IoT Elements, Layered Architectures and Security Issues: A Comprehensive Survey
Abstract
:1. Introduction
- Give a picture of all proposed layered architecture of IoT,
- Highlight the security attacks that can occur on each layer and affect the IoT applications,
- Present the communication technologies used by IoT applications along with characteristics and drawbacks as well,
- Provide information about security mechanisms used to protect IoT.
- Suggest a new and generic six-layered secure architecture that can easily be extended with little impact to existing architectures to make secure IoT applications.
2. IoT Elements
2.1. Identification
2.2. Sensing
2.3. Communication
2.4. Computation
2.5. Services
2.6. Semantics
3. IoT Layered Architectures with Security Attacks
3.1. Three Layer Architecture
3.1.1. Perception Layer
- Eavesdropping: Eavesdropping is an unauthorized real-time attack where private communications, such as phone calls, text messages, fax transmissions or video conferences are intercepted by an attacker. It tries to steal information that is transmitted over a network. It takes advantage of unsecure transmission to access the information being sent and received.
- Node Capture: It is one of the hazardous attacks faced in the perception layer of IoT. An attacker gains full control over a key node, such as a gateway node. It may leak all information including communication between sender and receiver, a key used to make secure communication and information stored in memory [38].
- Fake Node and Malicious: It is an attack in which an attacker adds a node to the system and inputs fake data. It aims to stop transmitting real information. A node added by an attacker consumes precious energy of real nodes and potentially control in order to destroy the network.
- Replay Attack: It is also known as a play back attack. It is an attack in which an intruder eavesdrops on the conservation between sender and receiver and takes authentic information from the sender. An intruder sends same authenticated information to the victim that had already been received in his communication by showing proof of his identity and authenticity. The message is in encrypted form, so the receiver may treat it as a correct request and take action desired by the intruder [39].
- Timing Attack: It is usually used in devices that have weak computing capabilities. It enables an attacker to discover vulnerabilities and extract secrets maintained in the security of a system by observing how long it takes the system to respond to different queries, input or cryptographic algorithms [40].
3.1.2. Network Layer
- Denial of Service (DoS) Attack: A DoS attack is an attack to prevent authentic users from accessing devices or other network resources. It is typically accomplished by flooding the targeted devices or network resources with redundant requests in an order to make it impossible or difficult for some or all authentic users to use them [41].
- Main-in-The-Middle (MiTM) Attack: MiTM attack is an attack where the attacker secretly intercepts and alters the communication between sender and receiver who believe they are directly communicating with each other. Since an attacker controls the communication, therefore he or she can change messages according to their needs. It causes a serious threat to online security because they give the attacker the facility to capture and manipulate information in real time [42].
- Storage Attack: The information of users is stored on storage devices or the cloud. Both storage devices and cloud can be attacked by the attacker and user’s information may be changed to incorrect details. The replication of information associated with the access of other information by different types of people provides more chances for attacks.
- Exploit Attack: An exploit is any immoral or illegal attack in a form of software, chunks of data or a sequence of commands. It takes advantage of security vulnerabilities in an application, system or hardware. It usually comes with the aim of gaining control of the system and steals information stored on a network [43].
3.1.3. Application Layer
- Cross Site Scripting: It is an injection attack. It enables an attacker to insert a client-side script, such as java script in a trusted site viewed other users. By doing so, an attacker can completely change the contents of the application according to his needs and use original information in an illegal way [45].
- Malicious Code Attack: It is a code in any part of software intended to cause undesired effects and damage to the system. It is a type of threat that may not be blocked or controlled by the use of anti-virus tools. It can either activate itself or be like a program requiring a user’s attention to perform an action.
- The ability of dealing with Mass Data: Due to a large number of devices and a massive amount of data transmission between users, it has no ability to deal with data processing according to the requirements. As a result, it leads to network disturbance and data loss.
3.2. Four Layer Architecture
Support Layer
- DoS Attack: The DoS attack in a support layer is related to the network layer. An attacker sends a large amount of data to make network traffic inundated. Thus, the massive consumption of system resources exhausts the IoT and makes the user not capable of accessing the system.
- Malicious Insider Attack: It occurs from the inside of an IoT environment to access the personal information of users. It is performed by an authorized user to access the information of other user. It is a very different and complex attack that requires different mechanisms to prevent the threat [47,48].
3.3. Five Layer Architecture
3.3.1. Processing Layer
- Exhaustion: An attacker uses exhaustion to disturb the processing of IoT structure. It occurs as an after-effect of attacks, such as DoS attack in which an attacker sends the victim many requests to make the network unavailable for users. It could be a result of other attacks that aim to exhaust the system resources, such as battery and memory resources. IoT has a distributed nature; therefore, it does not have a high amount of hazards. It is much easier to implement protecting procedures against it [52].
- Malwares: It is an attack on the confidentiality of the information of users. It refers to the application of viruses, spyware, adware, Trojans horses and worms to interact with the system. It takes the form of executable codes, scripts and contents. It acts against the requirements of system to steal the confidentially of information [53].
3.3.2. Business Layer
- Business Logic Attack: It takes advantage of a flaw in a programming. It controls and manages the exchange of information between a user and a supporting database of an application. There are several common flaws in the business layer, such as improper coding by a programmer, password recovery validation, input validation, and encryption techniques [54].
4. Security Issues in Communication Technologies of IoT
4.1. ZigBee Technology
4.2. Bluetooth Technology
4.3. Radio Frequency Identification
4.4. Wireless Sensor Network
4.5. Wireless Fidelity (Wi-Fi)
4.6. 5G Networks
5. Security Mechanisms for IoT
5.1. Encryption and Hashed Based Security
5.2. Public Key Infrastructure (PKI) Like Protocol
5.3. Secure Authorization Mechanism with OAuth (Open Authorization)
- Which users have rights to access the specific information?
