Routing Attacks and Countermeasures in the RPL-Based Internet of Things
Open accessAbstract
The Routing Protocol for Low-Power and Lossy Networks (RPL) is a novel routing protocol standardized for constrained environments such as 6LoWPAN networks. Providing security in IPv6/RPL connected 6LoWPANs is challenging because the devices are connected to the untrusted Internet and are resource constrained, the communication links are lossy, and the devices use a set of novel IoT technologies such as RPL, 6LoWPAN, and CoAP/CoAPs. In this paper we provide a comprehensive analysis of IoT technologies and their new security capabilities that can be exploited by attackers or IDSs. One of the major contributions in this paper is our implementation and demonstration of well-known routing attacks against 6LoWPAN networks running RPL as a routing protocol. We implement these attacks in the RPL implementation in the Contiki operating system and demonstrate these attacks in the Cooja simulator. Furthermore, we highlight novel security features in the IPv6 protocol and exemplify the use of these features for intrusion detection in the IoT by implementing a lightweight heartbeat protocol.
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A variety of data augmentation techniques, including shifting sensor locations, arbitrary rotations, permuting sensor event locations, time warping, and scaling, will significantly improve the performance of deep learning-based human activity recognition.
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Cites
Secure routing in wireless sensor networks: attacks and countermeasures
Karlof, C., & Wagner, D. A. (2003) · Ad Hoc Networks · doi:10.1016/s1570-8705(03)00008-8 · Cited by 2,941 · see citing works
The Constrained Application Protocol (CoAP)
Shelby, Z., Hartke, K., & Bormann, C. (2014) · doi:10.17487/rfc7252 · Cited by 2,605 · cited 9× · see citing works
“Further, since connection-oriented web protocols such as HTTP or HTTPs are designed to be used over TCP, a new protocol, the Constrained Application Protocol (CoAP) [10], is being standardized for the IoT.”
MethodInfluentialTelos: enabling ultra-low power wireless research
Polastre, J., Szewczyk, R., & Culler, D. (2005) · Cited by 1,746 · see citing works
The sybil attack in sensor networks
Newsome, J., Shi, E., Song, D. X., & Perrig, A. (2004) · ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) · doi:10.1145/984622.984660 · Cited by 1,298 · see citing works
Cross-Level Sensor Network Simulation with COOJA
Österlind, F., Dunkels, A., Eriksson, J., Finne, N., & Voigt, T. (2006) · Conference on Local Computer Networks · doi:10.1109/lcn.2006.322172 · Cited by 1,084 · see citing works
Self-citationIP Encapsulating Security Payload (ESP)
Atkinson, R. J. (1995) · doi:10.17487/rfc1827 · Cited by 1,077 · see citing works
Kushalnagar, N., Montenegro, G. C., & Schumacher, C. (2007) · doi:10.17487/rfc4919 · Cited by 961 · see citing works
Telos: enabling ultra-low power wireless research
Polastre, J., Szewczyk, R., & Culler, D. (2005) · International Symposium on Information Processing in Sensor Networks (IPSN) · doi:10.1109/ipsn.2005.1440950 · Cited by 928 · see citing works
Compression Format for IPv6 Datagrams over IEEE 802.15.4-Based Networks
Thubert, P. (2011) · doi:10.17487/rfc6282 · Cited by 526 · see citing works
The ContikiMAC Radio Duty Cycling Protocol
Dunkels, A. (2011) · Cited by 448 · see citing works
Full TCP/IP for 8-bit architectures
Dunkels, A. (2003) · International Conference on Mobile Systems, Applications, and Services · doi:10.1145/1066116.1066118 · Cited by 397 · see citing works
DTLS based security and two-way authentication for the Internet of Things
Kothmayr, T., Schmitt, C., Hu, W., Brünig, M., & Carle, G. (2013) · Ad Hoc Networks · doi:10.1016/j.adhoc.2013.05.003 · Cited by 391 · see citing works
Kovatsch, M., Duquennoy, S., & Dunkels, A. (2011) · IEEE International Conference on Mobile Ad-Hoc and Sensor Systems (MASS) · doi:10.1109/mass.2011.100 · Cited by 235 · see citing works
Securing communication in 6LoWPAN with compressed IPsec
Raza, S., Duquennoy, S., Chung, T., Yazar, D., Voigt, T., & Roedig, U. (2011) · International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) · doi:10.1109/dcoss.2011.5982177 · Cited by 225 · see citing works
