Cited By
View all- Thampi SEl-Alfy EThampi SEl-Alfy E(2019)Soft computing and intelligent systemsJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-16990536:3(1939-1944)Online publication date: 1-Jan-2019
Unsupervised anomaly detection in underwater acoustic sensor networks
Pages 2367 - 2372
Abstract
An underwater acoustic sensor network (UASN) offers a promising solution for the exploration of underwater resources remotely. As the UASN acoustic channel is open and the environment is hostile, the risk of malicious activities is very high, particularly in time-critical military applications. In this paper, we propose an unsupervised anomaly detection system by learning the social behavioral correlation among nodes. The location data retrieved from sensors are learned using long short term memory (LSTM) networks to capture the anomalous nature. The network is simulated by modeling anomalies and analyzed the performance. The analysis of results indicates that the anomaly detection system offers an acceptable accuracy with high true positive rate and F-Score by showing consistency in multiple mobility behavior.
References
[1]
A.P. Das and S.M. Thampi, Single anchor node based localization in mobile underwater wireless sensor networks, in Algorithms and Architectures for Parallel Processing Springer, 2015, pp. 757–770.
[2]
J. Kong, Z. Ji, W. Wang, M. Gerla, R. Bagrodia and B. Bhargava, Low-cost attacks against packet delivery, localization and time synchronization services in under-water sensor networks, in Proceedings of the 4th ACM Workshop on Wireless Security ACM, 2005, pp. 87–96.
[3]
A.P. Das and S.M. Thampi, Secure communication in mobile underwater wireless sensor networks, in Proceedings of the IEEE International Conference on Advances in Computing, Communications and Informatics, India, 2015, pp. 2164–2173.
[4]
Y. Cong, G. Yang, Z. Wei and W. Zhou, Security in underwater sensor network, in Communications and Mobile Computing (CMC), 2010 International Conference on, vol. 1, 2010, pp. 162–168. IEEE.
[5]
R. Zhang and Y. Zhang, Wormhole-resilient secure neighbor discovery in underwater acoustic networks, in INFOCOM, 2010 Proceedings IEEE, 2010, pp. 1–9.
[6]
W. Wang, J. Kong, B. Bhargava and M. Gerla, Visualisation of wormholes in underwater sensor networks: a distributed approach, International Journal of Security and Networks 3(1) (2008), 10–23.
[7]
J. Kong, Z. Ji, W. Wang, M. Gerla, R. Bagrodia and B. Bhargava, On wormhole attacks in under-water sensor networks: A two-tier localization approach, UCLA Computer Science Department Technical Report 4005 (2004).
[8]
G. Dini and A. Lo Duca, A secure communication suite for underwater acoustic sensor networks, Sensors 12(11) (2012), 15 133–15 158.
[9]
A.P. Das and S.M. Thampi, Simulation tools for underwater sensor networks: A survey, Network Protocols and Algorithms 8(4) (2016), 41–55.
[10]
“Aqua-sim,” http://obinet.engr.uconn.edu/wiki/index.php/Aqua-Sim.
[11]
K. Mridula and P. Ameer, Localization under anchor node uncertainty for underwater acoustic sensor networks, International Journal of Communication Systems 31(2) (2018), e3445.
[12]
G. Dini and A.L. Duca, Seflood: A secure network discovery protocol for underwater acoustic networks, in Computers and Communications (ISCC), 2011 IEEE Symposium on IEEE, 2011, pp. 636–638.
[13]
G. Ateniese, A. Capossele, P. Gjanci, C. Petrioli and D. Spaccini, Secfun: Security framework for underwater acoustic sensor networks, in OCEANS 2015-Genova IEEE, 2015, pp. 1–9.
[14]
A.P. Das and S.M. Thampi, Anomaly detection in uasn localization based on time series analysis and fuzzy logic, in Mobile Networks and Applications, in Press.
[15]
M. Xu and L. Liu, Sensevault: A three-tier framework for securing mobile underwater sensor networks, IEEE Transactions on Mobile Computing (2018).
[16]
G. Han, J. Jiang, L. Shu and M. Guizani, An attack-resistant trust model based on multidimensional trust metrics in underwater acoustic sensor network, IEEE Transactions on Mobile Computing 14(12) (2015), 2447–2459.
[17]
J. Jiang, G. Han, L. Shu, S. Chan and K. Wang, A trust model based on cloud theory in underwater acoustic sensor networks, IEEE Transactions on Industrial Informatics 13(1) (2017), 342–350.
[18]
A.P. Das and S.M. Thampi, Fault-resilient localization for underwater sensor networks, Ad Hoc Networks, 2016.
[19]
L. Meiqin, G. Xiaodong and Z. Senlin, Localization based on best spatial correlation distance mobility prediction for underwater wireless sensor networks, in 34th Chinese Control Conference, Hangzhou, 2015, pp. 7827–7832.
[20]
“Bonnmotion,” http://sys.cs.uos.de/bonnmotion/index.shtml.
[21]
G. Pei, M. Gerla, X. Hong and C.-C. Chiang, A wireless hierarchical routing protocol with group mobility, in Proceedings of the IEEE Wireless Communications and Networking Conference, New Orleans, USA, 1999, pp.1538–1542.
Index Terms
- Unsupervised anomaly detection in underwater acoustic sensor networks
Index terms have been assigned to the content through auto-classification.
Recommendations
Anomaly Detection in UASN Localization Based on Time Series Analysis and Fuzzy Logic
AbstractUnderwater acoustic sensor network (UASN) offers a promising solution for exploring underwater resources remotely. For getting a better understanding of sensed data, accurate localization is essential. As the UASN acoustic channel is open and the ...
Low-Power Based Coherent Acoustic Modem for Emerging Underwater Acoustic Sensor Networks
Smart, small, inexpensive sensor nodes are used to construct underwater acoustic sensor networks. In addition, with the recent increase in the importance of underwater applications, the need for underwater communication has become more important. Hence, ...
Design of a Low-Cost Underwater Acoustic Modem
There has been an increasing interest in creating short-range, low data rate, underwater wireless sensor networks for scientific marine exploration and monitoring. However, the lack of an inexpensive, underwater acoustic modem is preventing the ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
© 2019 – IOS Press and the authors. All rights reserved.
Publisher
IOS Press
Netherlands
Publication History
Published: 01 January 2019
Author Tags
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- View Citations1Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 03 Mar 2025
Other Metrics
Citations
Cited By
View all- Thampi SEl-Alfy EThampi SEl-Alfy E(2019)Soft computing and intelligent systemsJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-16990536:3(1939-1944)Online publication date: 1-Jan-2019