Article
Computer Science, Theory & Methods
Ying Liu, Ting Zhi, Ming Shen, Lu Wang, Yikun Li, Ming Wan
Summary: This paper proposes a two-level DDoS attack detection method based on information entropy and deep learning to effectively detect attack traffic in the SDN environment.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Computer Science, Information Systems
Zhen Liu, Changzhen Hu, Chun Shan
Summary: The means to achieve DDoS attacks are becoming more automated and diverse, but current methods still struggle with the repetitive or periodic nature of traffic data. This study proposes a new DDoS detection method based on FFT and information entropy to address the limitations of existing approaches. The method is lightweight, faster, and more generally applicable, as demonstrated by high detection accuracy in experiments with the latest dataset.
COMPUTERS & SECURITY
(2021)
Article
Computer Science, Information Systems
Sunny Behal, Krishan Kumar, Monika Sachdeva
Summary: This paper presents D-FAC, an anomaly-based distributed defense system that effectively detects and distinguishes various types of DDoS attacks with superior performance on various detection metrics.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2021)
Article
Computer Science, Information Systems
Nimisha Pandey, Pramod Kumar Mishra
Summary: The Internet of Things consists of connected devices that collaborate to perform tasks and provide services. Distributed denial of service (DDoS) attacks aim to exhaust resources by flooding the target with unnecessary traffic. IoT systems, being resource-constrained, are highly vulnerable to DDoS attacks. This paper analyzes the performance of different entropy-based detection parameters for DDoS attacks and finds that a combination of cfr-entropy and quartile-based threshold provides the best results.
INTERNET OF THINGS
(2023)
Article
Computer Science, Artificial Intelligence
Abdullah Emir Cil, Kazim Yildiz, Ali Buldu
Summary: It is suggested to use the deep neural network (DNN) as a deep learning model for detecting DDoS attacks, and experiments have shown that the model can detect and classify attacks in network traffic with high accuracy.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Theory & Methods
Jisa David, Ciza Thomas
Summary: This research focuses on efficient and early detection of distributed denial of service attacks and discrimination of flash crowds by analyzing network traffic parameters and calculating generalized entropies. The experimental results show higher detection rate and lower false positives compared to existing methods, with reduced processing time.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Xian Wang, Xiaoyao Xie
Summary: Building an efficient system for the detection of DDoS attacks is crucial for network security management. Existing studies on this topic can be categorized into statistical library building, IP address information entropy, and machine learning, each with its own limitations. This paper proposes a novel network quintuple information entropy detection algorithm based on judgment matrix hierarchy analysis, which exhibits superior detection performance and good generalization capacities compared to other algorithms.
Article
Computer Science, Artificial Intelligence
Akshat Gaurav, Brij B. Gupta, Wadee Alhalabi, Anna Visvizi, Yousef Asiri
Summary: The purpose of this study is to provide an overview of distributed denial of service (DDoS) attack detection in intelligent systems. Due to the increasing use of intelligent systems, especially during the COVID-19 pandemic, DDoS attacks have become a major concern. This study analyzes different types of DDoS attacks and defense techniques for intelligent systems, using relevant papers from the Scopus databases. It makes an important contribution to the field of DDoS attack detection by offering a comprehensive overview of the field's evolution and current status, as well as a synthesized summary of various perspectives, definitions, and trends.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Information Systems
Ming Chen, Jing Chen, Xianglin Wei, Bing Chen
Summary: LDDoS attacks, considered a subtype of DDoS attacks, pose a potential threat to Internet security. Most existing LDDoS attacks are constructed and evaluated through theoretical deduction and/or simulation tests. Research shows that successful LDDoS attacks can be achieved, but their attack effect only lasts for a short time.
IET INFORMATION SECURITY
(2021)
Article
Computer Science, Hardware & Architecture
Damu Ding, Marco Savi, Domenico Siracusa
Summary: Distributed Denial-of-Service (DDoS) attacks pose a persistent threat to modern telecommunications networks, and detecting and combating these attacks remains a crucial challenge. Programmable data planes in Software-Defined Networks offer a solution, but the commonly used programming language, P4, lacks certain arithmetic operations required for advanced network monitoring functionalities. This work introduces two novel strategies for flow cardinality and normalized network traffic entropy estimation, and proposes a DDoS detection strategy based on variations of normalized network traffic entropy. Results show comparable or higher detection accuracy compared to existing solutions.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2022)
Article
Computer Science, Information Systems
Reuven Cohen, Matty Kadosh, Alan Lo, Qasem Sayah
Summary: This paper proposes an LB scheme that guarantees high throughput and supports frequent server pool updates while effectively fighting against high-rate SYN attacks.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
Anderson Bergamini de Neira, Burak Kantarci, Michele Nogueira
Summary: This survey article summarizes the classification of studies on DDoS attack prediction, highlighting the current state-of-the-art and research opportunities in this field.
