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Blockchain-based ddos attack mitigation protocol for device-to-device interaction in smart home

Digital Communications and Networks 2023年第2期9卷 383-392页

作者： Bello Musa Yakubu Majid Iqbal Khan Abid Khan Farhana Jabeen Gwanggil Jeon Department of Mathematics and Computer Science Chulalongkorn UniversityBangkok10330Thailand Department of Computer Science COMSATS University Islamabad(CUI)Islamabad45550Pakistan College of Science and Engineering University of DerbyDerbyDE221GBUnited Kingdom Department of Embedded Systems Engineering Incheon National UniversityIncheon22012South Korea

Smart home devices are vulnerable to a variety of *** matter gets more complicated when a number of devices collaborate to launch a colluding attack(e.g.,Distributed-Denial-of-Service(ddos))in a network(e.g.,Smart home).To handle these attacks,most studies have hitherto proposed authentication protocols that cannot necessarily be implemented in devices,especially during Device-to-Device(D2D)*** into the potential of Ethereum blockchain and smart contracts,this work proposes a lightweight authentication mechanism that enables safe D2D interactions in a smart *** Ethereum blockchain enables the implementation of a decentralized prototype as well as a peer-to-peer distributed ledger *** work also uses a single server queuing system model and the authentication mechanism to curtail ddos attacks by controlling the number of service requests in the *** simulation was conducted twenty times,each with varying number of devices chosen at random(ranging from 1 to 30).Each requester device sends an arbitrary request with a unique resource requirement at a *** is done to measure the system's consistency across a variety of device *** experimental results show that the proposed protocol not only prevents colluding attacks,but also outperforms the benchmark protocols in terms of computational cost,message processing,and response times.

关键词： ddos attack Device-to-device Smart homes Blockchain Authentication Ethereum smartcontract

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Unprecedented Smart Algorithm for Uninterrupted SDN Services During ddos attack

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Computers, Materials & Continua 2022年第1期70卷 875-894页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Rizaludin Kaspin Iram Haider Sana Nisar J.P.C.Rodrigues Bhawani Shankar Chowdhry Muhammad AslamUqaili Satya Prasad Majumder Danda B.Rawat Richard Etengu Rajkumar Buyya Faculty of Computing&Informatics Multimedia UniversityPersiaranMultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation Centre63000CyberjayaSelangorMalaysia Federal University of Piauí(UFPI) TeresinaPIBrazil Instituto de Telecomunica珲es 6201-001Covilh?Portugal National Center of Robotics and Automation-Condition Monitoring Systems Lab MUETJamshoroPakistan Department of Electrical and Electronic Engineering BUETDhaka1205Bangladesh Department of Electrical Engineering and Computer Science Data Science and Cybersecurity CenterHoward UniversityWashingtonDCUSA Cloud Computing and Distributed Systems(CLOUDS)Laboratory School of Computing and Information SystemsThe University of MelbourneMelbourneVIC 3053Australia

In the design and planning of next-generation Internet of Things(IoT),telecommunication,and satellite communication systems,controller placement is crucial in software-defined networking(SDN).The programmability of the SDN controller is sophisticated for the centralized control system of the entire ***,it creates a significant loophole for the manifestation of a distributed denial of service(ddos)attack ***,recently a Distributed Reflected Denial of Service(DRDoS)attack,an unusual ddos attack,has been ***,minimal deliberation has given to this forthcoming single point of SDN infrastructure failure ***,recently the high frequencies of ddos attacks have increased *** this paper,a smart algorithm for planning SDN smart backup controllers under ddos attack scenarios has *** proposed smart algorithm can recommend single or multiple smart backup controllers in the event of ddos *** obtained simulated results demonstrate that the validation of the proposed algorithm and the performance analysis achieved 99.99%accuracy in placing the smart backup controller under ddos attacks within 0.125 to 46508.7 s in SDN.