- What should be a mechanism to access the services?
- Which types of operation that can be performed by the users?
5.4. Lightweight Cryptographic Algorithms
5.4.1. Symmetric Key Lightweight Cryptographic Algorithm
5.4.2. Public Key Lightweight Cryptographic Algorithm
5.4.3. Cryptographic Hash Functions
5.5. Embedded Security Framework
5.5.1. User Identification
5.5.2. Identity Management
5.5.3. Secure Data Communication
5.5.4. Secure Network
5.5.5. Secure Storage
5.5.6. Secure Software Execution Environment
5.5.7. Secure Contents
5.5.8. Tamper Resistance
- Security: It provides security to the information of users in a form of lightweight cryptography. It is used to convert a message into cipher text to prevent attackers. It consumes less power and less memory to convert an original message into cipher text. It does not require high processing speed.
- Secure Operating System: It provides secure operations to ensure a secure communication between two parties by providing secure booting, secure execution environment and secure contents.
- Physical Protection: It provides physical security to the secret keys. The purpose of protecting it is to keep the secret keys from the attackers so that they cannot access the messages.
- Secure Storage: It protects the information of users stored in random access memory (RAM), read only memory (ROM) and any other secondary storage.
5.6. Identity Management Framework
5.7. Risk-Based Adaptive Framework
5.8. Association of SDN with IoT
5.9. Cooperation of Nodes Based Communication Protocol
5.10. Reputation System Based Mechanism
5.11. Cluster Based Intrusion Detection and Prevention System
5.12. Preference Based Privacy Protection Method
5.13. Access Control Mechanisms
5.14. OpenHab Technology
5.15. IoTOne Technology
5.15.1. Device Compatibility
5.15.2. User Friendly Environment
5.15.3. Security
5.16. Virtual Identity (VID) Framework
5.17. Identity-Based Personal Location System
5.17.1. Registration Subsystem
5.17.2. User Authentication Subsystem
5.17.3. Policy Subsystem
5.17.4. Client Subsystem
6. Improved Layered Architecture of IoT
- Perception Layer
- Observer Layer
- Processing Layer
- Security Layer
- Network Layer
- Application Layer
6.1. Perception Layer
6.2. Observer Layer
6.3. Processing Layer
6.4. Security Layer
6.5. Network Layer
6.6. Application Layer
7. Key Challenges and Future Directions
7.1. Poor Management
7.2. Naming and Identity Management
7.3. Trust Management and Policy
7.4. Big Data
7.5. Security
7.6. Storage
7.7. Authentication and Authorization
7.8. Secure Network
8. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Internet Users. Available online: http://www.Internetlivestats.com/Internet-users/ (accessed on 14 December 2017).
- Global Internet Usage. Available online: https://www.en.wikipedia.org/wiki/Global_Internet_usage/ (accessed on 14 December 2017).
- Oppitz, M.; Tomsu, P. Internet of Things. In Inventing the Cloud Century; Springer: Cham, Switzerland, 2018; pp. 435–469. [Google Scholar]
- Zhang, D.; Yang, L.T.; Chen, M.; Zhao, S.; Guo, M.; Zhang, Y. Real-time locating systems using active RFID for Internet of Things. IEEE Syst. J. 2016, 10, 1226–1235. [Google Scholar] [CrossRef]
- Nagashree, R.N.; Rao, V.; Aswini, N. Near field communication. Int. J. Wirel. Microw. Technol. (IJWMT) 2014, 4, 20. [Google Scholar]
- Whitmore, A.; Agarwal, A.; Da Xu, L. The Internet of Things—A survey of topics and trends. Inf. Syst. Front. 2015, 17, 261–274. [Google Scholar] [CrossRef]
- Al-Fuqaha, A.; Guizani, M.; Mohammadi, M.; Aledhari, M.; Ayyash, M. Internet of things: A survey on enabling technologies, protocols, and applications. IEEE Commun. Surv. Tutor. 2015, 17, 2347–2376. [Google Scholar] [CrossRef]
- Mishra, D.; Gunasekaran, A.; Childe, S.J.; Papadopoulos, T.; Dubey, R.; Wamba, S. Vision, applications and future challenges of Internet of Things: A bibliometric study of the recent literature. Ind. Manag. Data Syst. 2016, 116, 1331–1355. [Google Scholar] [CrossRef]
- Islam, S.R.; Kwak, D.; Kabir, M.H.; Hossain, M.; Kwak, K.S. The Internet of things for health care: A comprehensive survey. IEEE Access 2015, 3, 678–708. [Google Scholar] [CrossRef]
- Khan, I.U.; Shahzad, M.U.; Hassan, M.A. Internet of Things (IoTs): Applications in Home Automation. IJSEAT 2017, 5, 79–84. [Google Scholar]
- Memon, M.H.; Kumar, W.; Memon, A.; Chowdhry, B.S.; Aamir, M.; Kumar, P. Internet of Things (IoT) enabled smart animal farm. In Proceedings of the 3rd International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, India, 16–18 March 2016; pp. 2067–2072. [Google Scholar]
- Bi, Z.; Liu, Y.; Krider, J.; Buckland, J.; Whiteman, A.; Beachy, D.; Smith, J. Real-Time Force Monitoring of Smart Grippers for Internet of Things (IoT) Applications. J. Ind. Inf. Integr. 2018. [Google Scholar] [CrossRef]
- Gao, C.; Ling, Z.; Yuan, Y. The research and implement of smart home system based on Internet of things. In Proceedings of the 2011 International Conference on Electronics, Communications and Control (ICECC), Ningbo, China, 9–11 September 2011; pp. 2944–2947. [Google Scholar]
- Perera, C.; Zaslavsky, A.; Christen, P.; Georgakopoulos, D. Sensing as a service model for smart cities supported by Internet of things. Trans. Emerg. Telecommun. Technol. 2014, 25, 81–93. [Google Scholar] [CrossRef]
- Zanella, A.; Bui, N.; Castellani, A.; Vangelista, L.; Zorzi, M. Internet of Things for smart cities. IEEE Internet Things J. 2014, 1, 22–32. [Google Scholar] [CrossRef]
- Zhang, M.; Yu, T.; Zhai, G.F. Smart transport system based on “The Internet of Things”. Appl. Mech. Mater. 2011, 48, 1073–1076. [Google Scholar] [CrossRef]
- Zhou, Z.; Zhou, Z. Application of Internet of Things in agriculture products supply chain management. In Proceedings of the 2012 International Conference on Control Engineering and Communication Technology (ICCECT), Liaoning, China, 7–9 December 2012; pp. 259–261. [Google Scholar]
- Internet of Things (IoT) Devices. Available online: http://businessresearcher.sagepub.com/sbr-1863-102197-2772812/20170306/more-than-28-billion-devices-connect-via-internet-of-things (accessed on 16 December 2017).
