Our fight against false information is spearheaded by fact-checkers. They investigate the veracity of claims and document their findings as fact-checking reports. With the rapid increase in the amount of false information circulating online, the use of automation in fact-checking processes aims to strengthen this ecosystem by enhancing scalability. Datasets containing fact-checked claims play a key role in developing such automated solutions. However, to the best of our knowledge, there is no fact-checking dataset at the ecosystem level, covering claims from a sufficiently long period of time and sourced from a wide range of actors reflecting the entire ecosystem that admittedly follows widely-accepted codes and principles of fact-checking.

We provide efficient constructions for trace-and-revoke systems with public traceability in the black-box confirmation model. Our constructions achieve adaptive security, are based on standard assumptions and achieve significant efficiency gains compared to previous constructions.

In Broadcast Encryption (BE) systems like Pay-TV, AACS, online content sharing and broadcasting, reducing the header length (communication overhead per session) is of practical interest. The Subset Difference (SD) scheme due to Naor-Naor-Lotspiech (NNL) is the most popularly used BE scheme. We introduce the$(a,b,\gamma)$augmented binary tree subset difference ($(a,b,\gamma)$-ABTSD) scheme which is a generalization of the NNL-SD scheme. By varying the parameters$(a,b,\gamma)$, it is possible to obtain$O(n\log n)$different schemes. The average header length achieved by the new schemes is smaller than all known schemes having the same decryption time as that of the NNL-SD scheme and achieving non-trivial trade-offs between the user storage and the header size. The amount of key material that a user is required to store increases. For the earlier mentioned applications, reducing header size and achieving fast decryption is perhaps more of a concern than the user storage.

Two key parameters of broadcast encryption (BE) schemes are the transmission size and the user storage. Naor-Naor-Lotspiech (2001) introduced the subset difference (SD) scheme achieving a good trade-off between these two parameters. Halevy-Shamir (2002) introduced the idea of layering to reduce user storage of the NNL scheme at the cost of increased transmission overhead. Here, we introduce several simple ideas to obtain new layering strategies with different trade-offs between user storage and transmission overhead. We define the notion of storage minimal layering and describe a dynamic programming algorithm to compute layering schemes for which the user storage is the minimum attainable using layerings. Further, the constrained minimization problem is considered. A method is described which yields BE schemes whose transmission overhead is not much more than the SD scheme but, whose user storage is still significantly lower. Finally, an$O(r\log^2 n)$algorithm is obtained to compute the average transmission overhead for any layering-based scheme where$r$out of$n$users are revoked. This algorithm works for any layering strategy and also for arbitrary number of users. The algorithm has been used here to generate all data for the average transmission overhead.