关键词： SDN smart algorithm RTZLK-DAASCP ddos attack DRDoS

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A ddos attack Information Fusion Method Based on CNN for Multi-Element Data

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Computers, Materials & Continua 2020年第4期63卷 131-150页

作者： Jieren Cheng Canting Cai Xiangyan Tang Victor SSheng Wei Guo Mengyang Li School of Information Science and Technology Hainan UniversityHaikou570228China Key Laboratory of Internet Information Retrieval of Hainan Province Hainan UniversityHaikou570228China Department of Computer Science University of Central ArkansasConwayAR 72035US

Traditional distributed denial of service(ddos)detection methods need a lot of computing resource,and many of them which are based on single element have high missing rate and false alarm *** order to solve the problems,this paper proposes a ddos attack information fusion method based on CNN for multi-element ***,according to the distribution,concentration and high traffic abruptness of ddos attacks,this paper defines six features which are respectively obtained from the elements of source IP address,destination IP address,source port,destination port,packet size and the number of IP ***,we propose feature weight calculation algorithm based on principal component analysis to measure the importance of different features in different network *** algorithm of weighted multi-element feature fusion proposed in this paper is used to fuse different features,and obtain multi-element fusion feature(MEFF)***,the ddos attack information fusion classification model is established by using convolutional neural network and support vector machine respectively based on the MEFF time *** results show that the information fusion method proposed can effectively fuse multi-element data,reduce the missing rate and total error rate,memory resource consumption,running time,and improve the detection rate.

关键词： ddos attack multi-element data information fusion principal component analysis CNN

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ddos attack Detection Method for Space-Based Network Based on SDN Architecture

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ZTE Communications 2020年第4期18卷 18-25页

作者： JIA Min SHU Yuejie GUO Qing GAO Zihe XIE Suofei Communication Research Center School of Electronics and Information EngineeringHarbin Institute of TechnologyHarbin 150006China Institute of Telecommunication Satellite China Academy of Space TechnologyBeijing 100094China

With the development of satellite communications,the number of satellite nodes is constantly increasing,which undoubtedly increases the difficulty of maintaining network *** software defined network(SDN) with traditional space-based networks provides a new class of ideas for solving this ***,because of the highly centralized network management of the SDN controller,once the SDN controller is destroyed by network attacks,the network it manages will be paralyzed due to loss of *** of the main security threats to SDN controllers is Distributed Denial of Service(ddos) attacks,so how to detect ddos attacks scientifically has become a hot topic among SDN security *** paper proposes a ddos attack detection method for space-based networks based on SDN *** attack detection method combines the optimized Long Short-Term Memory(LSTM) deep learning model and Support Vector Machine(SVM),which can not only make classification judgments on the time series,but also achieve the purpose of detecting and judging through the flow characteristics of a period of *** addition,it can reduce the detection time as well as the system burden.

关键词： space-based network SDN ddos attack LSTM SVM

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Blue Screen of Death Observed for Microsoft Windows Server 2012 R2 under ddos Security attack

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Journal of Information Security 2016年第4期7卷 225-231页

作者： Koushicaa Sundar Sanjeev Kumar Department of Electrical and Computer Engineering The University of Texas—RGV Edinburg Texas USA

Microsoft server Operating Systems are considered to have in-built, host based security features that should provide some protection against Distributed Denial of Service (ddos) attacks. In this paper, we presented results of experiments that were conducted to test the security capability of the latest server Operating System from Microsoft Inc., namely Windows Server 2012 R2. Experiments were designed to evaluate its in-built security features in defending against a common Distributed Denial of Service (ddos) attack, namely the TCP-SYN based ddos attack. Surprisingly, it was found that the Windows Server 2012 R2 OS lacked sufficient host-based protection and was found to be unable to defend against even a medium intensity3.1 Gbps-magnitude of TCP-SYN attack traffic. The server was found to crash within minutes after displaying a Blue Screen of Death (BSoD) under such security attacks.

关键词： Network Security Server Security ddos attack TCP SYN Flood Blue Screen of Death

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Automated Controller Placement for Software-Defined Networks to Resist ddos attacks

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Computers, Materials & Continua 2021年第9期68卷 3147-3165页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Lee Ching Kwang Rizaludin Kaspin Bhawani Shankar Chowdhry Rajkumar Buyya Satya Prasad Majumder Manoj Gupta Shuaib Memon Faculty of Computing&Informatics Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation CentreCyberjaya63000SelangorMalaysia National Center of Robotics and Automation Mehran University of Engineering&TechnologyJamshoroPakistan Department of Computer Science and Engineering Hanyang UniversitySeoul04763South Korea School of Electrical and Electronic Engineering Nanyang Technological University639798Singapore Cloud Computing and Distributed Systems Laboratory The University of MelbourneMelbourneVIC 3053Australia Department of Electrical and Electronic Engineering Bangladesh University of Engineering and Technology(BUET)Dhaka1205Bangladesh Department of Electronics and Communication Engineering JECRC UniversityVidhaniJaipur303905India Auckland Institute of Studies Mt AlbertAucklandNew Zealand