Self-citationOn the Intruder Detection for Sinkhole Attack in Wireless Sensor Networks
Ngai, E. C. ‐., Liu, J., & Lyu, M. R.-T. (2006) · International Conference on Communications · doi:10.1109/icc.2006.255595 · Cited by 212 · see citing works
Raza, S., Duquennoy, S., Höglund, J., Roedig, U., & Voigt, T. (2012) · Security and Communication Networks · doi:10.1002/sec.406 · Cited by 185 · see citing works
Self-citation6LoWPAN Compressed DTLS for CoAP
Raza, S., Trabalza, D., & Voigt, T. (2012) · IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS) · doi:10.1109/dcoss.2012.55 · Cited by 174 · see citing works
Self-citationLow-power wireless IPv6 routing with ContikiRPL
Tsiftes, N., Eriksson, J., & Dunkels, A. (2010) · ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) · doi:10.1145/1791212.1791277 · Cited by 150 · see citing works
Preventing wormhole attacks on wireless ad hoc networks: a graph theoretic approach
Lazos, L., Poovendran, R., Meadows, C. A., Syverson, P. F., & Chang, L. W. (2005) · IEEE Wireless Communications and Networking Conference · doi:10.1109/wcnc.2005.1424678 · Cited by 136 · see citing works
Security Considerations in the IP-based Internet of Things
García-Morchón, Ó., Kumar, S., Struik, R., Keoh, S. L., & Hummen, R. (2013) · Cited by 115 · see citing works
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Securing the Internet of Things: Challenges, threats and solutions
Radoglou Grammatikis, P. I., Sarigiannidis, P. G., & Moscholios, I. D. (2019) · Internet of Things · doi:10.1016/j.iot.2018.11.003 · Cited by 308 · see citing works
Azam, Z., Islam, M. M., & Huda, M. N. (2023) · IEEE Access · doi:10.1109/access.2023.3296444 · Cited by 265 · see citing works
Understanding Security Requirements and Challenges in Internet of Things (IoT): A Review
Hameed, S., Khan, F. I., & Hameed, B. (2019) · Journal of Computer Networks and Communications · doi:10.1155/2019/9629381 · Cited by 219 · see citing works
A Comprehensive IoT Attacks Survey based on a Building-blocked Reference Model
Akram, H., Konstantas, D., & Mahyoub, M. (2018) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2018.090349 · Cited by 193 · see citing works
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Yao, H., Gao, P., Zhang, P., Wang, J., Jiang, C., & Lu, L. (2019) · IEEE Network · doi:10.1109/mnet.001.1800479 · Cited by 113 · see citing works
Current cyber-defense trends in industrial control systems
Rubio, J. E., Alcaraz, C., Roman, R., & Lopez, J. (2019) · Computers & Security · doi:10.1016/j.cose.2019.06.015 · Cited by 113 · see citing works
Intelligent Detection of IoT Botnets Using Machine Learning and Deep Learning
Kim, J., Shim, M., Hong, S., Shin, Y., & Choi, E. (2020) · Applied Sciences · doi:10.3390/app10197009 · Cited by 106 · see citing works
- Authors
- Wallgren, L., Raza, S., & Voigt, T.
- Affiliations
- SICS Swedish ICT, Isafjordsgatan 22, 16440 Kista, Stockholm, Sweden
- Uppsala University (SE)
- Corresponding author
- Raza, Shahid
- Venue
- International Journal of Distributed Sensor Networks
- Publisher
- SAGE Publications
- Published
- 2013-08-01
- Volume
- 9
- Issue
- 8
- Pages
- 794326
- ISSN
- 1550-1329 (ISSN-L)
- 1550-1477
- OpenAlex
- W2026609766
- Cited by
- 483
- References
- 21
- Citations by year
- 2026: 13 · 2025: 19 · 2024: 30 · 2023: 41 · 2022: 44 · 2021: 65 · 2020: 70 · 2019: 63 · 2018: 54 · 2017: 38 · 2016: 30 · 2015: 10 · 2014: 5 · 2013: 1
- FWCI
- 20.17
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- International Journal of Distributed Sensor Networks (publishedVersion, cc-by)
- KTH Publication Database DiVA (KTH Royal Institute of Technology) (submittedVersion, other-oa)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- European Commission (FP7-ICT-2011.1.3-288879)
- Swedish Institute of Computer Science (FP7-ICT-2011.1.3-288879)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Security in Wireless Sensor Networks
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Physical Sciences › Engineering › Electrical and Electronic Engineering › IPv6, Mobility, Handover, Networks, Security
- Keywords
- RPL routing protocol, Internet of Things security, routing attacks, 6LoWPAN, intrusion detection, resource-constrained devices, Contiki, Cooja simulator, CoAP
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