Glazed windows and doors do not offer much security and privacy.Common services in apartments lead to lack of security due to a chance of hidden cameras inserted through common electricity ducts into anybodys houses.

Dear Umair Khalid,

the security aspects of IoT and 5G Networks is a new broad and interesting field of research. In this connection, see my answer below:

https://www.researchgate.net/post/Security_of_5G

For interesting Research Area (RA) and security topics in IoT see my answer below:

https://www.researchgate.net/post/Can_any_body_suggest_a_dissertation_question_related_to_Internet_of_things_and_Artificial_Intelligence

The following IoT security RAs are currently important:

RA5: Detecting anomalies in the IoT – Self Adaptive IDS (Intrusion Detection System)

RA6: Machine learning for IoT Security & Privaty support

RA7: Adaptive Trust Systems in the IoT; Adaptive trust estimation

Here are some sources of literature on these RAs.

Best regards

Anatol Badach

RA 5: Detecting anomalies in the IoT

V. A. Desnitsky, I. V. Kotenko and S. B. Nogin:Detection of Anomalies in Data for Monitoring of Security Components in the Internet of Thingshttps://ieeexplore.ieee.org/document/7190452/

R. Ferrando and P. Stacey: Classification of Device Behaviour in Internet of Things Infrastructures: Towards Distinguishing the Abnormal From Security Threatshttps://arrow.dit.ie/cgi/viewcontent.cgi?article=1156&context=engscheleart2

S. Ahmad, A. Lavin, S. Purdy and Z. Agha: Unsupervised real-time anomaly detection for streaming datahttps://www.sciencedirect.com/science/article/pii/S0925231217309864

S. Ahmad, S. Purdy: Real-Time Anomaly Detection for Streaming Analyticshttps://arxiv.org/pdf/1607.02480.pdf

H. HWJ Bosman, G. Iacca, A. Tejada, H. J. Wörtche, A. Liotta: Spatial anomaly detection in sensor networks using neighborhood informationhttps://www.sciencedirect.com/science/article/pii/S1566253516300252

H. HWJ Bosman: Anomaly detection in networked embedded sensor systemshttps://pure.tue.nl/ws/files/31668745/20160912_Bosman.pdfAnomaly

JP Vasseur and M.G. Seewald: Threat Detection and Mitigation for IoT Systems using Self Learning Networks (SLN)https://docbox.etsi.org/Workshop/2016/201606_SECURITYWS/S05_MITIGATINGMECHANISMS/CISCO_SEEWALD.pdf

RA6: Machine learning for IoT Security & Privaty support

F. Restuccia, Member, S. D’Oro and T. Melodia: "Securing the Internet of Things: New Perspectives and Research Challenges" https://arxiv.org/pdf/1803.05022.pdf

S. Kaplantzis, A. Shilton, N. Mani and Y. Sekercioglu: Detecting Selective Forwarding Attacks in Wireless Sensor Networks using Support Vector Machineshttps://pdfs.semanticscholar.org/1364/90cbfdec54735532a977a6d36d488eb14dca.pdf

J. Ca˜nedo and A. Skjellum: Using Machine Learning to Secure IoT Systemshttps://ieeexplore.ieee.org/document/7906930/

A. Balaji Buduru: An Adaptive Approach to Securing Ubiquitous Smart Devices in IoT Environment with Probabilistic User Behavior Predictionhttps://repository.asu.edu/attachments/176569/content/Buduru_asu_0010E_16584.pdf

RA7: Adaptive Trust Systems in the IoT; Adaptive trust estimation

H. Son, N. Kang, B. Gwak and D. Lee: An Adaptive IoT Trust Estimation Scheme Combining Interaction History and Stereotypical Reputationhttps://ieeexplore.ieee.org/document/7983132/

Respected Anatol Badach

Thank you for your detailed and well explained answer. I was searching for something like that.

Dear Umair Khalid,

There are currently numerous security proposals that rely on Blockchain technology. You can read our paper: "Bubbles of Trust: A decentralized blockchain-based authentication system for IoT"

Cheers

Dear Sir

a hybrid system is a solution ( software security protocols + hardware security protocol).

Blockchain technology is a trendto be used as a solution for many security breaks in IoT(public, private and hybrid ).

Please read recently published our future directions paper:

Transformative Effects of IoT, Blockchain and Artificial Intelligence on Cloud Computing: Evolution, Vision, Trends and Open Challenges

Available Online @ https://iamssgill.files.wordpress.com/2019/10/transformative_effects_survey.pdf

which gives you insights on evolution of cloud computing from 1958, vision, current Trends and open challenges of Cloud Computing and its paradigms (Fog, AI, Blockchain, IoT, Deep Learning, Security, SDN, Big Data, Energy, 5G/6G, Containers, Quantum Computing, Bitcoin currency, Software Engineering, SLA, QoS, AutoScaling, Applications, Data Science, Serverless and Security). Further, a conceptual model for cloud futurology is proposed.