In software-defined networks(SDNs),controller placement is a critical factor in the design and planning for the future Internet of Things(IoT),telecommunication,and satellite communication *** research has concentrated largely on factors such as reliability,latency,controller capacity,propagation delay,and energy ***,SDNs are vulnerable to distributed denial of service(ddos)attacks that interfere with legitimate use of the *** ever-increasing frequency of ddos attacks has made it necessary to consider them in network design,especially in critical applications such as military,health care,and financial services networks requiring high *** propose a mathematical model for planning the deployment of SDN smart backup controllers(SBCs)to preserve service in the presence of ddos *** a number of input parameters,our model has two distinct ***,it determines the optimal number of primary controllers to place at specific locations or nodes under normal operating ***,it recommends an optimal number of smart backup controllers for use with different levels of ddos *** goal of the model is to improve resistance to ddos attacks while optimizing the overall cost based on the *** simulated results demonstrate that the model is useful in planning for SDN reliability in the presence of ddos attacks while managing the overall cost.

关键词： SDN automated controller placement SBC ILP ddos attack

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Cooperative Detection Method for ddos attacks Based on Blockchain

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Computer Systems Science & Engineering 2022年第10期43卷 103-117页

作者： Jieren Cheng Xinzhi Yao Hui Li Hao Lu Naixue Xiong Ping Luo Le Liu Hao Guo Wen Feng Hainan University Haikou570228China Hainan Blockchain Technology Engineering Research Center Haikou570228China Hainan Huochain Tech Company Limited Haikou570100China Research Office of Information Technology Air Force Early Warning AcademyWuhan430019China Department of Mathematics and Computer Science Northeastern State UniversityTahlequah74464USA

Distributed Denial of Service(ddos)attacks is always one of the major problems for service *** blockchain to detect ddos attacks is one of the current popular ***,the problems of high time overhead and cost exist in the most of the blockchain methods for detecting ddos *** paper proposes a blockchain-based collaborative detection method for ddos ***,the trained ddos attack detection model is encrypted by the Intel Software Guard Extensions(SGX),which provides high security for uploading the ddos attack detection model to the ***,the service provider uploads the encrypted model to Inter Planetary File System(IPFS)and then a corresponding Content-ID(CID)is generated by IPFS which greatly saves the cost of uploading encrypted models to the *** addition,due to the small amount of model data,the time cost of uploading the ddos attack detection model is greatly ***,through the blockchain and smart contracts,the CID is distributed to other service providers,who can use the CID to download the corresponding ddos attack detection model from *** provides a decentralized,trusted and tamper-proof environment for service ***,smart contracts and IPFS greatly improve the distribution efficiency of the model,while the distribution of CID greatly improves the efficiency of the transmission on the *** this way,the purpose of collaborative detection can be achieved,and the time cost of transmission on blockchain and IPFS can be considerably *** designed a blockchain-based ddos attack collaborative detection framework to improve the data transmission efficiency on the blockchain,and use IPFS to greatly reduce the cost of the distribution *** the experiment,compared with most blockchain-based method for ddos attack detection,the proposed model using blockchain distribution shows the advantages of low cost and *** remote authentication mechanism of Intel

关键词： Blockchain smart contract IPFS ddos attack

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Entropy-Based Approach to Detect ddos attacks on Software Defined Networking Controller

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Computers, Materials & Continua 2021年第10期69卷 373-391页

作者： Mohammad Aladaileh Mohammed Anbar Iznan H.Hasbullah Yousef K.Sanjalawe Yung-Wey Chong National Advanced IPv6 Centre of Excellence Universiti Sains MalaysiaPenangMalaysia Department of Computer Sciences Northern Border UniversityAr’arKingdom of Saudi Arabia

