Digital Crime: Evolution, Detection And Prevention

Aim

Digital crime can be referred to as a criminal activity that is done over the internet using a computational device. Identity theft or unauthorized use of one’s personal data, phishing eavesdropping are few examples of cyber crime. The e crime survey reports of 2009 reveals that 41% of the digital crime cases indicated an increase in the technical sophistication of the attacks on their network. Furthermore, the report states that there is 45% increase in phishing target attacks on employees (Harrell and Langton 2013). These data proves that digital crime is increasing considerably over the years, as in this digital world, majority of the companies prefer to integrate their business operations to the internet. The virtual world has taken over the real one and with the increase use of e-business and e commerce, free flowing of information and ensuring its security is a major challenge (Hyman 2013). This challenge can be overcome by implementing proper detection and prevention methods. The report discusses the evolution of cybercrimes along with its detection and prevention.

The aim of this report is to –

1. a) Understand and analyze the evolution of cyber crime
2. b) Understand the need of proper e-crime detection methods
3. c) Evaluate the use of proper e-crime detection methods to prevent such attacks

Although it is difficult to determine when the first crime involving a computer took place, digital crime had been an issue over the years. Cyber crime or digital crime can be defined as an illegal or unauthorized behavior that involves automatic processing and transmission of data. There are mainly two types of computer threats, active threats and passive threats. Passive threat deals with silent data transmission and therefore it is difficult to detect. Passive threats on other hand involve modification or theft of confidential data and records from the system, and are easier to detect. With the evolution of digital crimes, there had been an increase in sophistication of the cyber crime prevention and detection techniques. The major objective of these detection systems is to detect any network anomaly and trace the source of attack (Rid and Buchanan 2015). Many organizations have been installing proper attack monitoring system in order to detect and eliminate a threat that can compromise the confidential data of the system.

Digital security is important as it provides the opportunity for the users in protecting their important information that is present on a network. It further helps in defending the computer system against various types of attacks that can create subsequent damage to a system. The list of cyber crimes is widespread and therefore, proper security measures are utmost essential. The different types of cyber crime illustrated in the following table-

Background

 
The above table demonstrates some of the cases of cyber crimes. Developing a world of information technology or incorporating information technology in daily business has a negative effect as well.  In order to maintain the confidentiality of the data and information, ensuring digital security with proper detection and prevention methods is important. Furthermore, with the evolution of sophistication of attack and changing of the attackers’ profile,

Figure 1: Representing the change in attackers profile

(Source: Sindhu and Meshram 2012)

Attacker or hackers are employing different exploits to target a system in order to infuse malware into the system. Researches prove that automated attacks throughout 2008 have resulted in an immeasurable number of website compromises. Furthermore, ScanSafe STST analysis on cyber crime occurrences reveals that there is a high degree of targeting involved with the today’s web malware. It is observed that there is an increasing number of cases of malware infection in the system employing ARP poisoning and man-in-the middle attack. Since the malware is highly configurable, the hackers are able to configure, launch and monitor and attack remotely, that becomes difficult to detect.  One of the major reasons for increase in cyber crime is the increasing use of internet. In 2011, more than one third of the world’s population has an access to internet.  Furthermore, over 60 per cent of all internet users are from developing countries with 45 cent of the internet users below the age of 25 (Grabosky 2014). Computer related crime is a long established phenomenon; however, the growth of the global connectivity is inseparably connected to contemporary cybercrime. Therefore, it can be said that cyber crime is a growing concern both domestically and internationally. Digital crime, thus us not a threat that can be curbed by compliance. The figure below illustrates the increase in cyber crime reports across the world-

Figure 2: Representing the rate of cyber complaints over the years

(Source: Grabosky 2014 )

Detection Methods

It is possible to detect cybercrimes with the help of different intrusion detection techniques. These techniques are elaborated below (Alazab et al. 2012)-

1. A software called tripwares can be used to detect a digital crime. This software take snapshots of the key stream characteristics that is used to detect critical file changes, thus providing evidence of electronic crime.
2. Configuration checking tools can be further used to detect an insecure system. It is generally used in detecting any suspicious patterns of system misconfiguration that can prove to be malicious.
3.  Honey pot lures is another digital crime detection technique that entraps a criminal by faking the presence of sensitive and confidential information in a system.
4. Anomaly detection system is another major cyber crime detection technique. It identifies and focuses on unusual patterns of activity such as unusual keystroke intervals, abnormal commands and unconventional program activities. These can provide certain evidences regarding the existence of electronic crime in a system (Raiyn 2014).
5. Another common intrusion detection system is the use of operating system commands. Use of certain operating system commands, such as checking the log files and comparing the output of the similar programs of the system can be used to search for evidences of possible electronic crimes (Deylami and Singh 2012).