- Yaqoob, I.; Ahmed, E.; Hashem, I.A.T.; Ahmed, A.I.A.; Gani, A.; Imran, M.; Guizani, M. Internet of Things Architecture: Recent Advances, Taxonomy, Requirements, and Open Challenges. IEEE Wirel. Commun. 2017, 24, 10–16. [Google Scholar] [CrossRef]
- Jing, Q.; Vasilakos, A.V.; Wan, J.; Lu, J.; Qiu, D. Security of the Internet of things: Perspectives and challenges. Wirel. Netw. 2014, 20, 2481–2501. [Google Scholar] [CrossRef]
- Sicari, S.; Rizzardi, A.; Grieco, L.A.; Coen-Porisini, A. Security, privacy and trust in Internet of Things: The road ahead. Comput. Netw. 2015, 76, 146–164. [Google Scholar] [CrossRef]
- Koshizuka, N.; Sakamura, K. Ubiquitous ID: Standards for ubiquitous computing and the Internet of Things. IEEE Pervasive Comput. 2010, 9, 98–101. [Google Scholar] [CrossRef]
- Want, R. An introduction to RFID technology. IEEE Pervasive Comput. 2006, 5, 25–33. [Google Scholar] [CrossRef]
- Want, R. Near field communication. IEEE Pervasive Comput. 2011, 10, 4–7. [Google Scholar] [CrossRef]
- McDermott-Wells, P. What is bluetooth? IEEE Potentials 2004, 23, 33–35. [Google Scholar] [CrossRef]
- Ferro, E.; Potorti, F. Bluetooth and Wi-Fi wireless protocols: A survey and a comparison. IEEE Wirel. Commun. 2005, 12, 12–26. [Google Scholar] [CrossRef]
- Crosby, G.V.; Vafa, F. Wireless sensor networks and LTE-A network convergence. In Proceedings of the IEEE 38th Conference on Local Computer Networks (LCN), Sydney, Australia, 21–24 October 2013; pp. 731–734. [Google Scholar]
- Levis, P.; Madden, S.; Polastre, J.; Szewczyk, R.; Whitehouse, K.; Woo, A.; Gay, D.; Hill, J.; Welsh, M.; Brewer, E.; et al. TinyOS: An operating system for sensor networks. Ambient Intell. 2005, 35, 115–148. [Google Scholar]
- Cao, Q.; Abdelzaher, T.; Stankovic, J.; He, T. The liteos operating system: Towards unix-like abstractions for wireless sensor networks. In Proceedings of the International Conference on Information Processing in Sensor Networks, 2008 (IPSN’08), St. Louis, MO, USA, 22–24 April 2008; pp. 233–244. [Google Scholar]
- Xing, X.J.; Wang, J.L.; Li, M.D. Services and key technologies of the Internet of Things. ZTE Commun. 2010, 2, 011. [Google Scholar]
- Gigli, M.; Koo, S. Internet of things: Services and applications categorization. Adv. Internet Things 2011, 1, 27. [Google Scholar] [CrossRef]
- Mashal, I.; Alsaryrah, O.; Chung, T.Y.; Yang, C.Z.; Kuo, W.H.; Agrawal, D.P. Choices for interaction with things on Internet and underlying issues. Ad Hoc Netw. 2015, 28, 68–90. [Google Scholar] [CrossRef]
- Miao, Y.; Bu, Y.X. Research on the architecture and key technology of Internet of Things (IoT) applied on smart grid. In Proceedings of the 2010 International Conference on Advances in Energy Engineering (ICAEE), Beijing, China, 19–20 June 2010; pp. 69–72. [Google Scholar]
- Said, O.; Masud, M. Towards Internet of things: Survey and future vision. Int. J. Comput. Netw. 2013, 5, 1–17. [Google Scholar]
- Suo, H.; Wan, J.; Zou, C.; Liu, J. Security in the Internet of things: A review. In Proceedings of the 2012 International Conference on Computer Science and Electronics Engineering (ICCSEE), Hangzhou, China, 23–25 March 2012; Volume 3, pp. 648–651. [Google Scholar]
- Kozlov, D.; Veijalainen, J.; Ali, Y. Security and privacy threats in IoT architectures. In Proceedings of the 7th International Conference on Body Area Networks, Oslo, Norway, 24–26 February 2012; ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering): Brussels, Belgium, 2012; pp. 256–262. [Google Scholar]
- Xiaohui, X. Study on security problems and key technologies of the Internet of things. In Proceedings of the 5th International Conference on Computational and Information Sciences (ICCIS), Shiyan, China, 21–23 June 2013; pp. 407–410. [Google Scholar]
- Bharathi, M.V.; Tanguturi, R.C.; Jayakumar, C.; Selvamani, K. Node capture attack in Wireless Sensor Network: A survey. In Proceedings of the 2012 IEEE International Conference on Computational Intelligence & Computing Research (ICCIC), Coimbatore, India, 18–20 December 2012; pp. 1–3. [Google Scholar]
- Puthal, D.; Nepal, S.; Ranjan, R.; Chen, J. Threats to networking cloud and edge datacenters in the Internet of Things. IEEE Cloud Comput. 2016, 3, 64–71. [Google Scholar] [CrossRef]
- Brumley, D.; Boneh, D. Remote timing attacks are practical. Comput. Netw. 2005, 48, 701–716. [Google Scholar] [CrossRef] [Green Version]
- Prabhakar, S. Network Security in Digitalization: Attacks and Defence. Int. J. Res. Comput. Appl. Robot. 2017, 5, 46–52. [Google Scholar]
- Conti, M.; Dragoni, N.; Lesyk, V. A survey of man in the middle attacks. IEEE Commun. Surv. Tutor. 2016, 18, 2027–2051. [Google Scholar] [CrossRef]
- Exploit Attack in Network Layer. Available online: http://searchsecurity.techtarget.com/definition/exploit (accessed on 6 January 2018).
