Recent Trends in Computer Science, Engineering and Applications - 2025

ijcsea 50 views 16 slides Sep 04, 2025
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About This Presentation

Recent Trends in Computer Science, Engineering and Applications - 2025

International Journal of Computer Science, Engineering and Applications (IJCSEA)

ISSN: 2230 - 9616 [Online] ; 2231 - 0088 [Print]

https://airccse.org/journal/ijcsea/index.html

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Slide Content

Recent Trends in Computer
Science, Engineering and
Applications - 2025


International Journal of Computer Science,
Engineering and Applications (IJCSEA)
ISSN : 2230 - 9616 [Online] ; 2231 - 0088 [Print]
https://airccse.org/journal/ijcsea/index.html
Citations, h-index, i10-index of IJCSEA
Citations 3430 h-index 26 i10-index 72

APPLYING SOFTWARE ENGINEERING SOLUTIONS TO LAW FIRM
MANAGEMENT, NIGERIA AS A CASE STUDY
Chinonyerem Eleweke and Kazeem Oluwakemi Oseni, University of Bedfordshire, UK
ABSTRACT
Legal technology has changed the way law firms are managed worldwide. Substantial
research has been undertaken on the role of legal technology in law firm management
especially in developed countries. Though, most studies have only focused on the benefits
and challenges, and have failed to analyse law firm management areas requiring software
solutions. The principal objective of this paper was to investigate the level of technology
adoption among Nigerian law firms, as well as to develop a software solution to automate
work processes in identified areas. This investigation was done using systematic literature
review to gather relevant data on the subject area and identify knowledge gaps. Findings from
the research indicated a need for further analysis of the various areas in law practice that
could require software solutions. The findings also discussed the implementation of a
property management module which is an important contribution to the management of law
firms in Nigeria. A speech-to-text transcription feature was also implemented to eliminate the
need for lengthy typing.
KEYWORDS
Law firm management, legal technology, property management, speech-to-text.
Full Text: https://aircconline.com/ijcsea/V15N2/15225ijcsea01.pdf
Volume URL: https://airccse.org/journal/ijcsea/current2025.html

REFERENCES
[1] I. A. Mohammed, "Critical Analysis on the Impact of Software Engineering in the
Technological Industry," vol. 7, pp. 182–186, 2020.
[2] Statista, "Legal tech: A statista report on the global legal tech market," 2023.
[3] R. Whalen, "Defining legal technology and its implications," Int J Law Info Tech, vol. 30,
(1), pp. 47–67, 2022. Available: https://doi.org/10.1093/ijlit/eaac005. DOI:
10.1093/ijlit/eaac005.
[4] J. Webb, "Legal Technology: The Great Disruption?" U of Melbourne Legal Studies
Research Paper, 2020. Available: http://dx.doi.org/10.2139/ssrn.3664476.
[5] A. O. Omodele and A. O. Olubukola, "The Pros and Cons of Technology in the Judicial
Process in Lagos State, Nigeria," African Journal of Humanities and Contemporary
Education Research, vol. 13, (1), pp. 329–340, 2023.
[6] Bloomberg, "How the use of legal technology has had an impact in law firms and in-
house legal departments worldwide as of march 2020," Statista Inc, 2020.
[7] N. C. E. Paul and E. F. Uko, "THE ROLES OF INFORMATION AND
COMMUNICATION TECHNOLOGY IN LEGAL PROFESSION," pp. 86 –92, 2022.
Available:
[8] C. A. Aniekwe, "Legal Framework for The Use of Information and Communications
Technology (ICT) In the Nigerian Justice System: A call For Review," IJOCLLEP, vol. 1, pp.
125, 2019.
[9] C. Achinewhu, "Law Practice and Education in Nigeria: The Importance of Technology."
Bulgarian Comparative Education Society, 2023. .
[10] P. A. Aidonojie et al, "The Challenges and Impact of Technological Advancement to the
Legal Profession in Nigeria given the Covid-19 Pandemic," KIU Journal of Humanities, vol.
6, (4), pp. 5– 19, 2022.
[11] Y. Xu et al, "Adopting customer relationship management technology," vol. 102, pp.
442–452, 2002. . DOI: 10.1108/02635570210445871.
[12] Statista, "Number of legal tech startups worldwide as of 2019, by region." Statista Inc.,
2020.
[13] J. Owoeye and I. Mabawonku, "Access and Use of Information and Communication
Technologybased Resources by Legal Professionals in Nigeria," 2019. Available:
https://jaistonline.org/12vol2/24.pdf.
[14] M. Oluwa, "ICT and the Legal Profession." 2016. Available:
https://omlivingstones.wordpress.com/2016/07/01/ict-and-the-legal-profession/.
[15] M. Damkor, D. J. Irinyang and M. Haruna, "The Role of Information Communication
Technology in Nigeria Educational System," International Journal of Research in Humanities
and Social Studies, vol. 2, (2), pp. 64–68, 2015. Available: https://www.ijrhss.org/pdf/v2-
i2/8.pdf.