The Software-Defined Networking(SDN)technology improves network management over existing technology via centralized network *** SDN provides a perfect platform for researchers to solve traditional network’s outstanding ***,despite the advantages of centralized control,concern about its security is *** more traditional network switched to SDN technology,the more attractive it becomes to malicious actors,especially the controller,because it is the network’s brain.A Distributed Denial of Service(ddos)attack on the controller could cripple the entire *** that reason,researchers are always looking for ways to detect ddos attacks against the controller with higher accuracy and lower false-positive *** paper proposes an entropy-based approach to detect low-rate and high-rate ddos attacks against the SDN controller,regardless of the number of attackers or *** proposed approach generalized the Rényi joint entropy for analyzing the network traffic flow to detect ddos attack traffic flow of varying *** two packet header features and generalized Rényi joint entropy,the proposed approach achieved a better detection rate than the EDDSC approach that uses Shannon entropy metrics.

关键词： Software-defined networking ddos attack distributed denial of service Rényi joint entropy

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An Abnormal Network Flow Feature Sequence Prediction Approach for ddos attacks Detection in Big Data Environment

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Computers, Materials & Continua 2018年第4期55卷 95-119页

作者： Jieren Cheng Ruomeng Xu Xiangyan Tang Victor S.Sheng Canting Cai School of Information Science and Technology Hainan University570228HaikouChina State Key Laboratory of Marine Resource Utilization in South China Sea 570228HaikouChina Department of Computer Science University of Central ArkansasConwayAR 72035USA

Distributed denial-of-service(ddos)is a rapidly growing problem with the fast development of the *** are multitude ddos detection approaches,however,three major problems about ddos attack detection appear in the big data ***,to shorten the respond time of the ddos attack detector;secondly,to reduce the required compute resources;lastly,to achieve a high detection rate with low false alarm *** the paper,we propose an abnormal network flow feature sequence prediction approach which could fit to be used as a ddos attack detector in the big data environment and solve aforementioned *** define a network flow abnormal index as PDRA with the percentage of old IP addresses,the increment of the new IP addresses,the ratio of new IP addresses to the old IP addresses and average accessing rate of each new IP *** design an IP address database using sequential storage model which has a constant time *** autoregressive integrated moving average(ARIMA)trending prediction module will be started if and only if the number of continuous PDRA sequence value,which all exceed an PDRA abnormal threshold(PAT),reaches a certain preset *** then calculate the probability that is the percentage of forecasting PDRA sequence value which exceed the *** we identify the ddos attack based on the abnormal probability of the forecasting PDRA *** theorem and experiment show that the method we proposed can effectively reduce the compute resources consumption,identify ddos attack at its initial stage with higher detection rate and lower false alarm rate.

关键词： ddos attack time series prediction ARIMA big data

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Towards real-time ML-based ddos detection via cost-efficient window-based feature extraction

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Science China(Information Sciences) 2023年第5期66卷 114-129页

作者： Haibin LI Yi ZHAO Wenbing YAO Ke XU Qi LI Department of Computer Science and Technology Tsinghua University Beijing National Research Center for Information Science and Technology (BNRist) Institute for Network Sciences and Cyberspace Tsinghua University

Distributed denial of service(ddos) detection is still an open and challenging problem. In particular, sophisticated attacks, e.g., attacks that disguise attack packets as benign traffic always appear, which can easily evade traditional signature-based methods. Due to the low requirements for computing resources compared to deep learning, many machine learning(ML)-based methods have been realistically deployed to address this issue. However, most existing ML-based DDo S detection methods are highly dependent on the features extracted from each flow, which incur remarkable detection delay and computation overhead. This article investigates the limitations of typical ML-based DDo S detection methods caused by the extraction of flow-level features. Moreover, we develop a cost-efficient window-based method that extracts features from a fixed number of packets periodically, instead of per flow, aiming to reduce the detection delay and computation overhead. The newly proposed window-based method has the advantages of well-controlled overhead and wide support of common routers due to its simplicity and high efficiency by design. Through extensive experiments on real datasets, we evaluate the performance of flow-based and window-based *** experimental results demonstrate that our proposed window-based method can significantly reduce the detection delay and computation overhead while ensuring detection accuracy.

关键词： ddos attack machine learning feature extraction detection delay cost-efficiency

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