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Description
Jamming is a deliberate attempt to disrupt wireless communication by transmitting interfering
signals on specific frequencies. With the growing reliance on wireless systems in critical
infrastructures, the threat of malicious signal interference has become a major concern for
security and defense. Traditional jamming devices block communication across wide
frequency ranges, but this often results in excessive collateral disruption. This paper focuses
on the design of a Jamming Response System (JRS) using microcontroller-based
architectures that introduces an adaptive and directional approach to signal jamming. The
system analyses the frequency spectrum, detects suspicious activity, and activates targeted
jamming only upon confirmation of a threat. This paper covers techniques such as frequency
monitoring, dynamic frequency locking, adaptive filtering, power modulation, and
directional antenna control for precision jamming. Recent advancements such as machine
learning-based anomaly detection are also discussed to enable the system to differentiate
between benign and malicious transmissions. The goal of this paper is to provide a theoretical
design and simulation framework for intelligent and responsible jamming systems,
highlighting their applications in cybersecurity, military defense, and critical
infrastructure protection. Comparative discussion of adaptive jamming with conventional
jamming methods is also included.