[16] I. San, A. M. Mohamad and I. Sule, "Commoditization and Productization of Legal
Services: The new trends and the challenges of Nigerian lawyers," International Journal of
Law and Politics Studies, vol. 4, pp. 19–26, 2022. . DOI: 10.32996/ijlps.2022.4.2.3

ESTIMATION FORMULA FOR INDIRECT VALUE REALIZATION OF VIRTUAL
MEETINGS
Fatima A. Al Roomi and Hafed A. Al Ghamdi Saudi Aramco, Dhahran, Saudi Arabia
ABSTRACT
The COVID-19 pandemic has precipitated an urgent and widespread demand for virtual
communication solutions, leading to significant growth in the adoption of Unified
Communication Solutions (UCS). Despite this expansion, existing methodologies for
estimating the realized benefits and their impacts on business productivity remain inadequate,
as they fail to encompass all available solutions in the market. Moreover, the substantial costs
associated with these solutions often leave companies and enterprises struggling with
uncertainties regarding return on investment, primarily due to the absence of a standardized
benefit calculation approach. Consequently, there is a pressing need for standardized formula
to uniformly calculate the benefits accrued from virtual communications. This paper aims to
delineate the critical elements necessary for evaluating the benefits of virtual
communications. Building on these foundational elements, a comprehensive formula will be
introduced to standardize the assessment of virtual meeting benefits.
KEYWORDS
Virtual Meetings, Unified Communication Solutions, UCS, Realized Benefits, Estimation
Formula.
Full Text: https://aircconline.com/ijcsea/V14N4/14424ijcsea01.pdf
Volume URL: https://airccse.org/journal/ijcsea/current2024.html