Article
Computer Science, Information Systems
Loic D. Tsobdjou, Samuel Pierre, Alejandro Quintero
Summary: This paper discusses the characteristics and impacts of distributed denial of service attacks and emphasizes the importance of designing defense mechanisms. A new online system is proposed to detect flooding attacks with better performance compared to similar works.
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
(2022)
Article
Computer Science, Hardware & Architecture
Vinicius de Miranda Rios, Pedro R. M. Inacio, Damien Magoni, Mario M. Freire
Summary: This paper investigates a technique called RoQ attack and successfully detects this type of attack using machine learning algorithms and fuzzy logic methods, showing good classification performance in both simulated and real traffic. However, the better performance of the approach based on FL, MLP and ED comes at the cost of longer execution time.
Article
Computer Science, Information Systems
Rojalina Priyadarshini, Rabindra Kumar Barik
Summary: Fog computing provides additional support to the cloud environment, but enterprises are uncertain about using it due to security and privacy concerns. This paper proposes a source-based DDoS defense mechanism that uses Software Defined Networking to detect and mitigate DDoS attacks.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Debasish Das, Utpal Sharma, D. K. Bhattacharyya
INTERNATIONAL JOURNAL OF INFORMATION SECURITY
(2019)
Article
Computer Science, Artificial Intelligence
Rajib Goswami, D. K. Bhattacharyya, Malayananda Dutta
JOURNAL OF INTELLIGENT INFORMATION SYSTEMS
(2017)
Article
Multidisciplinary Sciences
Pooja Sharma, Dhruba K. Bhattacharyya, Jugal Kalita
SCIENTIFIC REPORTS
(2017)
Article
Biology
Tulika Kakati, Hasin A. Ahmed, Dhruba K. Bhattacharyya, Jugal K. Kalita
COMPUTATIONAL BIOLOGY AND CHEMISTRY
(2018)
Article
Biochemical Research Methods
Koyel Mandal, Rosy Sarmah, Dhruba Kumar Bhattacharyya
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2019)
Review
Computer Science, Hardware & Architecture
Upasana Sarmah, D. K. Bhattacharyya, J. K. Kalita
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2018)
Article
Computer Science, Information Systems
Rup Kumar Deka, Dhruba Kumar Bhattacharyya, Jugal Kumar Kalita
COMPUTER COMMUNICATIONS
(2019)
Review
Biology
Tulika Kakati, Dhruba K. Bhattacharyya, Pankaj Barah, Jugal K. Kalita
COMPUTERS IN BIOLOGY AND MEDICINE
(2019)
Article
Computer Science, Artificial Intelligence
Hussain Ahmed Chowdhury, Dhruba Kumar Bhattacharyya, Jugal Kumar Kalita
Summary: The study introduces a density-based clustering method UIFDBC that can detect clusters of arbitrary shapes without user input. Evaluation results show the method outperforms its counterparts in discovering arbitrary shaped clusters and has the ability to handle low-density instances.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Biochemical Research Methods
Koyel Mandal, Rosy Sarmah, Dhruba Kumar Bhattacharyya
Summary: The paper introduces the POPBic algorithm, incorporating KEGG pathways to discover genes with similar expression patterns based on pathway relationships. Experimental results demonstrate the algorithm's sensitivity and robustness in the presence of noise, confirming its ability to detect biologically significant biclusters.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2021)
Article
Computer Science, Artificial Intelligence
Koyel Mandal, Rosy Sarmah, Dhruba Kumar Bhattacharyya
Summary: Exploratory analysis of high throughput gene sample time data plays a crucial role in biomedical and bioinformatics research, providing insights into gene regulatory mechanisms and hidden biological knowledge. In this study, a novel semi-supervised Pathway-based Order Preserving Triclustering algorithm is proposed to identify different types of triclusters. Experimental results on artificial and real datasets, including breast cancer and HIV data, demonstrate the effectiveness of the algorithm.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Remote Sensing
Dibyajyoti Chutia, Naiwrita Borah, Diganta Baruah, Dhruba Kumar Bhattacharyya, P. L. N. Raju, K. K. Sarma
Article
Mathematical & Computational Biology
P. Kakati, D. K. Bhattacharyya, J. K. Kalita
NETWORK MODELING AND ANALYSIS IN HEALTH INFORMATICS AND BIOINFORMATICS
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Manaswita Saikia, Nazrul Hoque, Dhruba Kumar Bhattacharyya
RECENT DEVELOPMENTS IN MACHINE LEARNING AND DATA ANALYTICS
(2019)
Article
Biotechnology & Applied Microbiology
Bikash Jaiswal, Kumar Utkarsh, D. K. Bhattacharyya
JOURNAL OF GENETIC ENGINEERING AND BIOTECHNOLOGY
(2018)