- Ali, B.; Awad, A.I. Cyber and Physical Security Vulnerability Assessment for IoT-Based Smart Homes. Sensors 2018, 18, 817. [Google Scholar] [CrossRef] [PubMed]
- Gupta, S.; Gupta, B.B. Cross-Site Scripting (XSS) attacks and defense mechanisms: Classification and state-of-the-art. Int. J. Syst. Assur. Eng. Manag. 2017, 8, 512–530. [Google Scholar] [CrossRef]
- Darwish, D. Improved Layered Architecture for Internet of Things. Int. J. Comput. Acad. Res. (IJCAR) 2015, 4, 214–223. [Google Scholar]
- Sanzgiri, A.; Dasgupta, D. Classification of insider threat detection techniques. In Proceedings of the 11th Annual Cyber and Information Security Research Conference, Oak Ridge, TN, USA, 5–7 April 2016; ACM: New York, NY, USA, 2016; p. 25. [Google Scholar]
- Nurse, J.R.; Erola, A.; Agrafiotis, I.; Goldsmith, M.; Creese, S. Smart insiders: Exploring the threat from insiders using the Internet-of-things. In Proceedings of the 2015 International Workshop on Secure Internet of Things (SIoT), Vienna, Austria, 21–25 September 2015; pp. 5–14. [Google Scholar]
- Madakam, S.; Ramaswamy, R.; Tripathi, S. Internet of Things (IoT): A literature review. J. Comput. Commun. 2015, 3, 164. [Google Scholar] [CrossRef]
- Khan, R.; Khan, S.U.; Zaheer, R.; Khan, S. Future Internet: The Internet of things architecture, possible applications and key challenges. In Proceedings of the 2012 10th International Conference on Frontiers of Information Technology (FIT), Islamabad, India, 17–19 December 2012; pp. 257–260. [Google Scholar]
- Sethi, P.; Sarangi, S.R. Internet of Things: Architectures, Protocols, and Applications. J. Electr. Comput. Eng. 2017, 2017, 9324035. [Google Scholar] [CrossRef]
- Ashraf, Q.M.; Habaebi, M.H. Autonomic schemes for threat mitigation in Internet of Things. J. Netw. Comput. Appl. 2015, 49, 112–127. [Google Scholar] [CrossRef]
- Canzanese, R.; Kam, M.; Mancoridis, S. Toward an automatic, online behavioral malware classification system. In Proceedings of the IEEE 7th International Conference on Self-Adaptive and Self-Organizing Systems (SASO), Philadelphia, PA, USA, 9–13 September 2013; pp. 111–120. [Google Scholar]
- Business Logic Attack. Available online: http://whatis.techtarget.com/definition/business-logic-attack (accessed on 6 January 2018).
- Bilge, L.; Dumitras, T. Before we knew it: An empirical study of zero-day attacks in the real world. In Proceedings of the 2012 ACM Conference on Computer and Communications Security, Raleigh, NC, USA, 16–18 October 2012; ACM: New York, NY, USA, 2012; pp. 833–844. [Google Scholar]
- Kaur, R.; Singh, M. A survey on zero-day polymorphic worm detection techniques. IEEE Commun. Surv. Tutor. 2014, 16, 1520–1549. [Google Scholar] [CrossRef]
- Wang, W.; He, G.; Wan, J. Research on Zigbee wireless communication technology. In Proceedings of the 2011 International Conference on Electrical and Control Engineering (ICECE), Yichang, China, 16–18 September 2011; pp. 1245–1249. [Google Scholar]
- Zillner, T. Zigbee Exploited—the Good, the Bad and the Ugly. Available online: https://www.blackhat.com/docs/us-15/materials/us-15-Zillner-ZigBee-Exploited-The-Good-The-Bad-And-The-Ugly.pdf (accessed on 6 January 2018).