REFERENCES
[1] Antheunis, M. L., Schouten, A. P., & Walther, J. B. (2020). The hyperpersonal effect in
online dating: Effects of text-based CMC vs. videoconferencing before meeting face-to-face.
Media Psychology, 23(6), 820-839.https://doi.org/10.1080/15213269.2019.1648217
[2] Cisco Webex. (2022). Cisco Webex Virtual Meetings.
https://www.cisco.com/c/en/us/products/conferencing/webex-meetings/index.html
[3] Cisco Jaber. (2022). Cisco Jaber Unified Communications Solution.
https://www.cisco.com/c/en/us/products/unified-communications/jabber/index.html
[4] Microsoft Teams. (2022). Microsoft Teams Video Conferencing.
https://www.microsoft.com/enin/microsoft-teams/group-chat-software [5] Zoom. (2020).
Video Conferencing. https://www.zoom.us
[6] Hanaysha, J. R., &Alzoubi, H. M. (2022). The effect of digital supply chain on
organizational performance: An empirical study in Malaysia manufacturing industry.
Uncertain Supply Chain Management, 10(2), 495-510.
[7] Higgins, S. G., Nogiwa-Valdez, A. A., & Stevens, M. M. (2022). Considerations for
implementing electronic laboratory notebooks in an academic research environment. Nature
Protocols, 17(2), 179- 189.
[8] Keemink, J. R., Sharp, R. J., Dargan, A. K., & Forder, J. E. (2022). Reflections on the Use
of Synchronous Online Focus Groups in Social Care Research. International Journal of
Qualitative Methods, 21, 16094069221095314.
[9] McCain, C., Kemp, B., Baier, M. B., Zea, A. H., Sabottke, C., Schachner, E. R.,
...&Spieler, B. (2022). A Framework for the Virtual Medical Interview Process:
Considerations for the Applicant and the Interviewer. Ochsner Journal, 22(1), 61-70.
[10] Newman, S. A., & Ford, R. C. (2021). Five steps to leading your team in the virtual
COVID-19 workplace. Organizational Dynamics, 50(1),
100802.https://doi.org/10.1016/j.orgdyn.2020.100802
[11] Novikov, P. (2020). Impact of COVID-19 emergency transition to online learning onto
the international students' perceptions of educational process at Russian university. Journal of
Social Studies Education Research, 11(3), 270-302. Retrieved September 15, 2022 from
https://www.learntechlib.org/p/217752/.
[12] Riedl, R. (2022). On the stress potential of videoconferencing: definition and root causes
of Zoom fatigue. Electronic Markets, 32(1), 153-177.
[13] Robinson, M. T. (2021). The Virtual Teaching Experience with Google Classroom
During COVID19: A Phenomenological Study. St. John's University (New York).
[14] Schwartz, C. (2019). The Value of Transitioning to a Cloud-based Phone Platform for an
SME.
[15] Sun, P., &Gu, L. (2021). Optimization of cross-border e-commerce logistics supervision
system based on internet of things technology. Complexity,
2021.https://doi.org/10.1155/2021/4582838
[16] SUNIL, R. (2022). Microsoft Dynamics
365.http://localhost:8080/xmlui/handle/123456789/16606

[17] Whillans, A., Perlow, L., &Turek, A. (2021). Experimenting during the shift to virtual
team work: Learnings from how teams adapted their activities during the COVID-19
pandemic. Information and Organization, 31(1),
100343.https://doi.org/10.1016/j.infoandorg.2021.100343
[18] Žemaitis, K. (2022). Overcoming challenges of using video conferencing technology in
small and medium-sized enterprises (Doctoral dissertation, Kaunotechnologijosuniversitetas).
[19] Cisco IT Case Study. (2008). Cisco TelePresence Benefits.
https://www.cisco.com/c/dam/en_us/about/ciscoitatwork/downloads/ciscoitatwork/pdf/Cisco
_IT_Cas e_Study_TelePresence_Benefits.pdf

ESTIMATION OF PERSISTENCE AT A COMMUNITY COLLEGE: A
COMPARISON OF ALTERNATIVE MACHINE LEARNING MODELS
Fermin Ornelas Institutional Research, Rio Salado College, Maricopa Community Colleges,
Tempe, AZ, USA.
ABSTRACT
This research focuses on developing persistence models for Rio Salado College. It is an
initial effort to predict persistence from one term to the next. Several ensemble models are
experimented and compared in their respective key metrics such as: confusion matrix, AUC,
F1-Score, and feature importance. Exploratory data analysis is undertaken to narrow the set
of variables utilized in the models. Two models were considered for possible implementation:
a logistic regression and a gradient boosting machine. The former is easier to implement and
explain to non-technical personnel, while the latter behaves like a black box. Based on key
performance metrics, the model of choice was the gradient boosting machine. Development
and testing were conducted with python using jupyter notebooks. The author hopes that this
experimental process will fill a vacuum in the analytical needs of community colleges.
KEYWORDS
accuracy, AUC, confusion matrix, ensemble models, feature importance, gradient boosting
machines, Machine Learning, persistence, precision, recall.
Full Text: https://aircconline.com/ijcsea/V13N1/13123ijcsea01.pdf
Volume URL: https://airccse.org/journal/ijcsea/current2023.html

