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A Security and Application of Wireless Sensor Network: A Comprehensive Study

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A comprehensive review of wireless sensor networks: Applications, challenges, radio technologies, and protocols

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Fadhil Mohammad Salman; A comprehensive review of wireless sensor networks: Applications, challenges, radio technologies, and protocols. AIP Conf. Proc. 4 December 2023; 2834 (1): 020021. https://doi.org/10.1063/5.0161523

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Recently, significant advances in digital sensing technology and wireless communications have led to the production of small-scale smart sensors that have the ability to sense physical changes in different environments and convert them into digital signals that are collected in one central location. These networks are called wireless sensor networks (WSNs) because they have the ability to wirelessly communicate with each other for the purpose of passing data between them and deliver it to the central station. Wireless sensor networks have great importance in human environments, as they are used to monitor and record physical changes in environments that are not accessible to humans, such as environments with very high temperatures, or in cases of chemical environmental pollution, in forests and seas as well as in deep layers of earth to monitor seismic and volcanic activity. In view of the great importance of wireless sensor networks and their obvious impact on human life, and for the purpose of providing researchers with brief and complete information about these networks, we have presented this paper that briefly reviews what sensor networks are, their specifications, applications and the challenges they face. This paper also included most of the radio communication techniques used in sensor architectures. As well as touching on the most important routing algorithms in "WSNs" and their classifications with a comparison of their performance. Finally, this paper provided an overview of research trends that could lead to significant technological development and beneficial growth to overcome the challenges of wireless sensor networks.

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Wireless Sensor Network Security Research and Challenges: A Backdrop

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• Dimple Juneja 3 ,
• Atul Sharma 3 &
• A. K Sharma 4  

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 169))

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• International Conference on High Performance Architecture and Grid Computing

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If sensor networks are to attain their potential, security is one of the most important aspects to be taken care of. The need for security in military applications is obvious, but even more benign uses, such as home health monitoring, habitat monitoring and sub-surface exploration require confidentiality. WSNs are perfect for detecting environmental, biological, or chemical threats over large scale areas, but maliciously induced false alarms could completely negate value of the system. The widespread deployment of sensor networks is directly related to their security strength. These stated facts form the basis for this survey paper. This paper present a brief overview of challenges in designing a security mechanism for WSN, classify different types of attacks and lists available protocols, while laying outline for proposed work.

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Juneja, D., Sharma, A., Kumar, A.: A Novel and Efficient Algorithm for Deploying Mobile Sensors in Subsurface. Computer and Information Science 3(2), 94–105 (2010); ISSN 1913-8989 (Print), ISSN 1913-8997 (Online)

Article   Google Scholar  

Juneja, D., Sharma, A., Kumar, A.: A Query Driven Routing Protocol for Wireless Sensor Nodes in Subsurface. International Journal of Engineering Science and Technology 2(6), 1836–1843; ISSN: 0975-5462

Google Scholar  

Juneja, D., Sharma, A., Kumar, A.: A Novel Application Of Extended Kalman Filter For Efficient Information Processing In Subsurfaces. International Journal of Computer Applications 17(2), 28–32 (2011); Published By FCS (Foundation of Computer Science, USA). ISSN: 0975-8887

Al-Sakib, Pathan, K., Lee, W., Hyung, Hong, S., Choong.: Security in Wireless Sensor Networks: Issues and Challenges. In: ICACT 2006 (2006)

Lu, B., Habetler, T.G., Harley, R.G., Gutiérrez, J.A.: Applying Wireless Sensor Networks in Industrial Plant Energy Management Systems – Part I: A Closed-Loop Scheme. In: Sensors, October 30 -November 3, pp. 145–150. IEEE, Los Alamitos (2005)

Virone, G., Wood, A., Selavo, L., Cao, Q., Fang, L., Doan, T., He, Z., Stankovic, J.A.: An Advanced Wireless Sensor Network for Health Monitoring. In: Transdisciplinary Conference on Distributed Diagnosis and Home Healthcare (D2H2), Arlington, VA, April 2-4 (2006)

