Intrusion Detection and Vulnerability Analysis with Temporal Relationalship
DOI:
https://doi.org/10.61841/4n3fh985Keywords:
Intrusion Detection, Attack Ramification, Vulnerability Analysis, Temporal Dependency Network and Dynamic Bayesian NetworkAbstract
The network attacks are discovered using the Intrusion Detection Systems (IDS). Anomaly, signature and compound attack detection schemes are employed to fetch malicious data traffic activities. The attack impact analysis operations are carried out to discover the malicious objects in the network. The system objects are contaminated with process injection or hijacking. The attack ramification model discovers the contaminated objects. The dependency networks are build to model the information flow over the objects in the network. The dependency network is a directed graph build to indicate the data communication over the objects. The attack ramification models are designed with intrusion root information. The attack ramifications are applied to identify the malicious objects and contaminated objects. The attack ramifications are discovered with the information flows from the attack sources. The Attack Ramification with Bayesian Network (ARBN) scheme discovers the attack impact without the knowledge of the intrusion root. The probabilistic reasoning approach is employed to analyze the object state for ramification process. The objects lifetime is divided into temporal slices to verify the object state changes. The system call traces and object slices are correlated to construct the Temporal Dependency Network (TDN). The Bayesian Network (BN) is constructed with the uncertain data communication activities extracted from the TDN. The attack impact is fetched with loopy belief propagation on the BN model. The network security system is build with attack impact analysis and recovery operations. Live traffic data analysis process is carried out with improved temporal slicing concepts. Attack Ramification and Recovery with Dynamic Bayesian Network (ARRDBN) is build to support attack impact analysis and recovery tasks. The unsupervised attack handling mechanism automatically discovers the feasible solution for the associated attacks.
Downloads
References
[1] M.-W. L. DING-SOU CHEN and J. LIU, “Isolating multiple sensor faults based on self-contribution plots
with adaptive monitoring,” China Steel Technical Report, no. 24, pp. 64–73, 2011.
[2] V. Reppa, M. Polycarpou, and C. Panayiotou, “Decentralized isolation of multiple sensor faults in largescale interconnected nonlinear systems,”, IEEE Transactions on Automatic Control, vol. 60, no. 6, pp.
1582–1596, June 2015.
[3] D. Fragkoulis, G. Roux, and B. Dahhou, “A global scheme for multiple and simultaneous faults in system
actuators and sensors,” in Systems, Signals and Devices, 2009. 6th International Multi-Conference on,
March 2009, pp. 1–6.
[4] L. Mhamdi, H. Dhouibi, N. Liouane, and Z. Simeu-Abazi, “Multiple fault diagnosis using mathematical
models,” in Control Conference (ASCC), 2013 9th Asian, June 2013, pp. 1–6.
[5] C.-C. Li and J.-C. Jeng, “Multiple sensor fault diagnosis for dynamic processes,” ISA Transactions, vol. 49,
no. 4, pp. 415 – 432, 2010.
[6] I. Issury and D. Henry, “A methodology for multiple and simultaneous fault isolation,” in Control
Conference (ECC), 2009 European, Aug 2009.
[7] B. Pourbabaee, N. Meskin, and K. Khorasani, “Sensor fault detection, isolation, and identification using
multiple-model-based hybrid kalman filter for gas turbine engines,” IEEE Transactions on Control Systems
Technology, vol. 24, no. 4, pp. 1184–1200, July 2016
[8] P. Arpaia, C. Manna, and G. Montenero, “Ant-search strategy based on likelihood trail intensity
modification for multiple-fault diagnosis in sensor networks,” Sensors, IEEE, vol. 13, no. 1, pp. 148–158,
Jan 2013.
[9] A. Sharma, H. Chen, M. Ding, K. Yoshihira, and G. Jiang, “Fault detection and localization in distributed
systems using invariant relationships,” in Dependable Systems and Networks (DSN), 2013 43rd Annual
IEEE/IFIP International Conference on, June 2013, pp. 1–8.
[10] Z. Du and X. Jin, “Multiple faults diagnosis for sensors in air handling unit using fisher discriminant
analysis,” Energy Conversion and Management, vol. 49, no. 12, pp. 3654 – 3665, 2008.
