Volume-12 , Issue-4 , Aug 2024, ISSN 2320-7639 (Online) Go Back

• Open Access   Article

  Generative Adversarial Networks Using Name Entity Recognition Model Using Clinical Health Records

  Yojitha Chilukuri, Ulligaddala Srinivasarao

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.12 , Issue.4 , pp.1-7, Aug-2024

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  Abstract
  Recently, there has been increased attention in the Clinical Named Entity Recognition research area within Medical Records (MR). As much clinical-related information exists in structured and unstructured textual data, Named Entity Recognition technology helps extract different types of patient data. The widespread use of MR has sparked interest in utilizing technology, especially in Biomedical Named Entity Recognition, which faces challenges due to various entities such as medications, genes, diseases, and proteins. Recently, advanced NLP technology has shown outstanding performance through pre-training textual encoders. The encoding of input data is pivotal to the effectiveness of neural sequence labeling models, as they are essential for generating the morphological data. This paper focuses on a variant of the deep neural network model to improve the proposed method. This analysis tackles the challenge of Biomedical Named Entity Recognition by employing Generative adversarial networks that integrate biological data analysis. Numerical sequences are converted into word embedding models. The creation of embeddings based on input is facilitated by pre-trained word embeddings such as GloVe. The model efficiency achieves an improved accuracy of 97.74%.

  Key-Words / Index Term
  Generative adversarial networks, Deep neural network, word embedding, Name entity recognition.

  References
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  Citation
  Yojitha Chilukuri, Ulligaddala Srinivasarao, "Generative Adversarial Networks Using Name Entity Recognition Model Using Clinical Health Records," International Journal of Scientific Research in Computer Science and Engineering, Vol.12, Issue.4, pp.1-7, 2024

• Open Access   Article

  Examining Cryptographic Primitives and Introducing the Periodic-Shift Cipher

  Padma Sree Uma Nandini Kadavakollu, Sony Kumari, Srinivasa Rao Gundu

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.12 , Issue.4 , pp.8-17, Aug-2024

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  Abstract
  Cryptography is an essential element of modern digital security. It consists of techniques for translating plaintext into ciphertext and back to allow safe communication. It also serves as a foundation for critical applications such as secure internet interactions, electronic business, and data integrity authentication. This work investigates five types of cryptographic primitives: symmetric encryption, asymmetric cryptography, hash functions, and digital signatures, while examining their impact on the CIA Triangle—confidentiality, integrity, and availability. Both classical and modern advances in cryptography are discussed, tracing their evolution from classical ciphers to modern algorithms like RSA, along with the emerging threat of quantum computing. Additionally, a unique encryption technique, the Periodic-Shift Cipher B/I law, is introduced. Designed for educational purposes, it emphasizes simplicity and security, using only odd-numbered shifts and the new “a=z” rule. This article reviews some of the positives and negatives of this architecture and suggests areas for further investigation to enhance pro-cryptography education and better prepare forensic specialists for future security challenges.

  Key-Words / Index Term
  Cryptography, Digital security, Secure communication, Symmetric encryption, Asymmetric cryptography, Hash functions, Digital signatures, RSA algorithm

  References
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  Citation
  Padma Sree Uma Nandini Kadavakollu, Sony Kumari, Srinivasa Rao Gundu, "Examining Cryptographic Primitives and Introducing the Periodic-Shift Cipher," International Journal of Scientific Research in Computer Science and Engineering, Vol.12, Issue.4, pp.8-17, 2024

• Open Access   Article

  A New Technique of Ranking Madagascar’s Universities Using CoCoFISo Method in a Multi-Criteria Decision Support System: MadUrank

  Rôlin Gabriel RASOANAIVO, Joseph Alphonse TATA

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.12 , Issue.4 , pp.18-31, Aug-2024

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  Abstract
  The ranking of national universities provides an additional means of gauging the performance of universities that have not yet been included in global rankings. In the case of Madagascar, we proposed the implementation of a multi-criteria decision support system, designated as MadUrank, for the purpose of ranking the six public universities in the country. The system employs two distinct methodologies. Firstly, the method based on the removal effects of criteria (MEREC), is used to establish the relative importance of the criteria. Secondly, the combined compromise for ideal solution (CoCoFISo) method, is employed to determine the ranking of universities. The selection of criteria was based on the availability of data, with five criteria ultimately chosen. These were the number of students registered (STUREG), the ratio of students to administrative and technical staff (ATS), the ratio of students to permanent teachers (PTEACH), the success rate in examinations (SUCCES), and the percentage of students receiving scholarships (STUSCHO). The data set comprises observations from 2016 to 2020. In consideration of the data set, the MEREC method afforded priority to the STUREG criterion for the years 2016, 2017, and 2020, and to the STUSCHO criterion for the years 2018 and 2019. In accordance with the aforementioned priority criteria and the data set, the CoCoFISo method designated the Université d’Antananarivo as the top-ranked institution in 2016 and the Université de Fianarantsoa as the top-ranked institution from 2017 to 2020.

