Social learning for resilient data fusion against data falsification attacks
نویسندگان
چکیده
منابع مشابه
Social Learning Against Data Falsification in Sensor Networks
Although surveillance and sensor networks play a key role in Internet of Things, sensor nodes are usually vulnerable to tampering due to their widespread locations. In this letter we consider data falsification attacks where an smart attacker takes control of critical nodes within the network, including nodes serving as fusion centers. In order to face this critical security thread, we propose ...
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Cognitive radio (CR) network is an excellent solution to the spectrum scarcity problem. Cooperative spectrum sensing (CSS) has been widely used to precisely detect of primary user (PU) signals. The trustworthiness of the CSS is vulnerable to spectrum sensing data falsification (SSDF) attack. In an SSDF attack, some malicious users intentionally report wrong sensing results to cheat the fusion c...
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ژورنال
عنوان ژورنال: Computational Social Networks
سال: 2018
ISSN: 2197-4314
DOI: 10.1186/s40649-018-0057-7