[11] Yuan Yang, Zhongmin Cai, Chunyan Wang and Junjie Zhang, “Probabilistically Inferring Attack
Ramifications Using Temporal Dependency Network”, IEEE Transactions on Information Forensics and
Security, Volume 13, Issue 11, 2018.
[12] Muhammad Ejaz Ahmed, Saeed Ullah and Hyoungshick Kim, “Statistical Application Fingerprinting for
DDoS Attack Mitigation”, IEEE Transactions on Information Forensics and Security, Volume: 14 , Issue: 6,
June 2019.
[13] Alippi.C, S. Ntalampiras and M. Roveri, “Model-free fault detection and isolation in large-scale cyberphysical systems,” IEEE Trans. Emerg. Topics Comput. Intell., vol. 1, no. 1, pp. 61–71, Feb. 2017.
[14] Prakash, S. and Vijayakumar, M., “An effective network traffic data control using improved Apriori rule
mining,” Circuits and Systems, Issue 10, Vol. 07, pp. 3162-3173, June 2016.
[15] Sureshkumar V S, Chandrasekar A,” Fuzzy-GA Optimized Multi-Cloud Multi-Task Scheduler For Cloud
Storage And Service Applications” International Journal of Scientific & Engineering Research, Vol.04,
Issue.3,pp-1-7, 2013.
[16] Preethi, B.C. and Vijayakumar, M. “ A novel Cloud Integration Algorithm(CIA) for Energy Efficient High
Performance Computing Applications in Big Data Multimedia Applications”, Romanian Journal of
Information Science and Technology, vol. 2, no.1, pp. 1-11, March 2018.
[17] Vijayakumar M, Prakash s, “An Improved Sensitive Association Rule Mining using Fuzzy Partition
Algorithm”, Asian Journal of Research in Social Sciences and Humanities, Vol.6,Issue.6, pp.969-981, 2016.
[18] Prakash S, Vijayakumar M, “ Risk assessment in cancer treatment using association rule mining
techniques”, Asian Journal of Research in Social Sciences and Humanities,Vol.6,Issue.10, pp.1031-1037,
2016.
[19] Prabhakar E, “ Enhanced adaboost algorithm with modified weighting scheme for imbalanced problems,
The SIJ transaction on Computer science & its application,Vol.6,Issue.4, pp.22-26, 2018.
[20] Suresh kumar V S, Thiruvankatasamy S, Sudhakar R, “Optimized Multicloud Multitask Scheduler For
Cloud Storage And Service By Genetic Algorithm And Rank Selection Method”, Vol.3,Issue.2, pp.1-6,
2014.
[21] Prabhakar E, Santhosh M, Hari Krishnan A, Kumar T, Sudhakar R,” Sentiment Analysis of US Airline
Twitter Data using New Adaboost Approach”, International Journal of Engineering Research &
Technology (IJERT), Vol.7, Issue.1, pp.1-6, 2019.
[22] Dhivyaa C R, Vijayakumar M,” An effective detection mechanism for localizing macular region and
grading maculopathy”, Journal of medical systems, Vol.43, Issue.3, pp.53-, 2019.
[23] K Nithya, M Saranya, CR Dhivyaa, “Concept Based Labeling of Text Documents Using Support Vector
Machine”, International Journal on Recent and Innovation Trends in Computing and Communication, vol.
2, no. 3, pp. 541-544, (2014).
[24] Nandagopal S., Arunachalam V.P., Karthik S."A novel approach for inter-transaction association rule
mining, Journal of Applied Sciences Research VOL, 8, Issue 7, 2012.
[25] Kannan R., Selvambikai M., Jeena Rajathy I., Ananthi S. Rasayan, A study on structural analysis of
electroplated Nano crystalline nickel based thin films, Journal of Chemistry, Vol 10, issue 4, 2017.
[26] Arunvivek G.K., Maheswaran G., Senthil Kumar S., Senthilkumar M., Bragadeeswaran T. Experimental
study on influence of recycled fresh concrete waste coarse aggregate on properties of concrete. International
Journal of Applied Engineering Research, Vol 10, issue 11, 2015
[27] Krishna S.K., Sathya M. Usage of nanoparticle as adsorbent in adsorption process. A review International
Journal of Applied Chemistry, vol 11, Issue 2, 2015.
