Hybrid intrusion detection system using blockchain framework

被引:6
|
作者
Khonde, S. R. [1 ,2 ]
Ulagamuthalvi, V. [1 ]
机构
[1] Sathyabama Inst Sci & Technol, Dept Comp Sci & Engn, Chennai, Tamil Nadu, India
[2] SP Pune Univ, MES Coll Engn, Dept Comp Engn, Pune, Maharashtra, India
关键词
Blockchain; Intrusion detection system; Secured communication; XGBoost; Isolation random forest; Artificial neural network; Ensemble approach;
D O I
10.1186/s13638-022-02089-4
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Data security and confidentiality are major goals now days due to the extensive use of the internet for data sharing. In modern era, most of the networks are compromised by intruders to grab access to private, confidential, and highly secured data. An intrusion detection system (IDS) is widely used to secure the network from getting compromised by intruders. Most of the IDS share the signatures of the novel attacks detected by anomaly approach for improving the detection rate and processing time. Security of signature shared by nodes is becoming a considerable problem. This paper presents a novel framework blockchain based hybrid intrusion detection system (BC-HyIDS), which uses the blockchain framework for exchanging signatures from one node to the other in distributed IDS. BC-HyIDS works in three phases where it uses both detection methods and blockchain in the third phase to provide security to data transferred through the network. This system makes use of a cryptosystem to encrypt the data stored in blocks to improve security one level higher. Hyperledger fabric v2.0 and Hyperledger sawtooth is used to implement system. Blockchain framework is created as a prototype using distributed ledger technology which helps in securing signature exchange. Performance of BC-HyIDS is evaluated in terms of accuracy, detection rate, and false alarm rate. From results, it is observed that a 2.8% increase in accuracy, 4.3% increase in detection rate, and a reduction of 2.6% in FAR is achieved. Blockchain performance is evaluated using Hyperledger fabric v2.0 and Hyperledger sawtooth on throughput, processing time, and average latency. BC-HyIDS shows improved performance when used with blockchain.
引用
收藏
页数:25
相关论文
共 50 条
  • [1] Hybrid intrusion detection system using blockchain framework
    S. R. Khonde
    V. Ulagamuthalvi
    [J]. EURASIP Journal on Wireless Communications and Networking, 2022
  • [2] A novel hybrid framework for Cloud Intrusion Detection System using system call sequence analysis
    Chaudhari, Ashish
    Gohil, Bhavesh
    Rao, Udai Pratap
    [J]. CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2024, 27 (03): : 3753 - 3769
  • [3] CIDS: Collaborative Intrusion Detection System using Blockchain Technology
    Gurung, Gopal
    Bendiab, Gueltoum
    Shiaele, Maria
    Shiaeles, Stavros
    [J]. 2022 IEEE INTERNATIONAL CONFERENCE ON CYBER SECURITY AND RESILIENCE (IEEE CSR), 2022, : 125 - 130
  • [4] Advocating for Hybrid Intrusion Detection Prevention System and Framework Improvement
    Rizvi, Syed
    Labrador, Gabriel
    Guyan, Matt
    Savan, Jeremy
    [J]. COMPLEX ADAPTIVE SYSTEMS, 2016, 95 : 369 - 374
  • [5] Blockchain Assisted Hybrid Intrusion Detection System in Autonomous Vehicles for Industry 5.0
    Anbalagan, Sudha
    Raja, Gunasekaran
    Gurumoorthy, Sugeerthi
    Suresh, R. Deepak
    Ayyakannu, Kaviyarasu
    [J]. IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2023, 69 (04) : 881 - 889
  • [6] Intrusion Detection and Mitigation System Using Blockchain Analysis for Bitcoin Exchange
    Kim, Suah
    Kim, Beomjoong
    Kim, Hyoung Joong
    [J]. PROCEEDINGS OF 2018 INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND INTERNET OF THINGS (CCIOT 2018), 2018, : 40 - 44
  • [7] Snort Based Collaborative Intrusion Detection System Using Blockchain in SDN
    Ujjan, Raja Majid Ali
    Pervez, Zeeshan
    Dahal, Keshav
    [J]. 2019 13TH INTERNATIONAL CONFERENCE ON SOFTWARE, KNOWLEDGE, INFORMATION MANAGEMENT AND APPLICATIONS (SKIMA), 2019,
  • [8] Hybrid intrusion detection system using machine learning
    Meryem, Amar
    Ouahidi, Bouabid EL
    [J]. Network Security, 2020, 2020 (05): : 8 - 19
  • [9] A hybrid machine learning framework for intrusion detection system in smart cities
    Gill, Komal Singh
    Dhillon, Arwinder
    [J]. EVOLVING SYSTEMS, 2024,
  • [10] Hybrid Intrusion Detection System
    Adhao, Rahul B.
    Mahefuj, Samadhan J.
    Pachghare, Vinod K.
    Khadse, Vijay M.
    [J]. INTERNATIONAL JOURNAL OF NEXT-GENERATION COMPUTING, 2021, 12 (05): : 573 - 579