- Peng, C.; Huang, J. A home energy monitoring and control system based on ZigBee technology. Int. J. Green Energy 2016, 13, 1615–1623. [Google Scholar] [CrossRef]
- Talaviya, G.; Ramteke, R.; Shete, A.K. Wireless fingerprint based college attendance system using Zigbee technology. Int. J. Eng. Adv. Technol. (IJEAT) 2013, 2249, 8958. [Google Scholar]
- Salleh, A.; Aziz, A.; Abidin, M.Z.; Misran, M.H.; Mohamad, N.R. Development of greenhouse monitoring using wireless sensor network through ZigBee technology. Int. J. Eng. Sci. Invent. (IJESI) 2013, 2, 6–12. [Google Scholar]
- Padgette, J.; Scarfone, K.; Chen, L. Guide to Bluetooth Security; National Institute of Standards and Technology: Gaithersburg, MD, USA, 2012. [Google Scholar]
- Cabero, J.M.; Molina, V.; Urteaga, I.; Liberal, F.; Martin, J.L. Acquisition of human traces with Bluetooth technology: Challenges and proposals. Ad Hoc Netw. 2014, 12, 2–16. [Google Scholar] [CrossRef]
- Asadullah, M.; Ullah, K. Smart home automation system using Bluetooth technology. In Proceedings of the 2017 International Conference on Innovations in Electrical Engineering and Computational Technologies (ICIEECT), Karachi, Pakistan, 5–7 April 2017; pp. 1–6. [Google Scholar]
- Diaz, J.J.V.; Gonzalez, A.B.R.; Wilby, M.R. Bluetooth Traffic Monitoring Systems for Travel Time Estimation on Freeways. IEEE Trans. Intell. Transp. Syst. 2016, 17, 123–132. [Google Scholar] [CrossRef]
- Morshed, M.M.; Atkins, A.; Yu, H. Privacy and security protection of RFID data in e-passport. In Proceedings of the 2011 5th International Conference on Software, Knowledge Information, Industrial Management and Applications (SKIMA), Benevento, Italy, 8–11 September 2011; pp. 1–7. [Google Scholar]
- Khoo, B. RFID as an enabler of the Internet of things: Issues of security and privacy. In Proceedings of the 2011 International Conference on Internet of Things (iThings/CPSCom) and 4th International Conference on Cyber, Physical and Social Computing, Dalian, China, 19–22 October 2011; pp. 709–712. [Google Scholar]
- Amendola, S.; Lodato, R.; Manzari, S.; Occhiuzzi, C.; Marrocco, G. RFID technology for IoT-based personal healthcare in smart spaces. IEEE Internet Things J. 2014, 1, 144–152. [Google Scholar] [CrossRef]
- Hutabarat, D.P.; Patria, D.; Budijono, S.; Saleh, R. Human tracking application in a certain closed area using RFID sensors and IP camera. In Proceedings of the 2016 3rd International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE), Semarang, Indonesia, 19–20 October 2016; pp. 11–16. [Google Scholar]
- Zou, Y.; Xiao, J.; Han, J.; Wu, K.; Li, Y.; Ni, L.M. Grfid: A device-free rfid-based gesture recognition system. IEEE Trans. Mob. Comput. 2017, 16, 381–393. [Google Scholar] [CrossRef]
- Fadel, E.; Gungor, V.C.; Nassef, L.; Akkari, N.; Malik, M.A.; Almasri, S.; Akyildiz, I.F. A survey on wireless sensor networks for smart grid. Comput. Commun. 2015, 71, 22–33. [Google Scholar] [CrossRef]
- Jaladi, A.R.; Khithani, K.; Pawar, P.; Malvi, K.; Sahoo, G. Environmental Monitoring Using Wireless Sensor Networks (WSN) based on IOT. Int. Res. J. Eng. Technol. 2017, 4, 1371–7378. [Google Scholar]
- Butun, I.; Morgera, S.D.; Sankar, R. A survey of intrusion detection systems in wireless sensor networks. IEEE Commun. Surv. Tutor. 2014, 16, 266–282. [Google Scholar] [CrossRef]
- Can, O.; Sahingoz, O.K. A survey of intrusion detection systems in wireless sensor networks. In Proceedings of the 6th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO), Istanbul, Turkey, 27–29 May 2015; pp. 1–6. [Google Scholar]
- Drira, W.; Renault, E.; Zeghlache, D. Towards a secure social sensor network. In Proceedings of the 2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Shanghai, China, 18–21 December 2013; pp. 24–29. [Google Scholar]
- Grabovica, M.; Popic, S.; Pezer, D.; Knezevic, V. Provided security measures of enabling technologies in Internet of Things (IoT): A survey. In Proceedings of the Zooming Innovation in Consumer Electronics International Conference (ZINC), Novi Sad, Serbia, 1–2 June 2016; pp. 28–31. [Google Scholar]
- Yang, C.; Shao, H.R. WiFi-based indoor positioning. IEEE Commun. Mag. 2015, 53, 150–157. [Google Scholar] [CrossRef]
- Liu, H.H. The Quick Radio Fingerprint Collection Method for a WiFi-Based Indoor Positioning System. Mob. Netw. Appl. 2017, 22, 61–71. [Google Scholar] [CrossRef]
- Wenbo, Y.; Quanyu, W.; Zhenwei, G. Smart home implementation based on Internet and WiFi technology. In Proceedings of the 34th Chinese Control Conference (CCC), Hangzhou, China, 28–30 July 2015; pp. 9072–9077. [Google Scholar]
- Fan, Y.J.; Yin, Y.H.; Da Xu, L.; Zeng, Y.; Wu, F. IoT-based smart rehabilitation system. IEEE Trans. Ind. Inf. 2014, 10, 1568–1577. [Google Scholar]
- Akpakwu, G.A.; Silva, B.J.; Hancke, G.P.; Abu-Mahfouz, A.M. A survey on 5G networks for the Internet of Things: Communication technologies and challenges. IEEE Access 2018, 6, 3619–3647. [Google Scholar] [CrossRef]
- Nunez, M. What Is 5G and How Will It Make My Life Better? Available online: https://gizmodo.com/what-is-5g-andhow-will-it-make-my-life-better-1760847799 (accessed on 26 January 2018).