REFERENCES
[1] Aceujo, Esteban M., Frech J., Ugalde, Araya, M. P., & Zafar B. (2020). The impact of
COVID-19 on student experience and expectations: Evidence from a survey. Journal of
Public Economics 191.
[2] Agnihotri, L. & A. Ott. (2014). Building A Student At-Risk Model: An End-to-End
Perspective. Proceedings of the 7th International Conference on Educational Data Mining.
[3] Altig, Dave, Baker S., Barrero, J. M., Bloom, N., Bunn, P., Chen S., Davis, S. J., Leather,
J., Meyer, B., Mihaylov, E., Mizen, P., Parker, N., Renault, T., Smietanka, P., & Thwaits, G.
(2020). Economic Uncertainty Before and During the COID-19 Pandemic. Journal of Public
Economics 191.
[4] Bird, A. Kelli, Castleman, L. B., Mabel, Z., & Song, Y. (2021). Bringing Transparency to
Predictive Analytics: A Systematic Comparison of Predictive Modeling Methods in Higher
Education. (EdWorking Paper: 21-438). nages
[5] Community college enrollment crisis? Historical Trends in Community College
Enrollment. AACC, 2019.
[6] Ekowo, M., Palmer, I. (2016). The Promises and Peril of Predictive Analytics in Higher
Education. A Landscape Analysis. New America, Oct. 2016 Fain, P. Top of the Mountain?
https://www.insidehighered.com/news/2011/12/21/community-college-enrollment-growth-
ends.
[7] Feldman, M. J. (1993) Factors Associated with One-Year Retention in a Community
College. Research in Higher Education, Vol. 34, No 4, 1993. [8] Fike, D. S. & Fike, R.
(2008). Predictors of First-Year Student Retention in the Community College. Volume 36,
Number 2. October 2008, 68-88.
[9] Juszkiewicz, J. (2020, July). Trends in Community College Enrollment and Completion
Data, Issue 6. Washington, DC: American Association of Community Colleges.
[10] Kapoor, S. & Narayanan, A. (2022). Leakage and the Reproducibility Crisis in ML-
based Science. arXiv:2207.07048v1 [cs.LG] 14 Jul 2022
[11] Kyriakides, G. & Margaritis, K. G. Hands-on Ensemble Learning with Python. Packt.
www.packt.com.
[12] Kimbark, K., Peters, M. L., Richardson, T. (2016). Effectiveness of the Student Success
Course on Persistence, Retention, Academic Achievement, and Student Engagement.
Community College Journal of Re search and Practice.
http://dx.doi.org/10.1080/10668926.2016.1166352
[13] Klempin, S., Grant, M., Ramos, M. (2018). Practitioner Perspectives on the Use of
Predictive Analytics in Targeted Advising for College Students. CCRC Working Paper No.
103. May, 2018.
[14] Lane Terralever. The Pandemic’s Impact on Higher Education Marketing in 2020 and
Beyond. https//www.laneterralever.com/industries/higher-education-marketing-
agency/higher-educationmarketing-white-paper-pandemic-impact.
[15] Lopez-Wagner, M. C., Carollo, T., Shindledecker. Predictors of Retention: Identification
of Students At-Risk and Implementation of Continued Intervention Strategies.