[28] Sudha S., Manimegalai B., Thirumoorthy P. A study on routing approach for in-network aggregation in
wireless sensor networks, International Conference on Computer Communication and Informatics:
Ushering in Technologies of Tomorrow, Today, ICCCI 2014.
[29] Satheesh A., Jeyageetha V. Improving power system stability with facts controller using certain intelligent
techniques, International Journal of Applied Engineering Research, Vol 9, no 23, 2014.
[30] Ashok V., Kumar N, Determination of blood glucose concentration by using wavelet transform and neural
networks, Iranian Journal of Medical Sciences, Vol 38, Issue 1, 2013.
[31] Somasundaram K., Saritha S., Ramesh K, Enhancement of network lifetime by improving the leach protocol
for large scale WSN, Indian Journal of Science and Technology, Vol 9, Issue 16, 2016.
[32] Jayavel S., Arumugam S., Singh B., Pandey P., Giri A., Sharma A. Use of Artificial Intelligence in
automation of sequential steps of software development / production, Journal of Theoretical and Applied
Information Technology, Vol 57, Issue 3, 2013.
[33] Ramesh Kumar K.A., Balamurugan K., Gnanaraj D., Ilangovan S, Investigations on the effect of flyash on
the SiC reinforced aluminium metal matrix composites, Advanced Composites Letters, Vol 23, Issue 3,
2014.
[34] Suresh V.M., Karthikeswaran D., Sudha V.M., Murali Chandraseker D, Web server load balancing using
SSL back-end forwarding method. IEEE-International Conference on Advances in Engineering, Science
and Management, ICAESM-2012, 2012.
[35] Karthikeswaran D., Sudha V.M., Suresh V.M., Javed Sultan A, A pattern based framework for privacy
preservation through association rule mining, IEEE-International Conference on Advances in Engineering,
Science and Management, ICAESM-2012, 2012.
[36] Senthil J., Arumugam S., Shah P, Real time automatic code generation using generative programming
paradigm, European Journal of Scientific Research, vol. 78, issue 4, 2012.
[37] Vijayakumar J., Arumugam S, Certain investigations on foot rot disease for betelvine plants using digital
imaging technique, Proceedings - 2013 International Conference on Emerging Trends in Communication,
Control, Signal Processing and Computing Applications, IEEE-C2SPCA", 2013.
[38] Vijayakumar J., Arumugam S. Odium piperis fungus identification for piper betel plants using digital image
processing, Journal of Theoretical and Applied Information Technology, vol 60, issue 2, 2014.
[39] Manchula A., Arumugam S, Face and fingerprint biometric fusion: Multimodal feature template matching
algorithm, International Journal of Applied Engineering Research, vol 9, issue 22, 2014.
[40] Ramesh Kumar K.A., Balamurugan K., Arungalai Vendan S., Bensam Raj J, Investigations on thermal
properties, stress and deformation of Al/SiC metal matrix composite based on finite element method.
Carbon - Science and Technology, Vol 6, Issue 3, 2014.
[41] Kanchana A., Arumugam S, Palm print texture recognition using connected-section morphological
segmentation, Asian Journal of Information Technology Vol 6, Issue 3, 2014.
[42] Padmapriya R., Thangavelu P, Characterization of nearly open sets using fuzzy sets, Global Journal of Pure
and Applied Mathematics, vol 11, issue 1, 2015.
[43] P.B. Narandiran, T. Bragadeeswaran, M. Kamalakannan, V. Aravind, Manufacture of Flyash Brick Using
Steel Slag and Tapioca Powder. Jour of Adv Research in Dynamical & Control Systems, Vol. 10, No. 12,
2018, 527-532
[44] R. Girimurugan*, N. Senniangiri, K. Adithya, B. Velliyangiri, Mechanical Behaviour of Coconut Shell
Powder Granule Reinforced Epoxy Resin Matrix Bio Composites, Jour of Adv Research in Dynamical &
Control Systems, Vol. 10, No. 12, 2018, 533-541
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
