ABOUT ANTIVIRUS
Introduction
Anomaly Intrusion Detection System (A-IDS) is a significant portion of cyber security countermeasure, that exists in almost all the latest security devices. Here, the security devices which are used by A-IDS in the systems have been discussed. The implementation of one of the following is discussed: SIEM, IPS (Intrusion prevention system) and Antivirus.
The typical network data to be employed in the security devices has been mentioned. At the final step, the anomaly of the collected data is analysed with the help of security systems.
The security systems like the Intrusion Prevention System (IPS), Antivirus, and Security Incident and Event Management (SIEM) are crucial for cyber security, and widely in use in all the networks. The study of employing these security systems needs lots of knowledge as well as experience. The related jobs are largely in demand in Australia. As security is not a product, many efforts must be done to set up a secure network. The challenges of the implementation have been discussed. The solutions to the industry challenge have been discussed.
Method :
Today, the virus can infect a computer in a number of ways. There are many points possible for infection, which needs to be secured. For this purpose, an anti-virus needs to be implemented which has multiple levels for blocking the propagation of the virus (Aljawarneh, 2018). The security can be provided by an antivirus at the level of a workstation in a network. For implementing this, a desktop or an antivirus solution for workstation is required which can be obtained from the vendors. The infection, which is caused by an external medium like a floppy disk, e-mails, applications like Trojan horse virus, macro, LAN, etc. can be prevented by using an antivirus (Jyothsna, 2011).
Figure 1. Block Diagram
The mail server also needs to be secured because an email can infect the network or the computer system with a good speed. If the mail server is protected, the organization can be protected due to the virus which is propagated through an email. The email antivirus proves to be a good solution in this case (Gyanchandani, 2012).
The virus can also attack a web server or an FTP server because they access the internet directly and have a large vulnerability. These can be protected in two ways. One method involves the implementation of an antivirus based on the server (Yassin, 2013). This method can help with trapping and quarantining the virus at the level of the server. The other computers present on this LAN are not infected in this manner. Another method of protection is by the execution of the intrusion detection system. It helps to provide a protecting layer for some Dos (Denial of service) attacks. It is capable of blocking some virus exploits that can propagate by any known exploits in the server like IIS worms. It is not similar to a firewall because of the addition of an extra intelligence layer (Geramiraz, 2012). This can identify as well as block any behaviour of the server which is malicious. If the above methods are applied at the level of the server then the security of the server from the attack of the virus can be insured.
Requirements to choose the best antivirus for a business.
Best Server Antivirus Software and explanation?
Benefits of using each
All features of it
how it reacts when it detects a virus?
Installation for an enterprise?
Structure?
Required system to set up?
References
Aljawarneh, S., Aldwairi, M. and Yassein, M.B., 2018. Anomaly-based intrusion detection system through feature selection analysis and building hybrid efficient model. Journal of Computational Science, 25, pp.152-160.
Jyothsna, V.V.R.P.V., Prasad, V.R. and Prasad, K.M., 2011. A review of anomaly based intrusion detection systems. International Journal of Computer Applications, 28(7), pp.26-35.
Gyanchandani, M., Rana, J.L. and Yadav, R.N., 2012. Taxonomy of anomaly based intrusion detection system: a review. International Journal of Scientific and Research Publications, 2(12), pp.1-13.
Yassin, W., Udzir, N.I., Muda, Z. and Sulaiman, M.N., 2013, August. Anomaly-based intrusion detection through k-means clustering and naives bayes classification. In Proc. 4th Int. Conf. Comput. Informatics, ICOCI (No. 49, pp. 298-303).
Geramiraz, F., Memaripour, A.S. and Abbaspour, M., 2012. Adaptive Anomaly-Based Intrusion Detection System Using Fuzzy Controller. IJ Network Security, 14(6), pp.352-361.
Chitrakar, R. and Huang, C., 2012, September. Anomaly based intrusion detection using hybrid learning approach of combining k-medoids clustering and naive bayes classification. In 2012 8th International Conference on Wireless Communications, Networking and Mobile Computing (pp. 1-5). IEEE.
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