activities. The officers or cybercrime expert needs to work with other police personnel to achieve success. The research done by the researcher is incomplete as it is very tough for them to take out the information in exact numbers as they do not find a genuine source which could help them in their research (Ashcroft 2015). There are a lot of agencies and companies who required cybercrime experts to protect their data.

It is also a challenge for the researchers to define cybercrime as it contains a lot of definitions and different researchers have different views on it (Gordon and Ford 2006). Several arguments have been done to identify the definition of cybercrime. Cybercrime is described as an international dimension which is responsible to transfer the illegal content through one country to another. This can be personal data or professional data and can also be related to the secret information of the country. All the countries need to come together to fight against the cybercrime activities as it can hamper everyone (Charitonidis Rashid, and Taylor 2015). Most of the cybercriminals depend on the computers and internet for their criminal activities. Researchers have tried to review the existing researches to gather the evidence but they come across multiple definitions as there are different investigations done by different researchers. The reason is the gap in analysing because a lot of data is not available. It is very important to analyse the collection and integration of the reports on which the research is based but because of the incomplete reports, the researchers have different views in dealing with cybercrime which does not give anyone correct idea of the dissemination (Harichandran 2016). The plan and the course of action of the researchers vary. To analyse the data is the medium through which the researchers can find the right answer along with the evidence but here both are missing due to the increasing numbers and fewer investigations (Mei and Frank 2015). Many people provide their feedback and their views on intelligence or also come with the questions. There are many reports and research that provides different understanding and analysing about the cybercriminals. On the other hand, very less information and investigation exist about cybercrime which focuses on understanding the process, challenges, and the enforcement of the law. The research related to cybercrime in result increase the challenges. There is a lot of scope of research but it could be only done after proper analysing but the common outcome of the researches is related to the training and awareness of the cybercrime for the cybercrime officials. The level of cybercrime and digital forensics is increasing with the development of digital devices. For example, as per Hunton (2011), the technical investigation should be increased and should add the policies in cybercrime investigations on different roles such as technical investigator, network investigator, forensic investigator, digital forensic investigator, technical expert, and so on. They are focussed and are well aware of the risks which are formed by cybercriminals. With this, the development of technical types of equipment, skills, and knowledge should be increased (Hunton 2011). According to Harichandran (2016), it is important to focus on the needs of cyber experts related to the techniques and types of equipment they need as the complete resources can help them to investigate. Surveys can help to collect the data from the students, workers, professors or people from different occupations (Harichandran 2016). The research can be also adopted by the police officials who investigate the cases related to cybercrime daily and respond to these offences. It is found that the cybercrime officials are responsible for handling the crime related to cyber and a lot of information can be collected in it but due to the busy schedule of the officers, they cannot provide the researchers with the detail of the cybercrimes as even they do not have the exact details, numbers or figures of it. Different researchers have different investigations and research according to the data they can collect but still do not have any accurate information or numbers because of the risings cases of cybercrime and the new techniques introduced by cybercriminals time to time. Senjo (2004) in his study performed a survey in which he tried to collect the details and reviews of the police officials regarding cybercrime and a majority of officials recognized cybercrime as a serious issue and even dangerous for the smart users. The study and the suggestions collected by the police officials were very much similar to the mass media and other stereotypes however the purpose of the reviews was only to collect the data through which the research can found a base (Senjo 2004). The advantage to collect data through reviews is that the researchers can achieve a large database of participants and reviews. However, there is also a disadvantage that there is always a reason behind the answer as they do not want the public to fear about the crime which is happening due to the advancements in the technology or are politically unable to answer the facts, and so on. Researchers are always in the process to achieve the information regarding cybercrime.

It is concluded that cybercrime is the most dangerous issue going on in the world. The reason behind calling cybercrime the most dangerous is because no or very less research is available for cybercrime investigation. Cybercrime refers to hacking the computers. Hacking is stealing of anything which is in or accessed by the computer, for example, passwords, locations access, access of webcam, network hacking, online theft (credit card theft), demanding money, blackmailing, promoting terrorism, planning terrorism, and so on. This all is done by the deep web or dark web which is mostly used by the cybercriminals. Mostly the cybercriminals hack the computers to steal money or for personal reasons. This is a new type of theft which is introduced after the computer and internet and very popular among youth. Many criminals find opportunities online to execute the crime and for this, they try to penetrate the system illegally which can also harm the system in various ways. There is a dedicated site called tor browser used by the criminals to execute cybercrime. Many of the challenges have faced by the researchers to research about cybercrime. The major challenge is the unavailability of the evidence as there are very fewer investigations available online. Even cybercrime investigators or police officials have fewer types of equipment and techniques so that they could fight with these crimes however in the meantime, new techniques have been introduced by the cybercriminals to pursue their criminal activities. Other challenges are intelligence gathering, analyse the cybercriminals and criminal activities, lack of intelligence tools and equipment, the quantity of work, and so on. The increased research and investigation need to be done regarding cybercrime as it would create awareness among everyone and we all could fight with it by having the right knowledge.