[16] Inside Higher Ed. December, 2020. Higher Ed Faces Steep Cuts with Recent Oil Bust.
https://www.insidehighered.com/news/2020/12/16/higher-ed-faces-steep-cuts-recent-oil-bust
[17] Ryan, M. G., Improving Retention and Academic Achievement for First-Time Students
at a TwoYear College. Community College Journal of Research and Practice, 37: 131-134,
2013.
[18] Miller, J. E. & Berger, J. B. A Modified Model of College Student Persistence:
Exploring the Relationship Between Astin’s Theory of Involvement and Tinto’s Theory of
Student Departure. Journal of College Student Development; Jul/Aug 1997; 38, 4; ProQuest
Education Journals pg. 387. [19] Miller, T. E. and Herreid, C. Analysis of Variables to
Predict First-Year Persistence Using Logistic Regression Analysis at the University of South
Florida, 2008.
[20] Mishra, P. (2022) Practical Explainable AI Using Python. https://doi.org/10.1007/978-1-
4842-7158- 2.
[21] Nakajima, M., A., Dembo, M. H., Mossler, R. Student Persistence in Community
Colleges. Community College Journal of Research and Practice, 36: 591-613, 2012.
[22] N. S. C. Stay Informed with the Latest Enrollment Information. November, 2020.
https://nscresearchcenter.org/stay-informed/
[23] N. S. C. The Role of Community Colleges in Postsecondary Success: Community
Colleges Outcomes Report. nscresearchcenter.org.
[24] Ornelas, F. and Ordonez, C. (2017). Predicting Student Success: A Naïve Bayesian
Application to Community College Data. Tech Know Learn 22:299 -315. DOI
10.1007/s10758-017-9334-z.
[25] Parvez, R. & Chowdhury, N. H. K. (2020). Economics of Student Retention Behavior in
Higher Education. Paper presented at the Agricultural and Applied Economics Association
Meetings, 2020.
[26] Prudvi, P. S., Sharifahmadian, E. Applying Machine Learning Techniques to Find
Important Attributes for Heart Failure Severity Assessment. International Journal of
Computer Science Engineering Applications (IJCSEA) Vol 7, No 5, October 2017.
[27] Smith, V.S., Lange A., & Huston, D. R. (2012). Predictive Modeling to Forecast Student
Outcomes and Effective Interventions in Online Community College Courses. Journal of
Asynchronous Learning Networks. Vol. 16, Issue 3.
[28] Taylor, C., Veeramachaneni, K., O’Reilly, U. Likely to Stop? Predicting Stopout in
Massive Open Online Courses. arXiv:1408.3382v1 [cs.CY] 14 Aug. 2014.
[29] The Institute for College Access & Success (2019). Don’t Stop Improving: Supporting
Data-Driven Continuous Improvement in College Student Outcomes, March 2019.
[30] Tinto, V. (1988). Stages of Student Departure: Reflections on the Longitudinal Character
of Student Living. Journal of Higher Education, Jul. – Aug., 1988, Vol. 59, No. 4 (Jul. –
Aug., 1988), pp. 438- 455.

ORGAN DONATION MANAGEMENT SYSTEM (PROJECT: ODMS)
Abhay Yadav, Ariful Islam, Vasa Uday Kiran, Chitroju Naga Sai Jagadeesh, Gagandeep
Singh School of Computer Science Engineering, Lovely Professional University, Phagwara,
India.
ABSTRACT
Organ Donation Management System is a novel idea to support organ donors in India with a
new age interface and ease of registration, and systematic guidelines of Government India to
ensure the legalities. As we included a Aadhar authentication for this process to register a
donor, we duly abide by the laws, values and of Donors to serve the communities in India.
ODMS is an online system which consists of Android Application and a Website. The health
care system has access to detailed information of patients and donors within a management.
As the penetration of Mobile phone and gadgets is another boon for this project idea
deployment. We designed a system if a user willing to donate organs post their death due to
an unfortunate accident or incident with help of Aadhar system we trace the organ donor and
within the golden period we take the permission of family members of deceased organ donor
to transplant his organs to other patients in need. Aadhar plays a pivotal role in this entire
process for Authentication, Tracking the deceased donors and the Know Your Donor called
as KYD where a donor himself provide a legal acceptance of organ donation post his death
through video KYC and digital forms filling.
KEYWORDS
ODMS, Government of India, Aadhar, Organ Donor, Organ Recipient, Database, Website,
Android App.
Full Text: https://aircconline.com/ijcsea/V13N1/13123ijcsea02.pdf
Volume URL: https://airccse.org/journal/ijcsea/current2023.html