- Global mobile Suppliers Association. The Road to 5G: Drivers, Applications, Requirements and Technical Development; Global Mobile Suppliers Association: Surrey, UK, 2015. [Google Scholar]
- Li, S.; Xu, L.D.; Zhao, S. 5G internet of things: A survey. J. Ind. Inf. Integr. 2018. [Google Scholar] [CrossRef]
- Kumar, S.A.; Vealey, T.; Srivastava, H. Security in Internet of things: Challenges, solutions and future directions. In Proceedings of the 49th Hawaii International Conference on System Sciences (HICSS), Koloa, HI, USA, 5–8 January 2016; pp. 5772–5781. [Google Scholar]
- Li, F.; Xiong, P. Practical secure communication for integrating wireless sensor networks into the Internet of things. IEEE Sens. J. 2013, 13, 3677–3684. [Google Scholar] [CrossRef]
- Sundaram, B.V.; Ramnath, M.; Prasanth, M.; Sundaram, V. Encryption and hash based security in Internet of things. In Proceedings of the 3rd International Conference on Signal Processing, Communication and Networking (ICSCN), Chennai, India, 26–28 March 2015; pp. 1–6. [Google Scholar]
- Weber, R.H. Internet of Things–New security and privacy challenges. Comput. Law Secur. Rev. 2010, 26, 23–30. [Google Scholar] [CrossRef]
- Li, Z.; Yin, X.; Geng, Z.; Zhang, H.; Li, P.; Sun, Y.; Zhang, H.; Li, L. Research on PKI-like Protocol for the Internet of Things. In Proceedings of the 5th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA), Hong Kong, China, 16–17 January 2013; pp. 915–918. [Google Scholar]
- The OAuth 1.0 Protocol. Available online: http://tools.ietf.org/html/rfc5849 (accessed on 6 January 2018).
- Cirani, S.; Ferrari, G.; Veltri, L. Enforcing security mechanisms in the IP-based Internet of things: An algorithmic overview. Algorithms 2013, 6, 197–226. [Google Scholar] [CrossRef]
- Eisenbarth, T.; Kumar, S. A survey of lightweight-cryptography implementations. IEEE Des. Test Comput. 2007, 24, 522–533. [Google Scholar] [CrossRef]
- Fathy, A.; Tarrad, I.F.; Hamed, H.F.; Awad, A.I. Advanced encryption standard algorithm: Issues and implementation aspects. In Proceedings of the International Conference on Advanced Machine Learning Technologies and Applications, Cairo, Egypt, 8–10 December 2012; Springer: Berlin/Heidelberg, Germany, 2012; pp. 516–523. [Google Scholar]
- King, J.; Awad, A.I. A distributed security mechanism for resource-constrained IoT devices. Informatica 2016, 40, 133–143. [Google Scholar]
- Rivest, R.L.; Shamir, A.; Adleman, L. A method for obtaining digital signatures and public-key cryptosystems. Commun. ACM 1978, 21, 120–126. [Google Scholar] [CrossRef] [Green Version]
- Koblitz, N. Elliptic curve cryptosystems. Math. Comput. 1987, 48, 203–209. [Google Scholar] [CrossRef]
- American National Standards Institute. Available online: http://www.ansi.org (accessed on 31 January 2018).
- Institute of Electrical and Electronics Engineers. Available online: http://www.ieee.org (accessed on 31 January 2018).
- International Organization for Standardization. Available online: https://www.iso.org/home.html (accessed on 31 January 2018).[Green Version]
- Standards for Efficient Cryptography Group. Available online: http://secs.org (accessed on 31 January 2018).
- National Institute of Standards and Technology. Available online: http://www.nist.gov (accessed on 31 January 2018).