  Key-Words / Index Term
  Universities rankings, Madagascar’s Universities, Performance criteria, MEREC, CoCoFISo, MadUrank

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  Citation
  Rôlin Gabriel RASOANAIVO, Joseph Alphonse TATA, "A New Technique of Ranking Madagascar’s Universities Using CoCoFISo Method in a Multi-Criteria Decision Support System: MadUrank," International Journal of Scientific Research in Computer Science and Engineering, Vol.12, Issue.4, pp.18-31, 2024

• Open Access   Article

  Internet of Things (IoT) and their Intrusion: Solution and Potential Challenges

  Danial Haider, Tehreem Saboor, Aqsa Rais

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.12 , Issue.4 , pp.32-47, Aug-2024

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  Abstract
  As we know, the cyber-attacks are merging day by day. Everything that relates to the internet has compromised with the attacks. Internet connection and their connectivity with other devices make them more vulnerable to attacks. Numerous industries, including aerial observation, wireless communication, healthcare, construction, precision farming, search and rescue, and the military, heavily rely on their usage. Moreover, these systems or networks are still exposed and have loopholes that make it welcomed to attackers to invade the system or network easily. Intrusion detection system is the system that is used to sense and also protect the network from cyber-attacks that are possible due to internet connections. This paper highlights the threat and issues that are link with the intrusion detection system in IoT domain. Also, paper emphasis on the significance or importance of the IDS in IoT. Also highlights the various IDS like signature-based IDS, anomaly-based IDS etc. Furthermore, describes and elaborates the problems that are faced with respect to each type of IDS. Finally, suggest remediation against each problem of each type of IDS to safeguard the IoT domain.

  Key-Words / Index Term
  IoT, IDS, Attacks, Challenges

  References
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  Citation
  Danial Haider, Tehreem Saboor, Aqsa Rais, "Internet of Things (IoT) and their Intrusion: Solution and Potential Challenges," International Journal of Scientific Research in Computer Science and Engineering, Vol.12, Issue.4, pp.32-47, 2024

• Open Access   Article

  Cyber-Physical Systems with Anti-smog Guns for Busy City Areas to Suppress Air Pollution Efficiently

  Shivam Kumar Sah

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.12 , Issue.4 , pp.48-53, Aug-2024

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  Abstract
  Living in once the world’s most polluted city i.e. Kathmandu, it is obvious to question ourselves what adverse effect we could have by just inhalation of the toxic air every day, especially, when inhaling the air for a single day equals the fumes produced by nearly 10 cigarettes. Meanwhile, the long-term plans–planting trees, strict traffic regulations, and awareness–seemed to be implausible for the locals and city hustles. Similarly, instant solutions like Anti-smog vehicles invite more problems like traffic congestion and management efforts, and solutions like air scrubber technology are yet to be implemented that require prior data of polluted areas to place the scrubber efficiently. Therefore, a concept to tackle these issues, a system that automatically implements instant solutions to suppress air pollution for adverse effects, is to be introduced. This paper explores the concept of Technology, IoT, Data Science, and Cloud computing concepts to build a Cyber-Physical System and uses water mist with suitable eco-friendly surfactants to suppress air pollution in busy city areas efficiently. Our proposed solution uses a chain of Nephelometers throughout the city at specific distances that send data to the cloud that is further processed to operate the nearby automatic immobile Anti-smog gun to suppress the particulate matter without any traffic congestion or mass wastage of resources. The collected data collected in the cloud could be further evaluated to place additional Air Scrubber Systems in specific required areas.

  Key-Words / Index Term
  Cyber-Physical System, Air Pollution Suppression, Transdisciplinary approach, Anti-smog guns, Air Scrubber, Nephelometer, IoT, Cloud computing, etc.

  References
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  Citation
  Shivam Kumar Sah, "Cyber-Physical Systems with Anti-smog Guns for Busy City Areas to Suppress Air Pollution Efficiently," International Journal of Scientific Research in Computer Science and Engineering, Vol.12, Issue.4, pp.48-53, 2024

• Open Access   Article

  Association Rule Mining on Likert’s Scale Data using a Novel Attributes Pruning Technique

  Ogedengbe M.T., Junaidu S.B., Kana A.F.D.

