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The method of digital watermarking for improving objects based on clusters and perception values
Author(s) -
Parviz M. Shonazarov,
Fozil T. Kholov,
Bekhruz B. Saidov
Publication year - 2022
Publication title -
sistemy analiza i obrabotki dannyh
Language(s) - English
Resource type - Journals
eISSN - 2782-215X
pISSN - 2782-2001
DOI - 10.17212/2782-2001-2022-1-109-120
Subject(s) - computer science , cluster analysis , wireless sensor network , wireless , bandwidth (computing) , digital watermarking , computer network , real time computing , energy consumption , artificial intelligence , telecommunications , engineering , electrical engineering , image (mathematics)
One of the most important IoT concerns is resource constraints such as power supply, processing power, memory capacity, wireless range, and wireless bandwidth. Low bandwidth wireless routing requires multiple routing steps to reach a destination. The Internet of things (Internet of things, IoT) is a technology that consists of a set of objects that are connected via the Internet and collect information generated by sensors. IoT devices are devices that are networked and accessible to anyone and everything anytime and anywhere. Examples of such devices include temperature sensors, motion sensors, heart rate sensors, energy consumption sensors, etc. For example, a temperature sensor can be built into a thermostat, an indicator of the amount of electricity consumed in homes, and a traffic sensor at a traffic light. This article proposes a scheme based on fragile watermarking and improved clustering to resolve the conflict between security and limited perceptual resources. To improve security, we are developing a stochastic positioning strategy based on a clustering algorithm to compute the position embedded in the temporal dynamics of the data measurement. Thus, security vulnerabilities created by a stationary embedded situation can not only be effectively addressed but also result in zero data disturbance. Our research results show that the proposed algorithm can effectively integrate low-cost data, as well as reduce power consumption and increase network life.

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