References for Nature and Extent of Cybercrime

Ajayi, E.F.G., 2016. The impact of cybercrimes on global trade and commerce. International Journal of Information Security and Cybercrime (IJISC)5(2), pp.31-50. http://dx.doi.org/10.2139/ssrn.2810782

Al-Khaleel, A., Bani-Salameh, D. and Al-Saleh, M.I., 2014. On the memory artifacts of the tor browser bundle. In The International Conference on Computing Technology and Information Management (ICCTIM) (p. 41). Society of Digital Information and Wireless Communication. P. 41.

Almaatouq, A., Shmueli, E., Nouh, M., Alabdulkareem, A., Singh, V.K., Alsaleh, M., Alarifi, A. and Alfaris, A., 2016. If it looks like a spammer and behaves like a spammer, it must be a spammer: analysis and detection of microblogging spam accounts. International Journal of Information Security15(5), pp.475-491.

Ashcroft, M., Fisher, A., Kaati, L., Omer, E. and Prucha, N., 2015. Detecting jihadist messages on twitter. In 2015 European Intelligence and Security Informatics Conference (pp. 161-164). IEEE.

Burnap, P., Williams, M.L., Sloan, L., Rana, O., Housley, W., Edwards, A., Knight, V., Procter, R. and Voss, A., 2014. Tweeting the terror: modelling the social media reaction to the Woolwich terrorist attack. Social Network Analysis and Mining4(1), p.206.

Charitonidis, C., Rashid, A. and Taylor, P.J., 2015, August. Weak signals as predictors of real-world phenomena in social media. In Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015 (pp. 864-871).

Chen, H., Chiang, R.H. and Storey, V.C., 2012. Business intelligence and analytics: From big data to big impact. MIS quarterly, pp.1165-1188.

Early, J.R. 2010. Cyber-bullying on Increase. [Online]. http://www.tmcnet.com/usubmit/2010/02/07/4609017.Htm [Accessed on 18th September 2020]

Gordon, S. and Ford, R., 2006. On the definition and classification of cybercrime. Journal in Computer Virology2(1), pp.13-20.

Harichandran, V.S., Breitinger, F., Baggili, I. and Marrington, A., 2016. A cyber forensics needs analysis survey: Revisiting the domain's needs a decade later. Computers & Security57, pp.1-13.

Hunton, P., 2011. The stages of cybercrime investigations: Bridging the gap between technology examination and law enforcement investigation. Computer Law & Security Review27(1), pp.61-67.

Hunton, P., 2012. Managing the technical resource capability of cybercrime investigation: a UK law enforcement perspective. Public Money & Management32(3), pp.225-232.

Hunton, Paul. Managing the technical resource capability of cybercrime

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Management, 32(3):225–232, 2012.

Marcum, C.D. and Higgins, G.E., 2019. Cybercrime. In Handbook on Crime and Deviance (pp. 459-475). Springer, Cham.

McGuire, M. and Dowling, S., 2013. Cybercrime: A review of the evidence. Summary of key findings and implications. Home Office Research report75.

Mei, J. and Frank, R., 2015. Sentiment crawling: Extremist content collection through a sentiment analysis guided web-crawler. In 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 1024-1027). IEEE.

Nouh, M., Nurse, J.R., Webb, H. and Goldsmith, M., 2019. Cybercrime investigators are users too! Understanding the socio-technical challenges faced by law enforcement. arXiv preprint arXiv:1902.06961.

Nykodym, N., Taylor, R. and Vilela, J., 2005. Criminal profiling and insider cybercrime. Computer Law & Security Review21(5), pp.408-414.

Sarvari, H., Abozinadah, E., Mbaziira, A. and Mccoy, D., 2014. Constructing and analyzing criminal networks. In 2014 IEEE Security and Privacy Workshops (pp. 84-91). IEEE.

Senjo, S.R., 2004. An analysis of computer-related crime: Comparing police officer perceptions with empirical data. Security Journal17(2), pp.55-71.

Singh, M. and Garg, N.K., 2015. Cybercrime: An unwanted call in computer system. Journal of Technological Advances and Scientific Research, 1(2), 45-51.

Yar, M. and Steinmetz, K.F., 2019. Cybercrime and society. SAGE Publications Limited.

Zhang, Y., Zeng, S., Huang, C.N., Fan, L., Yu, X., Dang, Y., Larson, C.A., Denning, D., Roberts, N. and Chen, H., 2010. Developing a dark web collection and infrastructure for computational and social sciences. In 2010 IEEE International Conference on Intelligence and Security Informatics (pp. 59-64). IEEE.

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