Playing Repeated Network Interdiction Games with Semi-Bandit Feedback

We study repeated network interdiction games with no prior knowledge of the adversary and the environment, which can model many real world network security domains. Existing works often require plenty of available information for the defender and neglect the frequent interactions between both players, which are unrealistic and impractical, and thus, are not suitable for our settings. As such, we provide the first defender strategy, that enjoys nice theoretical and practical performance guarantees, by applying the adversarial online learning approach. In particular, we model the repeated network interdiction game with no prior knowledge as an online linear optimization problem, for which a novel and efficient online learning algorithm, SBGA, is proposed, which exploits the unique semi-bandit feedback in network security domains. We prove that SBGA achieves sublinear regret against adaptive adversary, compared with both the best fixed strategy in hindsight and a near optimal adaptive strategy. Extensive experiments also show that SBGA significantly outperforms existing approaches with fast convergence rate.

Fully Secure Codes Based Tracing and Revoking Scheme with Constant Ciphertext

In broadcast encryption system certain users may leak their decryption keys to build pirate decoders, so traitor tracing is quite necessary. There exist many codes based traitor tracing schemes. As pointed out by Billet and Phan in ICITS 2008, these schemes lack revocation ability. The ability of revocation can disable identified malicious users and users who fail to fulfill the payments, so that the broadcast encryption system can be more practical. Recently, Zhao and Li presented a construction of codes based tracing and revoking scheme which achieves user revocation as well as traitor tracing. However, their scheme is only secure against chosen plaintext attacks under selective-adversary model with random oracle. In this paper, we obtain a new construction of codes based tracing and revoking scheme which is proved secure against chosen ciphertext attacks under adaptive-adversary model without random oracle. Our idea is to insert codeword into Boneh and Hamburgs identity based broadcast encryption scheme to retain the ability of user revocation and use Boneh and Naors method to trace traitors. Our fully secure scheme is roughly as efficient as Zhao and Lis scheme while the security is enhanced.

Optimal Resilient Dynamic Dictionaries⋆

In the resilient memory model any memory cell can get cor- rupted at any time, and corrupted cells cannot be distinguished from uncorrupted cells. An upper bound, , on the number of corruptions and O(1) reliable memory cells are provided. In this model, a data structure is denoted resilient if it gives the correct output on the set of uncor- rupted elements. We propose two optimal resilient static dictionaries, a randomized one and a deterministic one. The randomized dictionary supports searches in O(log n + ) expected time using O(log ) random bits in the worst case, under the assumption that corruptions are not performed by an adaptive adversary. The deterministic static dictionary supports searches in O(log n + ) time in the worst case. We also in- troduce a deterministic dynamic resilient dictionary supporting searches in O(log n + ) time in the worst case, which is optimal, and updates in O(log n + ) amortized time. Our dynamic dictionary supports range queries in O(log n + + k) worst case time, where k is the size of the output.