Prevention Methods

The different preventive measures that can be taken in order to eliminate the risk of attack into the system are discussed below (Khan 2013)-

1. Use of firewalls into the system can help in prevention of digital crimes. Firewalls act as gatekeepers to a network from outside and prevent any foreign packet entering into the network.
2.  The system containing confidential data and information should be password protected in order to prevent any unauthorized use and access of the data.
3. The digital crime infused through viruses and malware can be prevented by using up to date antivirus in the information system (Rotich et al. 2014)
4. The confidential data should be properly encrypted in order to prevent unauthorized access (Deshmukh, Pasha and Qureshi 2013)
5. Finally, use of new or latest technology can help in protecting the security infrastructure of an organization. The system should be patched and updated time to time in order to prevent any digital threat creeping into the system.

Conclusion 

Therefore, from the above discussion, it can be concluded that there are several types of computer or digital crime that occurs over a cyber space. Proper methods and techniques are needed to be applied for minimizing the ill effects of the crime. The different types of digital crime that has evolved over the years include denial of service attacks, mail bombing, credit card fraud, software piracy, web store spoofing, viruses and malware. Designing or propagating any of those can be termed as a digital crime, which can further lead to criminal prosecution. The report discusses the major reasons for increase in cyber crimes over the years, one of which is increase in sophistication of attackers’ profile. The different risk mitigation and prevention techniques are discussed in the report. Latest technology can be put to work as a major preventive measure of digital crimes.

References 

Alazab, M., Venkatraman, S., Watters, P., Alazab, M. and Alazab, A., 2012. Cybercrime: the case of obfuscated malware. Global Security, Safety and Sustainability & e-Democracy, pp.204-211.

Deshmukh, D., Pasha, A. and Qureshi, D., 2013. Transparent Data Encryption–Solution for Security of Database Contents. arXiv preprint arXiv:1303.0418.

Deylami, H.M. and Singh, Y.P., 2012. Cybercrime detection techniques based on support vector machines. Artificial Intelligence Research, 2(1), p.1.

Dreßing, H., Bailer, J., Anders, A., Wagner, H. and Gallas, C., 2014. Cyberstalking in a large sample of social network users: Prevalence, characteristics, and impact upon victims. Cyberpsychology, Behavior, and Social Networking, 17(2), pp.61-67.

Grabosky, P., 2014. The evolution of cybercrime, 2004-2014. Browser Download This Paper.

Harrell, E. and Langton, L., 2013. Victims of identity theft, 2012 (p. 12). US Department of Justice, Office of Justice Programs, Bureau of Justice Statistics.

Hyman, P., 2013. Cybercrime: it’s serious, but exactly how serious?. Communications of the ACM, 56(3), pp.18-20.

Jhaveri, R.H., Patel, S.J. and Jinwala, D.C., 2012, January. DoS attacks in mobile ad hoc networks: A survey. In Advanced Computing & Communication Technologies (ACCT), 2012 Second International Conference on (pp. 535-541). IEEE.

Khan, A.A., 2013. Preventing phishing attacks using one time password and user machine identification. arXiv preprint arXiv:1305.2704.

Raiyn, J., 2014. A survey of cyber attack detection strategies. International Journal of Security and Its Applications, 8(1), pp.247-256.

Rid, T. and Buchanan, B., 2015. Attributing cyber attacks. Journal of Strategic Studies, 38(1-2), pp.4-37.

Rotich, E.K., Metto, S.K., Siele, L. and Muketha, G.M., 2014. A Survey on Cybercrime Perpetration and Prevention: A Review and Model for Cybercrime Prevention. European Journal of Science and Engineering, 2(1), pp.13-28.

Sindhu, K.K. and Meshram, B.B., 2012. Digital forensics and cyber crime datamining. Journal of Information Security, 3(3), p.196.

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