Bokareva, T., Hu, W., Kanhere, S., Ristic, B., Gordon, N., Bessell, T., Rutten, M., Jha, S.: Wireless Sensor Networks for Battlefield Surveillance. In: Land Warfare Conference 2006, Brisbane, Australia (October 2006)

Mainwaring, A., Polastre, J., Szewczyk, R., Culler, D., Anderson, J.: Wireless Sensor Networks for Habitat Monitoring. In: ACM WSNA 2002, Atlanta, Georgia, USA, September 28, pp. 88–97 (2002)

Wireless Sensor Networks, http://en.wikipedia.org/wiki/Wireless_Sensor_Networks

Tiny Operating System, http://en.wikipedia.org/wiki/TinyOS

Sastry, N., Wagner, D.: Security considerations for IEEE 802.15.4 networks. In: Proceedings of the 2004 ACM Workshop on Wireless Security. ACM Press, New York (2004)

Malan, D., Welsh, M., Smith, M.: A public-key infrastructure for key distribution in TinyOS based on elliptic curve cryptography. In: Sensor and Ad Hoc Communications and Networks (2004)

Chan, H., Perrig, A., Song, D.: Random key predistribution schemes for sensor networks. In: Proceedings of the Symposium Security and Privacy (2003)

Du, W., Deng, J., Han, Y., Chen, S., Varshney, P.: A key management scheme for wireless sensor networks using deployment knowledge. In: INFOCOM 2004: Twenty-third AnnualJoint Conference of the IEEE Computer and Communications Societies (2004)

Eschenauer, L., Gligor, V.D.: A key-management scheme for distributed sensor networks. In: Proceedings of the 9th ACM Conference on Computer and Communications Security. ACM Press, New York (2002)

Wagner, D.: Resilient aggregation in sensor networks. In: SASN 2004: Proceedings of the 2004 ACM Workshop on Security of Ad Hoc and Sensor Networks (2004)

Du, W., Han, Y.S., Deng, J., Varshney, P.K.: A Pairwise key predistribution scheme for wireless sensor networks. In: Proceedings of the ACM Conference on Computer and Communications Security (2003)

Ye, F., Luo, H., Lu, S., Zhang, L.: Statistical en-route filtering of injected false data in Sensor Networks. In: Proceedings - IEEE INFOCOM (2004)

Hoger, K., Andreas, W.: Protocols and Architecture for Wireless Sensor Networks. John Wiley & Sons Ltd, Chichester (2005); ISBN: 0-470-09510-5

Perrig, R., Szewczyk, V., Wen, D., Culler, J.D.: SPINS: security protocols for sensor networks. In: Proceedings of ACM MobiCom 2001, Rome, Italy, pp. 189–199 (2001)

Raymond, D.R., Marchany, R.C., Brownfield, M.I., Midkiff, S.F.: Effects of Denial-of-Sleep Attacks on Wireless Sensor Network MAC Protocols. IEEE Transactions on Vehicular Technology 58(1), 367–380 (2009)

Wood, A.D., Stankovic, J.A.: Denial of Service in Sensor Networks. IEEE Computer 35(10), 48–56 (2002)

Brownfield, M., Gupta, Y., Davis, N.: Wireless sensor network denial of sleep attack. In: Proceedings from the Sixth Annual IEEE SMC Information Assurance Workshop, IAW 2005, pp. 356–364 (2005)

Wood, A.D., Stankovic, J.A.: Denial of Service in Sensor Networks. IEEE Computers, 54–62 (October 2002)

Padmavathi, G., Shanmugapriya, D.: A Survey of Attacks, Security Mechanisms and Challenges in Wireless Sensor Networks. International Journal of Computer Science and Information Security (IJCSIS) 4(1 & 2), 1–9 (2009)

