Information-theoretic Key Encapsulation and its Application to Secure Communication
Bibliographic record
Abstract
A hybrid encryption scheme consists of a public-key part called the key encapsulation mechanism (KEM), that is used to generate and establish a shared secret key between two parties, and a (symmetric) secret-key part called the data encapsulation mechanism (DEM) that encrypts the data using the shared key. Hybrid encryption schemes are widely used for securing Internet communication. In this paper, we initiate the study of hybrid encryption in preprocessing model which assumes access to initial correlated variables by all parties (including the eavesdropper), and define information-theoretic KEM (iKEM) that together with a (computationally) secure DEM, results in a hybrid encryption scheme in preprocessing model. We define security of each building block, and prove a composition theorem that guarantees (computational) q-chosen-plaintext attack (CPA) security of the hybrid encryption system if the iKEM and the DEM satisfy q-chosen-encapsulation attack security and one-time security, respectively. We show that an iKEM can be realized by an information-theoretic one-way secret key agreement (OW-SKA) protocol where a single message is transmitted from Alice to Bob, with a new security definition that allows$q$queries to Alice. Using a OW-SKA that satisfies this new definition of security, effectively allows the established secret key to be used with a onetime symmetric key encryption system that can be implemented, for example, by XORing the output of a (computationally) secure pseudorandom generator with the message, to provide secure encryption of$q$arbitrary messages (polynomially bounded length). We discuss our results and directions for future work.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.004 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".