Annotated Bibliographies on Network and Information Security Tech

This annotated bibliography presents a collection of research papers on various aspects of network and information security technologies. The included articles cover topics such as cloud computing security, virus defense, wireless network security algorithms, firewall technology, botnet detection, and intrusion detection systems. The bibliography summarizes the key findings, methodologies, and limitations of each study, offering insights into the current landscape of network security research. The papers explore techniques like distributed CFO algorithms, fuzzy logic for security assessment, and hybrid intrusion recognition procedures. The studies also address the challenges of botnet detection, the evolution of firewall technology, and the vulnerabilities in wireless network communications. The bibliography offers a comprehensive overview of the current research and technologies used to protect networks from various threats, including viruses, malware, and botnets.

Annotated Bibliographies on Network and Information Security
Technologies

1. Sheng,Z., HuiShan,H., & XueKui, S. (2016). Research on Computer Network Virus Defense
Technology in Cloud Technology Environment. International Journal of Security and Its Applications,
10(3), 449-460.
In this article, Sheng, HuiShan, and Xuekui (2016) propose a structural representation for virus
concealment depending on cloud computing technology. The author analyzes the conventional virus
exposure techniques which can’t efficiently destroy the new kind of viruses and malevolent software
like Trojans, worms, etc. They pertained a novel distributed CFO algorithm, PIF algorithm, and
maximum independent set algorithm in cloud computing for effectively exposing and describing the
restrictive prompt characteristic of virus and malware. The article would be useful to network users
as it provides discussions on the invariable characteristic analysis technique depending on cloud
computing and enhancement in the virus and malware exposure proportion when contrasted with
the distinct computer system. The main limitation of the article is the synchronization drawback of
each and every virtual machine connection.
2. Ahmed, S., & Nader, M. (2016). New Algorithm for Wireless Network Communication Security.
International Journal on Cryptography and Information Security, 6(4), 11-19.
In this article, Ahmed and Nader (2016) exploited the fuzzy logic m-file in Mat lab for the defence
assessment of wireless networks. After studying the existing algorithms, the author proposed a new
fusion system procedure for wireless network security. They executed a relative study in between
the symmetric algorithms DES, AES, and 3DES. They also assessed the conventional procedure, novel
algorithm, clock cipher algorithm, and recommended algorithm in order to emphasize the safety
point of proposed algorithm. In this article, it is proved that the hybrid model is very complicated
than the traditional procedure for safety and elevated accomplishment in the wireless network. The
main limitation of the article is that the network security is limited based on the proposed algorithm
in the network valuation.
3. Dong, L., & Peng, Y. (2012). Network Security and Firewall Technology. International Conference
on Computer and Electrical Engineering, 53(2), 35-60.
In this article, Lily Dong and Yuanzhen Peng (2012) have taken the firewall technology as the main
network security technique. Since the authors discovered in practical that already prevailing firewall
technology rallies the present network security requirement with some complexity. This article is
based on the author’s concrete awareness on firewall technology methodologies and firewall

categorization. In this article, the authors converses the restrictions of the firewall itself since it does
not go through firewalls attachment, if it is secured in the network system by means of SLIP and PPP
precisely with the Internet coupled interior user, will then leads to a concealed risk. The firewall
technology used in this article assures that the safety of the network is enough in a definite network
progress situation and performs according to the insisted objective to implement the equivalent
security procedure.
4. Saudi, M., Faizal, M.A., Selamat, S.R., Fadhlee, M.D., & Ramzi, W.Y (2017). Revealing the future
influence in HTTP Botnet Detection. International Journal of Communication networks and
information security, 9(2), 50-70.
In this article, Saudi, Faizal, Selamat, Fadhlee, and Ramzi (2017) have discussed the most emerging
threat “Botnet” which aims most of the client’s network of computers. Many experiments are
carried out on the botnets and methods to spot the botnets in network traffic. In this article, the
authors selected a noteworth characteristic for boosting the exactness of botnet concealment.
Existing experiments aims only on the botnet detection techniques and do not expose the objective
apart from the choice. In this paper, the authors disclose the manipulating ability in botnet exposure
by utilizing arithmetical methodology. The experimental output received by the authors exhibits
about 91% precision that is almost tolerable for employing the influence aspect in exposing botnet
movement.
5. Lekha, J., & Ganapathi, P. (2017). Detection of illegal traffic pattern using Hybrid Improved CART
and Multiple Extreme Learning Machine Approach. International Journal of communication networks
and information security, 9(2), 40-65.
In this paper, Lekha and Ganapathi proposed a hybrid invasion recognition procedure for finding the
damage in the traffic pattern of network. The authors incorporated misuse detection in which the
network traffic pattern is divided into known and unknown threat and anomaly detection models. In
this article, the incorporated anomaly detection model divides the not identified threat as normal
data set and unknown threat for enhancing the accomplishment of usual traffic activity. The author
carried out the research by making use of NSL – KDD dataset and the accomplishment of the new
method is contrasted with the conventional finding methods through training period, analysis time,
detection percentage, and false positive ratio. The limitation of the paper is that it detects only 52%
percentage of the unknown threats.