Karlof, C., Wagner, D.: Secure routing in wireless sensor networks: attacks and countermeasures. In: Proceedings of the First IEEE International Workshop on Sensor Network Protocols and Applications, pp. 113–127 (2003)

Yu, B., Xiao, B.: Detecting selective forwarding attacks in wireless sensor networks. In: Proceedings of the Second International Workshop on Security in Systems and Networks (IPDPS 2006 Workshop), pp. 1–8 (2006)

Krontiris, I., Dimitriou, T.D., Giannetsos, T., Mpasoukos, M.: Intrusion detection of sinkhole attacks in wireless sensor networks. In: Kutyłowski, M., Cichoń, J., Kubiak, P. (eds.) ALGOSENSORS 2007. LNCS, vol. 4837, pp. 150–161. Springer, Heidelberg (2008)

Chapter   Google Scholar  

Newsome, E., Song, S.D., Perrig, A.: The sybil attack in sensor networks: analysis & defenses. In: IPSN 2004: Proceedings of the Third International Symposium on Information Processing in Sensor Networks, pp. 259–268. ACM Press, New York (2004)

Hu, Y.-C., Perrig, A., Johnson, D.B.: Wormhole detection in wireless ad hoc networks. Department of Computer Science, Rice University, Tech. Rep. TR01-384 (June 2002)

Tumrongwittayapak, C., Varakulsiripunth, R.: Detecting Sinkhole Attacks In Wireless Sensor Networks. In: Proceedings of the IEEE ICROS-SICE International Joint Conference, pp. 1966–1971 (2009)

Feng, Z., Leonidas, G.: Wireless Sensor Networks (An Information Processing Approach). Morgan Kaufmann Publisher under Elsevier; ISBN:1-55860-914-8

Deepak, G., Alberto, C., Wei, Y., Yan, Y., Jerry, Z., Deborah, E.: Networking Issues in Wireless Sensor Networks. Elsevier Science, Amsterdam (2003)

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MM Institute of Computer Technology & Business Management, MM University, Mullana (Ambala), Haryana, India

Dimple Juneja & Atul Sharma

YMCA University of Science & Technology, Faridabad, Haryana, India

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Archana Mantri , Suman Nandi  & Sandeep Kumar ,  & 

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Gaurav Kumar

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Juneja, D., Sharma, A., Sharma, A.K. (2011). Wireless Sensor Network Security Research and Challenges: A Backdrop. In: Mantri, A., Nandi, S., Kumar, G., Kumar, S. (eds) High Performance Architecture and Grid Computing. HPAGC 2011. Communications in Computer and Information Science, vol 169. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22577-2_55

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• IEEE Wireless Sensor Networks Projects

In the domain of Wireless Sensor Networks (WSN), there are several project topics that are progressing in contemporary years. The following are instances of project topics that have been investigated in IEEE publication and conferences and coordinate with current patterns in WSN study. Drop a message to us about your research queries let our experts take care of your work, you can be at ease.These projects act as a motivation for researchers, students, and experts those who explore to dedicate to the research domain:

