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Side-weight inference is a common attack method.
where p ib is the probability of side-weight inference and δ is the experience value (here, δ=0.5), which denotes the probability threshold of side-weight inference.
In Equation 5, the side-weight inference probability of all roads would be computed.
Target 4 The algorithm has a good ability to defense the side-weight inference attack.
Meanwhile, the algorithm can defense the attack of side-weight inference and replay.
Obviously, the higher the average entropy H b, the more difficult the side-weight inference.
However, if the demand of l-diversity is too large, the requirement of the side-weight inference would be met.
Algorithms in [16, 17] do not consider the attack of side-weight inference, so their security is not enough.
If the user's distribution of each side is not the same, the user is easily attacked by side-weight inference.
2) How to guarantee that the server can defense the replay attack and side-weight inference attack effectively? .
This is because the algorithm in this paper need to consider the attack of side-weight inference.
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