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Kentaro Kita

Publications and source records attributed to Kentaro Kita.

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Lacan: Making Accountability in Anonymous Networks Real

Anonymity and accountability are essential properties for our everyday activity on the Internet. However, they appear contradictory, and their reconciliation remains far from reality. Existing approaches fall short in this regard, as they either rely on an on-path trustee, per-packet authorization, per-packet public-key cryptography, or per-session intervention by a central authority. We propose Lacan, a protocol that reconciles anonymity and accountability within a realistic design. In Lacan, a sender enjoys anonymity provided by on-path relays, as long as she complies with a contract established with the receiver. Upon a contract violation, the verifier, an off-path trustee on behalf of the receiver, links the malicious message to the sender's identity indirectly via the packet, path, and session, thereby reducing public-key operations from per-packet to per-session. This linkage remains robust even against malicious relays and receivers, grounded in our novel chain of successor proofs for accountable path reconstruction, together with traceable signatures, path validation, and key-committing encryption. We analyze the anonymity and accountability, implement the protocol, and evaluate the performance.

cs.NI

AI Security Map: Holistic Organization of AI Security Technologies and Impacts on Stakeholders

As the social implementation of AI has been steadily progressing, research and development related to AI security has also been increasing. However, existing studies have been limited to organizing related techniques, attacks, defenses, and risks in terms of specific domains or AI elements. Thus, it extremely difficult to understand the relationships among them and how negative impacts on stakeholders are brought about. In this paper, we argue that the knowledge, technologies, and social impacts related to AI security should be holistically organized to help understand relationships among them. To this end, we first develop an AI security map that holistically organizes interrelationships among elements related to AI security as well as negative impacts on information systems and stakeholders. This map consists of the two aspects, namely the information system aspect (ISA) and the external influence aspect (EIA). The elements that AI should fulfill within information systems are classified under the ISA. The EIA includes elements that affect stakeholders as a result of AI being attacked or misused. For each element, corresponding negative impacts are identified. By referring to the AI security map, one can understand the potential negative impacts, along with their causes and countermeasures. Additionally, our map helps clarify how the negative impacts on AI-based systems relate to those on stakeholders. We show some findings newly obtained by referring to our map. We also provide several recommendations and open problems to guide future AI security communities.

cs.CR