• Energy-Efficient WSNs for Environmental Monitoring
• Description: To track ecological metrics like humidity, temperature, and level of air over wide regions, aim to formulate and apply a WSN framework enhanced for less power usage, by employing energy-harvesting mechanisms and effective data transmission protocols.
• Secure WSNs Using Blockchain Technology
• Description: In order to develop a decentralized and safe model for data transmission in WSNs, employ blockchain mechanism, thereby assuring data reliability and morality, which is specifically helpful in significant applications such as calamity management and healthcare tracking.
• Machine Learning-Based Anomaly Detection in WSNs
• Description: Intending to detect ecological variations or framework failures at an early stage, construct a machine learning system that works on cloud servers or network gateways in order to identify abnormalities in the data gathered by WSNs.
• WSN Integration with IoT for Smart Agriculture
• Description: For accurate farming, develop an incorporated IoT and WSN approach to enhance crop production and improve water usage by including weather data, autonomous irrigation framework and soil dampness sensors.
• Indoor Localization and Tracking Using WSNs
• Description: For applications like navigation assistance in wide buildings or asset monitoring in repositories, it is beneficial to deploy a WSN framework for precise indoor localization and monitoring by utilizing mechanisms such as Ultra-Wideband (UWB) or Received Signal Strength Indicator (RSSI).
• WSNs for Structural Health Monitoring
• Description: To identify cracks, vibrations, and other signals of architectural damage with actual-time notifying technologies, formulate a WSN model that employs sensors to track the architectural welfare of structure and buildings.
• Energy-Efficient Routing Protocols in WSNs
• Description: For solving trade-offs among network lifespan, energy usage, and data transmission consistency, explore and construct novel routing protocols that are enhanced for energy effectiveness in WSNs.
• Privacy-Preserving Data Aggregation in WSNs
• Description: Possibly, employing homomorphic encryption or safer multi-party computation algorithms, it is appreciable to investigate approaches for collecting data in WSNs in such a manner that conserves the confidentiality of the data resources.
• Cross-Layer Optimization Strategies for WSNs
• Description: By determining communications among various layers of network protocol stack, aim to research and apply cross-layer optimization policies that enhance the entire effectiveness of WSNs.
• Underwater Wireless Sensor Networks (UWSNs) for Oceanographic Data Collection
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What kinds of attacks can a wireless IDS detect?

To track wireless networks for doubtful actions and possible assaults, a Wireless Intrusion Detection System (WIDS) is formulated, thereby offering a significant layer of protection through identifying different kinds of assaults that are particularly designed or mainly efficient against wireless networks. Below are few of the types of assaults that a WIDS has the capability to identify:

• Unauthorized Access
• Description: To obtain access to wireless networks, approaches that are carried out by illicit users are detected. Generally, assaults against weak authentication technologies or utilizing risks in the network’s safety configuration are encompassed.
• Rogue Access Points
• Description: WIDS has the capability to identify illicit access points, possibly to grasp complicated data from wireless clients or to provide a deceptive into the network. Generally, it has been arranged within the scope of the network.
• Evil Twin Attacks
• Description: Malevolent access points are detected by WIDS, which deceive users into linking to them to interrupt data by imitating genuine ones with the similar SSID (Service Set Identifier).
• Denial of Service (DoS) and Distributed DoS (DDoS) Attacks
• Description: Identification of signal jamming or anomalous congestion trends that specifically intend to complicate the certain devices or network. To genuine users, the network or certain devices are inaccessible.
• Man-in-the-Middle (MitM) Attacks
• Description: Interruption approaches have to be recognized where the assaulter privately communicates and potentially modifies the interaction among two parties who trust that they are directly interacting with each other.
• MAC Spoofing
• Description: When an assaulter alters the Media Access Control (MAC) address of their device to imitate another device on the network, WIDS has the ability to identify this attack.
• Deauthentication and Disassociation Attacks
• Description: Detecting when an assaulter sends disassociation or deauthentication frames regularly to separate a client from an access point. Frequently, this is considered as a beginning to other assaults such as MitM.
• Eavesdropping/Sniffing
• Description: Wireless IDS contains the capability to track the passive assaults. In this kind of attack, the assaulters grasp data packets transmitted over the network to obtain complicated data.
• Network Injection Attacks
• Description: The illicit injection of packets into the network has to be recognized, that can be employed to interrupt congestion or to carry out spoofing or replay assaults.
• Description: Detecting approaches by moving around in a vehicle through utilizing mobile device or laptop in order to identify wireless networks to plan networks for upcoming assaults.
• SSID Cloaking
• Description: In order to conceal the SSID of an access point as a safety criterion, wireless IDS identifies approaches. At times, this can be utilized by assaulters to develop an evil twin access point.
• KRACK (Key Reinstallation Attacks)
• Description: In the WPA2 protocol, tracks the risks that can be implemented to decrypt replay attacks, hijack correlations, and network congestion.

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