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.12 , Issue.4 , pp.54-65, Aug-2024

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  Abstract
  In recent decades, the Apriori algorithm has emerged as a powerful tool for generating meaningful insights and supporting effective decision-making in data science. Traditionally a binary mining tool, Apriori is highly efficient in analysing transaction datasets in market basket analysis to uncover customer purchasing patterns. When applied to Likert scale datasets, however, it requires discretizing item attributes into binary values, which can result in significant information loss. This study proposes a novel mining technique called Common Question Attribute Pruning (CQAP), which enhances the standard Apriori algorithm by extending its capabilities to process 5-point Likert scale datasets without the need for attribute discretization, thereby preserving the ordinal nature of the respondents` opinions. The key innovation of this technique lies in its ability to represent all five points of the Likert scale within the Apriori framework, without converting them to Boolean transaction data (0s and 1s). The modified Apriori algorithm, termed the Extended Apriori Algorithm (Ext-AA), generates candidate sets by treating question-value (q,v) pairs as data points. During the candidate joining phase, any combinations with common question attributes are pruned. This approach introduces a new perspective on defining support count, minimum support threshold metric, and minimum confidence threshold metric, which helps in filtering out infrequent candidate sets and the determination of the strength of the association rules derived from the sample dataset. In experimental evaluations on sample datasets, the Ext-AA produced 8 strong rules, whereas the standard Apriori algorithm generated 135 rules which is 89.63% rule reduction after pruning. These results demonstrate the superior performance potential of CQAP technique against the state of art Apriori algorithm on the evaluated sample datasets.

  Key-Words / Index Term
  Apriori; Pruning; Likert scale; Questionnaire; Candidate-set; Itemset; Support; Confidence

  References
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  Citation
  Ogedengbe M.T., Junaidu S.B., Kana A.F.D., "Association Rule Mining on Likert’s Scale Data using a Novel Attributes Pruning Technique," International Journal of Scientific Research in Computer Science and Engineering, Vol.12, Issue.4, pp.54-65, 2024

• Open Access   Article

  Internet Protocol with Internet Programming (IP with IP): Architecture and Design

  Arun Kumar Singh, Alak Kumar Patra

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.12 , Issue.4 , pp.66-76, Aug-2024

  Abstract

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  Abstract
  The Internet Protocol (IP) is a communication protocol utilized for inter-device communication on the Internet. It is a protocol at the network layer that furnishes an addressing system for uniquely identifying devices on the network and facilitating the routing of data packets between them. Conversely, Internet Programming pertains to the creation of applications and services that operate on the Internet. This encompasses activities such as web development, mobile app development, and other types of networked application development. IP is a crucial element of Internet programming because it establishes the underlying infrastructure for inter-device communication on the Internet. Internet programmers must possess a comprehensive understanding of IP and its associated protocols, like TCP (Transmission Control Protocol) and UDP (User Datagram Protocol), to construct applications that can communicate over the Internet. Additionally, internet programmers employ a variety of programming languages, frameworks, and tools to build applications that function on the Internet. This can incorporate languages such as JavaScript, Python, Ruby, and PHP, as well as web development frameworks like React, Angular, and Vue. In summary, IP and Internet programming are closely connected, as IP forms the basis for inter-device communication on the Internet, while Internet programming utilizes this foundation to develop a wide range of networked applications and services. In this article, we will elucidate the significance of both IP and internet programming as indispensable constituents of the Internet, demonstrating their close interconnection. IP establishes the groundwork for data transmission, while internet programming furnishes the means for creating and delivering web-based applications and services.

  Key-Words / Index Term
  Internet Protocol (IP); Internet Programming; IPv4; IPv6; Type of Service; Protocol

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  Citation
  Arun Kumar Singh, Alak Kumar Patra, "Internet Protocol with Internet Programming (IP with IP): Architecture and Design," International Journal of Scientific Research in Computer Science and Engineering, Vol.12, Issue.4, pp.66-76, 2024

• Open Access   Article

  Identifying Botnets within the Traffic Generated By a Network in Two Different Datasets

  Grace Bunmi Akintola

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.12 , Issue.4 , pp.77-93, Aug-2024

  Abstract

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  Abstract
  The impact of cyber-attacks on organizational and private networks has been significant, causing extensive damage and posing serious threats to cybersecurity. This is largely due to the increasing sophistication of malicious hackers, making the detection and mitigation of these attacks more challenging. One such attack is the botnet attack, which involves using compromised systems to launch attacks, including Denial of Service (DoS) attacks, against victim systems. As a result, comprehensive literature reviews have been conducted to examine existing botnet defense and detection techniques, with a particular focus on machine learning due to its effectiveness in identifying and classifying botnet attacks within networks. This paper presents the development of an Artificial Neural Network (ANN) model, a supervised machine learning technique, using MATLAB software for creating, training, and simulating networks. Two datasets, KDD CUP’99 and UNSW-NB15, were used to demonstrate the effectiveness of the proposed model by extracting the same set of features from both. The model achieved classification accuracies of 99.88% and 96% for the respective datasets. A confusion matrix plot was used to illustrate these accuracy values in detail, further validating the model`s effectiveness by showing very low false negative and false positive rates in identifying and grouping botnet attacks.

  Key-Words / Index Term
  Botnets, Networks, Machine Learning, MATLAB, DoS attacks, detection techniques, and datasets

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  Citation
  Grace Bunmi Akintola, "Identifying Botnets within the Traffic Generated By a Network in Two Different Datasets," International Journal of Scientific Research in Computer Science and Engineering, Vol.12, Issue.4, pp.77-93, 2024