REFERENCES
[1] “Donate Life: What you need to know about organ donation in India”. [The better India].
22 November 2016. Retrieved 7 may 2021.
[2] “Organ Report”. [Notto.gov.in.]. Archived from the journal on 4 December 2019.
Retrieved 22 may 2020.
[3] “Narayana Nethralaya- Dr. Rajkumar Eye Bank”. having Achieved From the original
journal. [4] “Strategies and outcome in renal transplant”. Vivek B. Kute. published on 2022
march25.
[5] “Health e-living blog: register as an organ donor”. [Chester county hospital]. 02 April
2021.
[6] “How to register”. Transplant Quebec. Retrieved November 26, 2019.

EMBEDDED SYSTEMS AND SOFTWARE: ENABLING INNOVATION IN THE
DIGITAL AGE
Ali Shahdoust Moghadam Department of IT and Management Nexide B.V., Amsterdam, The
Netherlands
ABSTRACT
This article explores the pivotal role of embedded systems and software in driving
technological advancements across various industries. Embedded systems, characterized by
their integration into hardware devices and their ability to perform specific tasks with
precision, have become ubiquitous in our daily lives. Their applications span across diverse
fields such as automotive, healthcare, consumer electronics, and industrial automation. This
article delves into the fundamental concepts of embedded systems, highlights their
importance, discusses the challenges faced in their development, and explores the latest
trends and innovations in embedded software. We are committed to using our findings from
this exploration to help others in the embedded systems and software community. We believe
that by sharing our knowledge, we can help to accelerate innovation in this field.
KEYWORDS
Embedded systems, Embedded software, Hardware integration, Real-time computing,
Internet of Things (IoT).

Full Text: https://aircconline.com/ijcsea/V13N4/13423ijcsea01.pdf
Volume URL: https://airccse.org/journal/ijcsea/current2023.html

REFERENCES
[1] Lee, E.A. and Seshia, S.A., 2011. Introduction to embedded systems: A cyber-physical
systems approach. MIT Press.
[2] Wolf, W., 2008. Computers as components: Principles of embedded computing system
design. Elsevier.
[3] Alippi, C. (Ed.). (2019). Internet of Things: Technologies, Communications and
Computing. Springer.
[4] Zanella, A., Bui, N., Castellani, A., Vangelista, L. andZorzi, M., 2014. Internet of things
for smart cities. IEEE Internet of Things Journal, 1(1), pp.22-32.
[5] Rajkumar, R.R., Lee, I., Sha, L. and Stankovic, J.A., 2010. Cyber-physical systems: The
next computing revolution. In Design Automation Conference (DAC), 2010 47th ACM/IEEE
(pp. 731- 736)
[6] Satyanarayanan, M. (2017). The Emergence of Edge Computing. Computer, 50(1), 30-39.
[7] Lee, J.W., and Bagherzadeh, N. (Eds.). (2017). Cyber-Physical Systems: Foundations,
Principles, and Applications. Wiley.
[8] McFarland, M., and Hagedorn, J. (2018). Practical Industrial Internet of Things Security:
A practitioner's guide to securing connected industries. Packt Publishing.
[9] Sookhak, M., Gani, A., Buyya, R., and Khan, S.U. (2018). A Comprehensive Study on
Cloud Computing. Journal of Supercomputing, 74(4), 1341-1378.
[10] Stankovic, J.A. (2014). Research Directions for the Internet of Things. IEEE Internet of
Things Journal, 1(1), 3-9.