- Ravi, S.; Raghunathan, A.; Kocher, P.; Hattangady, S. Security in embedded systems: Design challenges. ACM Trans. Embedded Comput. Syst. (TECS) 2004, 3, 461–491. [Google Scholar] [CrossRef]
- Babar, S.; Stango, A.; Prasad, N.; Sen, J.; Prasad, R. Proposed embedded security framework for Internet of Things (IoT). In Proceedings of the 2nd International Conference on Wireless Communication, Vehicular Technology, Information Theory and Aerospace & Electronic Systems Technology (Wireless VITAE), Chennai, India, 28 February–3 March 2011; pp. 1–5. [Google Scholar]
- Horrow, S.; Sardana, A. Identity management framework for cloud based Internet of things. In Proceedings of the First International Conference on Security of Internet of Things, Kollam, India, 17–19 August 2012; pp. 200–203. [Google Scholar]
- Abie, H.; Balasingham, I. Risk-based adaptive security for smart IoT in eHealth. In Proceedings of the 7th International Conference on Body Area Networks, Oslo, Norway, 24–26 February 2012; ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering): Brussels, Belgium, 2012; pp. 269–275. [Google Scholar]
- Robertazzi, T.G. Software-Defined Networking. In Introduction to Computer Networking; Springer International Publishing: Cham, Switzerland, 2017; pp. 81–87. [Google Scholar]
- Al Shuhaimi, F.; Jose, M.; Singh, A.V. Software defined network as solution to overcome security challenges in IoT. In Proceedings of the 2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), Noida, India, 7–9 September 2016; pp. 491–496. [Google Scholar]
- Buchegger, S.; Le Boudec, J.Y. Performance analysis of the CONFIDANT protocol. In Proceedings of the 3rd ACM International Symposium on Mobile Ad Hoc Networking & Computing, Lausanne, Switzerland, 9–11 June 2002; ACM: New York, NY, USA, 2002; pp. 226–236. [Google Scholar]
- Michiardi, P.; Molva, R. Core: A collaborative reputation mechanism to enforce node cooperation in mobile ad hoc networks. In Advanced Communications and Multimedia Security; Springer: Boston, MA, USA, 2002; pp. 107–121. [Google Scholar]
- Oke, J.T.; Agajo, J.; Nuhu, B.K.; Kolo, J.G.; Ajao, L.A. Two Layers Trust-Based Intrusion Prevention System for Wireless Sensor Networks. Adv. Electr. Telecommun. Eng. 2018, 1, 23–29. [Google Scholar]
- Wenjun, L. IoT makes the City Smarter. Sci. Cult. 2010, 10, 12–13. [Google Scholar]
- Yang, Z. The development of the Internet of Things. J. Nanjing Univ. Posts Telecommun. (Soc. Sci.) 2010, 12, 8–9. [Google Scholar]
- Tao, H.; Peiran, W. Preference-based privacy protection mechanism for the Internet of things. In Proceedings of the 2010 International Symposium on Information Science and Engineering (ISISE), Shanghai, China, 24–26 December 2010; pp. 531–534. [Google Scholar]
- Bormann, C.; Castellani, A.P.; Shelby, Z. Coap: An application protocol for billions of tiny Internet nodes. IEEE Internet Comput. 2012, 16, 62–67. [Google Scholar] [CrossRef]
- Gupta, K.; Shukla, S. Internet of Things: Security challenges for next generation networks. In Proceedings of the 2016 International Conference on Innovation and Challenges in Cyber Security (ICICCS-INBUSH), Noida, India, 3–5 February 2016; pp. 315–318. [Google Scholar]
- Gyory, N.; Chuah, M. IoTOne: Integrated platform for heterogeneous IoT devices. In Proceedings of the 2017 International Conference on Computing, Networking and Communications (ICNC), Santa Clara, CA, USA, 26–29 January 2017; pp. 783–787. [Google Scholar]
- Sarma, A.; Matos, A.; Girao, J.; Aguiar, R.L. Virtual identity framework for telecom infrastructures. Wirel. Pers. Commun. 2008, 45, 521–543. [Google Scholar] [CrossRef]
- Hu, C.; Zhang, J.; Wen, Q. An identity-based personal location system with protected privacy in IoT. In Proceedings of the 4th IEEE International Conference on Broadband Network and Multimedia Technology (IC-BNMT), Shenzhen, China, 28–30 October 2011; pp. 192–195. [Google Scholar]
- Wu, M.; Lu, T.J.; Ling, F.Y.; Sun, J.; Du, H.Y. Research on the architecture of Internet of Things. In Proceedings of the 3rd International Conference on Advanced Computer Theory and Engineering (ICACTE), Chengdu, China, 20–22 August 2010; Volume 5, pp. V5-484–V5-487. [Google Scholar]
- Matharu, G.S.; Upadhyay, P.; Chaudhary, L. The Internet of Things: Challenges & security issues. In Proceedings of the 2014 International Conference on Emerging Technologies (ICET), Islamabad, Pakistan, 8–9 December 2014; pp. 54–59. [Google Scholar]
- Yan, Z.; Zhang, P.; Vasilakos, A.V. A survey on trust management for Internet of Things. J. Netw. Comput. Appl. 2014, 42, 120–134. [Google Scholar] [CrossRef]
- Roman, R.; Zhou, J.; Lopez, J. On the features and challenges of security and privacy in distributed Internet of Things. Comput. Netw. 2013, 57, 2266–2279. [Google Scholar] [CrossRef]
- Stankovic, J.A. Research directions for the Internet of Things. IEEE Internet Things J. 2014, 1, 3–9. [Google Scholar] [CrossRef]
- Borgohain, T.; Kumar, U.; Sanyal, S. Survey of security and privacy issues of Internet of Things. arXiv, 2015; arXiv:1501.02211. [Google Scholar]
- Shang, W.; Ding, Q.; Marianantoni, A.; Burke, J.; Zhang, L. Securing building management systems using named data networking. IEEE Netw. 2014, 28, 50–56. [Google Scholar]
- Liu, J.; Xiao, Y.; Chen, C.P. Authentication and access control in the Internet of things. In Proceedings of the 32nd International Conference on Distributed Computing Systems Workshops (ICDCSW), Macau, China, 18–21 June 2012; pp. 588–592. [Google Scholar]
- Zhang, Z.K.; Cho, M.C.Y.; Wang, C.W.; Hsu, C.W.; Chen, C.K.; Shieh, S. IoT security: Ongoing challenges and research opportunities. In Proceedings of the IEEE 7th International Conference on Service-Oriented Computing and Applications (SOCA), Matsue, Japan, 17–19 November 2014; pp. 230–234. [Google Scholar]
- Pawar, M.; Agarwal, J. A literature survey on security issues of WSN and different types of attacks in network. Indian J. Comput. Sci. Eng. 2017, 8, 80–83. [Google Scholar]
Home/Office | City | Transportation | Agriculture | Retail | |
---|---|---|---|---|---|
Number of Users | Very Few | Many | Many | Few | Few |
Communication | RFID and WSN | RFID and WSN | WSN | WSN | RFID and WSN |
