Secure store and forward proxy for dynamic IoT applications over M2M networks

Internet of Things (IoT) applications are expected to generate a huge unforeseen amount of traffic flowing from Consumer Electronics devices to the network. In order to overcome existing interoperability problems, several standardization bodies have joined to bring a new generation of Machine to Machine (M2M) networks as a result of the evolution of wireless sensor/actor networks and mobile cellular networks to converged networks. M2M is expected to enable IoT paradigms and related concepts into a reality at a reasonable cost. As part of the convergence, several technologies preventing new IoT services to interfere with existing Internet services are flourishing. Responsive, message-driven, resilient and elastic architectures are becoming essential parts of the system. These architectures will control the entire data flow for an IoT system requiring sometimes to store, shape and forward data among nodes of a M2M network to improve network performance. However, IoT generated data have an important personal component since it is generated in personal devices or are the result of the observation of the physical world, so rises significant security concerns. This article proposes a novel opportunistic flexible secure store and forward proxy for M2M networks and its mapping to asynchronous protocols that guarantees data confidentiality.

[1]  Bin Guo,et al.  From participatory sensing to Mobile Crowd Sensing , 2014, 2014 IEEE International Conference on Pervasive Computing and Communication Workshops (PERCOM WORKSHOPS).

[2]  R. Hollands Will the real smart city please stand up? , 2008, The Routledge Companion to Smart Cities.

[3]  M. Mambo,et al.  Proxy Cryptosystems: Delegation of the Power to Decrypt Ciphertexts (Special Section on Cryptography and Information Security) , 1997 .

[4]  Jo Woon Chong,et al.  A time synchronization technique for coap-based home automation systems , 2016, IEEE Transactions on Consumer Electronics.

[5]  Zhaohui Tang,et al.  Securing Industrial Control System: An End-to-End Integrity Verification Approach , 2015 .

[6]  Arun Prakash,et al.  Machine-to-Machine (M2M) communications: A survey , 2016, J. Netw. Comput. Appl..

[7]  Sajjad Haider Shami,et al.  Evolution of Communication Technologies for Smart Grid applications , 2013 .

[8]  Amardeo Sarma,et al.  Identities in the Future Internet of Things , 2009, Wirel. Pers. Commun..

[9]  Dae-Man Han,et al.  Smart home energy management system using IEEE 802.15.4 and zigbee , 2010, IEEE Transactions on Consumer Electronics.

[10]  Luigi Lo Iacono,et al.  REST-ful CoAP Message Authentication , 2015, 2015 International Workshop on Secure Internet of Things (SIoT).

[11]  R. H. Glitho,et al.  Application architectures for machine to machine communications: Research agenda vs. state-of-the art , 2011, 7th International Conference on Broadband Communications and Biomedical Applications.

[12]  Xiaohui Liang,et al.  GRS: The green, reliability, and security of emerging machine to machine communications , 2011, IEEE Communications Magazine.

[13]  Robert Simon Sherratt,et al.  Proxy re-encryption schemes for IoT and crowd sensing , 2016, 2016 IEEE International Conference on Consumer Electronics (ICCE).

[14]  Andreas Menychtas,et al.  Is there a Need for a Cloud Platform for European Smart Cities , 2011 .

[15]  Cengiz Gezer,et al.  An overview of oneM2M standard , 2016, 2016 24th Signal Processing and Communication Application Conference (SIU).

[16]  Nei Kato,et al.  Toward intelligent machine-to-machine communications in smart grid , 2011, IEEE Communications Magazine.

[17]  Haci Ilhan,et al.  Managing 6LoWPAN sensors with CoAP on internet , 2015, 2015 23nd Signal Processing and Communications Applications Conference (SIU).

[18]  Utz Roedig,et al.  6LoWPAN Extension for IPsec , 2011 .

[19]  Jesus Alonso-Zarate,et al.  Challenges of massive access in highly dense LTE-advanced networks with machine-to-machine communications , 2014, IEEE Wireless Communications.

[20]  Javier López,et al.  Integrating OpenID with proxy re-encryption to enhance privacy in cloud-based identity services , 2012, 4th IEEE International Conference on Cloud Computing Technology and Science Proceedings.

[21]  Shuang-Hua Yang,et al.  A zigbee-based home automation system , 2009, IEEE Transactions on Consumer Electronics.

[22]  Mark Deakin,et al.  From intelligent to smart cities , 2011 .

[23]  Kevin Ashton,et al.  That ‘Internet of Things’ Thing , 1999 .

[24]  Daren C. Brabham Crowdsourcing as a Model for Problem Solving , 2008 .

[25]  Matt Blaze,et al.  Divertible Protocols and Atomic Proxy Cryptography , 1998, EUROCRYPT.

[26]  Andrea Zanella,et al.  Internet of Things for Smart Cities , 2014, IEEE Internet of Things Journal.

[27]  Matthew Green,et al.  Improved proxy re-encryption schemes with applications to secure distributed storage , 2006, TSEC.

[28]  Rodrigo Roman,et al.  Securing the Internet of Things , 2017, Smart Cards, Tokens, Security and Applications, 2nd Ed..

[29]  Darko Huljenic,et al.  Basic principles of Machine-to-Machine communication and its impact on telecommunications industry , 2011, 2011 Proceedings of the 34th International Convention MIPRO.

[30]  Matthew K. Franklin,et al.  Identity-Based Encryption from the Weil Pairing , 2001, CRYPTO.

[31]  Thiemo Voigt,et al.  6LoWPAN Compressed DTLS for CoAP , 2012, 2012 IEEE 8th International Conference on Distributed Computing in Sensor Systems.

[32]  Nick Feamster,et al.  Improving network management with software defined networking , 2013, IEEE Commun. Mag..

[33]  C. Rogers,et al.  Smart Cities: Contradicting Definitions and Unclear Measures , 2014 .

[34]  Robert Simon Sherratt,et al.  A Survey on Wireless Body Area Networks for eHealthcare Systems in Residential Environments , 2016, Sensors.

[35]  G. Paquet,et al.  E-Governance and Smart Communities , 2001 .