ANALYZING THE IMPACT OF BLACKHOLE ATTACKS ON AODV AND DSR
ROUTING PROTOCOLS’ PERFORMANCE IN NS -2
Ferdinand Alifo
1
, Mustapha Awinsongya yakubu
2
, Martin Doe
3
and Michael Asante
4

1
MIS/Computer Dep., Ministry of Local Government, Local Gov’t Service.
2
University of Cincinnati Ohio, USA
3
Computer Science Department, University of Business and Integrated Development Studies,
Ghana
4
Department of Computer Science, Kwame Nkrumah University of Science and Technology,
Ghana
ABSTRACT
Mobile Ad-Hoc Networks (MANETs) are wireless networks characterized by their lack of a
fixed infrastructure, allowing nodes to move freely and serve as both routers and hosts. These
nodes establish virtual links and utilize routing protocols such as AODV, DSR, and DSDV to
establish connections. However, security is a significant concern, with the Blackhole attack
posing a notable threat, wherein a malicious node drops packets instead of forwarding them.
To investigate the impact of Blackhole nodes and assess the performance of AODV and DSR
protocols, the researchers employed the NS-2.35 ns-allinone2.35 version for simulation
purposes. The study focused on several metrics, including average throughput, packet
delivery ratio, and residual energy. The findings revealed that AODV demonstrated better
energy efficiency and packet delivery compared to DSR, but DSR outperformed AODV in
terms of throughput. Additionally, environmental factors and data sizes were taken into
account during the analysis.
KEYWORDS
Performance Analyss, AODV, DSR, MANET, Protocols, Security, Blackhole, NS2.
Full Text: https://aircconline.com/ijcsea/V13N4/13423ijcsea02.pdf
Volume URL: https://airccse.org/journal/ijcsea/current2023.html

REFERENCES
[1] B. H. Khudayer et al., "A Comparative Performance Evaluation of Routing Protocols for
Mobile Ad-hoc Networks," International Journal of Advanced Computer Science and
Applications, vol. 14, no. 4, 2023.
[2] S. Al-Emadi and A. Al-Mohannadi, "Towards enhancement of network communication
architectures and routing protocols for FANETs: A survey," in 2020 3rd International
Conference on Advanced Communication Technologies and Networking (CommNet), 2020:
IEEE, pp. 1-10.
[3] M. T. Sultan, H. El Sayed, and M. A. Khan, "Performance Analysis of the Impact of
DDoS Attack on Routing Protocols in Infrastructure-less Mobile Networks," in 2022 5th
International Conference on Communications, Signal Processing, and their Applications
(ICCSPA), 2022: IEEE, pp.1-6.
[4] T. Safdar Malik, M. N. Siddiqui, M. Mateen, K. R. Malik, S. Sun, and J. Wen,
"Comparison of blackhole and wormhole attacks in cloud MANET enabled IoT for
agricultural field monitoring," Security and Communication Networks, vol. 2022, 2022.
[5] M. H. Al Rubaiei, H. S. Jassim, and B. T. Sharef, "Performance analysis of black hole and
worm hole attacks in MANETs," International Journal of Communication Networks and
Information Security, vol. 14, no. 1, pp. 126-131, 2022.
[6] A. C. Onuora, E. E. Essien, and P. Ana, "A Comprehensive Review of Routing Protocols
for Mobile Ad Hoc Networks (Manets)," International Journal of Information System and
Computer Science (IJISCS) Vol, vol. 6, pp. 1-13, 2022.
[7] K. Thamizhmaran, "Secure Analysis of Routing Protocol under Wormhole for MANET,"
Journal of Advancement in Electronics Design, vol. 5, no. 2, pp. 47-52, 2022.
[8] P. Sarao, "Performance Analysis of MANET under Security Attacks," J. Commun., vol.
17, no. 3, pp.194-202, 2022.
[9] P. Pandey and R. Singh, "Efficient ad hoc on demand distance vector routing protocol
based on route stability in MANETs," International Journal of Wireless Information
Networks, vol. 29, no. 3, pp. 393-404, 2022.
[10] S. A. Syed and A. Shahzad, "Enhanced dynamic source routing for verifying trust in
mobile ad hoc network for secure routing," International Journal of Electrical and Computer
Engineering, vol. 12, no. 1, p. 425, 2022.
[11] C. N. Kishore and H. V. Kumar, "Dynamic source routing protocol for robust path
reliability and link sustainability aware routing in wireless communication," Optik, vol. 282,
p. 170036, 2023.