Network | Small | Medium | Large | Medium | Small |
Internet | Wi-Fi, 3G, 4G | Wi-Fi, 3G, 4G | Wi-Fi, Satellite | Wi-Fi, Satellite | Wi-Fi, 3G, 4G |
Bandwidth | Small | Large | Medium | Medium | Small |
Test Beds | Smart Home | Smart Cities | Few | PSCM System | Retail centers |
[13] | [14,15] | [16] | [17] |
IoT Elements | Technologies | |
---|---|---|
Identification | Naming | Electronic, Product Code, Ucode |
Addressing | IPv4, and IPv6 | |
Sensing | Smart, Sensors, RFID Tags, Wearable Sensing Devices and Actuators | |
Communication | Radio Frequency Identification, Wireless Sensor Network, Near Field Communication (NFC), Bluetooth, Long Term Evolution (LTE) | |
Computation | Hardware | Audrino, Raspherry Pi, Intel Galil |
Software | Operating System | |
Services | Identity-Related, Information Aggregation, Collaborative-Aware and Ubiquitous | |
Semantics | RDF, OWL, EXI |
Technologies | Mechanism | Security | Applications | Characteristics | Drawbacks |
---|---|---|---|---|---|
ZigBee [57,58,59,60,61] | Wireless | Encryption, ntegrity | Home and Industry | Low consumption, Cheap | Fixed key |
Bluetooth [62,63,64,65] | Wireless | Encryption, Authentication | PDA, Mobiles and Laptops | Cable replacement, Low cost | Blue jacking, Bluesnarfing |
RFID [66,67,68,69,70] | Frequency waves | Encryption (AES, DES) | Health care | Data capturing with no duplication | No authorization |
WSN [71,72,73,74,75] | Wireless | Key, Encryption, Authentication | Buildings and Health care | Low Cost, Power, and Resilience | DOS attack |
Wi-Fi [76,77,78,79,80] | Radio Signals | Authentication, Authorization | PC, Phones and Cameras | Faster, Secure, Convenient | Eavesdropping |
5G Network [81,82,83,84] | Wireless | Authentication, Authorization | Phone, IoT and Multimedia | Faster, Secure, Convenient | Distributed DoS |
Method’s Name with Layer | Description | Issues Which It Address |
---|---|---|
Hashed Based Encryption [87] in Perception Layer | Hash Functions are used along encryption algorithms. | It is used to check the integrity of the message. |
PKI protocol [89] in Perception Layer | Base station sends message to destination and has the public key. | It does not compromise about security so, deliver message by itself. |
Secure Authorization Mechanism [90,91] in Perception Layer | Client - Server based System. It consists of two mechanisms; RBAC and ABAC. | Client send a request to server in order to fetch required resources. As a result, client get resources from server in a secure way. |
Lightweight Cryptographic Algorithms [92] in Perception Layer | Keys are used to convert messages. | It is used to convert a message from plain text to cipher by using symmetric, asymmetric key and hash functions. |
Embedded Security Framework [102,103] in Perception Layer | It provides not only security but also secure OS, memory and run time environment. | It provides secure secondary storage, run time environment and secure memory management in order to provide security to users. |
Identity Management Framework [104] in Network Layer | It has two fragments of it; identity and service and Communicate via them. | It confirms from identity module which has information of users in order to prevent the attacker. |
Risk based Adaptive Framework [105] in Network Layer | Four portions an each portion do their tasks and send the responsibility to other. | It stores the information about attack so when attacks come again, remove the attacks at second portion. |
SDN with IoT [107] in Network Layer | SDN is used for better performance in low cost and use less hardware resource. | All communication is occurred by SDN which provides security to both; the IoT IoT agent and controller. |
Cooperation of Nodes based Comm Protocol [108] in Network Layer | Node sends information to a trust manager to prevent the network from the intruders | It works on ad hoc communication environment. It detects and prevents the intruders. |
Reputation System based Mechanism [109] in Network Layer | Node maintains two data structures; the reputation table and watchdog mechanism to detect intruders. | It works on ad hoc communication environment. It prevents the intruder the reputation system. |
Cluster based Intrusion Detection and Prevention System [110] in Network Layer | Detects intruder by computing trust level. Trust level depends on packet generating, sending and receiving ratio. | It detects and prevents the intruder by dividing the network into cluster. |
Preference Based Privacy Protection [113] in Application Layer | Communication occurs by service provider, client and third party in secure environment. | A third party organization acts like a bridge between service provider and client. It also checks security provided by the service provider to client. |
Access Control Mechanism [115] in Application Layer | Simple Mechanism in order to provide security to users. | |
OpenHab [116] in Application Layer | Provide security so people started to use it. | Simple registration but does not support device mismatch. |
IoTOne [116] in Application Layer | Solve the issues occurred in the OpenHab Technology | Clients send the request to server in order to verify a user and provide the service by itself and also allow device mismatch. |
Identity based Security Framework [117,118] in Application Layer | It consists of four subsystem; registration, user authentication, policy and client. | Policy based Framework that controls and manages users as well as resources. Polices are described by the Admin |
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Burhan, M.; Rehman, R.A.; Khan, B.; Kim, B.-S. IoT Elements, Layered Architectures and Security Issues: A Comprehensive Survey. Sensors 2018, 18, 2796. https://doi.org/10.3390/s18092796
Burhan M, Rehman RA, Khan B, Kim B-S. IoT Elements, Layered Architectures and Security Issues: A Comprehensive Survey. Sensors. 2018; 18(9):2796. https://doi.org/10.3390/s18092796
Chicago/Turabian StyleBurhan, Muhammad, Rana Asif Rehman, Bilal Khan, and Byung-Seo Kim. 2018. "IoT Elements, Layered Architectures and Security Issues: A Comprehensive Survey" Sensors 18, no. 9: 2796. https://doi.org/10.3390/s18092796