Design and Development of A Cloud-Based IDS using Apache Kafka and Spark Streaming

Wirz, Leon; Tanthanathewin, Rinrada; Ketphet, Asipan; Fugkeaw, Somchart

doi:10.1109/jcsse54890.2022.9836264

Cited by 7 publications

(2 citation statements)

References 10 publications

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“…Wirz et al 38 implemented a cloud‐based system that uses Apache Kafka and Spark streaming to detect and process high‐traffic inputs in HTTP communications. They used signature‐based detection to identify unusual input patterns and reduce false alarms in SQL injection attacks.…”

Section: Sqlia In Cloud Computingmentioning

confidence: 99%

Analysis of SQL injection attacks in the cloud and in WEB applications

Kumar,

Dutta,

Pranav

2024

Security and Privacy

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Cloud computing has revolutionized the way IT industries work. Most modern‐day companies rely on cloud services to accomplish their day‐to‐day tasks. From hosting websites to developing platforms and storing resources, cloud computing has tremendous use in the modern information technology industry. Although an emerging technique, it has many security challenges. In structured query language injection attacks, the attacker modifies some parts of the user query to still sensitive user information. This type of attack is challenging to detect and prevent. In this article, we have reviewed 65 research articles that address the issue of its prevention and detection in cloud and Traditional Networks, of which 11 research articles are related to general cloud attacks, and the rest of the 54 research articles are specifically on web security. Our result shows that Random Forest has an accuracy of 99.8% and a Precision rate of 99.9%, and the worst‐performing model is Multi‐Layer Perceptron (MLP) in the SQLIA Model. For recall value, Random Forest performs best while TensorFlow Linear Classifier performs worst. F1 score is best in Random Forest, while MLP is the most diminutive performer.

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Section: Sqlia In Cloud Computingmentioning

confidence: 99%

Analysis of SQL injection attacks in the cloud and in WEB applications

Kumar,

Dutta,

Pranav

2024

Security and Privacy

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“…Secara umum format log dari web server apache mencatat informasi sumber pengakses yang terdiri dari IP Address, username (jika dikonfigurasi), waktu, request type (GET/POST), kode status respon HTTP, ukuran, user-agent, dan sumber perujuk [22]. Implementasi TF-IDF pada dokumen berupa log web server, yaitu melakukan pre-processing, melakukan perhitungan frekuensi dari term, melakukan perhitungan frekuensi dari inversi dokumen, dan pembobotan.…”

Section: Hasil Dan Pembahasanunclassified

Analisis dan Penanganan Insiden Siber SQL Injection Menggunakan Kerangka NIST SP 800-61R2 dan Algoritma Klusterisasi K-Means

Asnawi,

Hariyadi,

Aesyi

et al. 2023

JKKI

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Based on the OWASP Top Ten document in 2021, attacks or vulnerabilities in an application in the form of injection still rank in the top 3. SQL Injection attacks are still classified as injection vulnerabilities so they need special attention from Information & Communication Technology Managers. Badan Siber dan Sandi Negara (BSSN) has published a document related to preventing SQL Injection attacks. However, the document has not included a cyber attack analysis process that uses the K-Means clustering approach. So in this research, a collaborative method of handling cyber attacks in the form of SQL Injection is proposed using the NIST SP 800-61R2 framework as a fundamental for handling cyber attacks and K-Means clustering. Before analyzing cyber attacks, it is better to use a framework or standardization that applies globally. Based on the research conducted, the K-Means clustering algorithm can help cybersecurity analysts in the process of analyzing cyber attacks that occur. The result of this research is that the optimal value is obtained that cyber attacks in the form of SQL Injection, namely 3 clusters. The hope of the research can facilitate cybersecurity analysts in analyzing cyber attacks that are poured into reports to parties in need

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