Define (7). as the suspicious level of node at time slot, where is the type of node, which could be H(Honest) or M(Malicious), and is observations collected from time slot 1 to time slot.
In Always Adverse attack, an attacker firstly performs a local binary hypothesis testing between H0 and H1 by comparing its energy observation with a predefined threshold, with H0 denoting the case that the primary signal is absent and H1 otherwise; then, the malicious SU raises its observations when its local binary decision is H0 and decreases its observations when its decision is H1.
In particular, there are some malicious SUs reporting falsified observations to the FC to deteriorate the spectrum sensing performance.
Alas, anyone wanting malicious gossip and pointed observation will need to wait, presumably until Hillary has made her mind up and gone for President and succeeded or failed, or chosen not to run at all.
Compared to hard SSDF attack, soft SSDF attack is generally more powerful and elusory for its relatively larger value space[9 12], since malicious SUs falsify real energy observations, rather than binary decisions, to mislead the fusion center (FC).
Attackers with malicious intents may report the opposite of their observations in order to disrupt the operation of the CR network (i.e., reduce the protection of PUs or spectrum usage efficiency).
So a prolonged rogue signal on a group of sensors can cause a sharp contrast in local spectrum observation from the others, thus appearing malicious and no different than SSDF.
In CR environments, a SU can be fooled by malicious elements of its environment, as it relies on observation and possibly on cooperation for spectrum decision and learning.
On the other hand, CRN features also help to mitigate malicious manipulation using: The ability to collaborate for authentication of local observations that are used to form perceived environments.
Considering the previous observations, Fig. 3 highlights the time periods during which some malicious peripherals can initiate DMA requests.
By transmitting a message at a rate higher than the rate of the malicious node, the malicious node can learn almost nothing about the messages from its observations.
