Consent as a Foundation for Responsible Autonomy

This paper focuses on a dynamic aspect of responsible autonomy, namely, to make intelligent agents be responsible at run time. That is, it considers settings where decision making by agents impinges upon the outcomes perceived by other agents. For an agent to act responsibly, it must accommodate the desires and other attitudes of its users and, through other agents, of their users. The contribution of this paper is twofold.

Verified Cryptographic Code for Everybody

Submitted by Anonymous on

Along with Amazon Web Services, Galois is publishing a new paper titled “Verified Cryptographic Code for Everybody,” and we really do mean everybody. One benefit of the way we’ve done this work is that everyone who was using the code already is now using verified code. The library we’ve verified parts of is called AWS-LibCrypto. Much of that library is code that originated from BoringSSL, and BoringSSL is composed of code originating from OpenSSL.

MLEFlow: Learning from History to Improve Load Balancing in Tor

Tor has millions of daily users seeking privacy while browsing the Internet. It has thousands of relays to route users’ packets while anonymizing their sources and destinations. Users choose relays to forward their traffic according to probability distributions published by the Tor authorities. The authorities generate these probability distributions based on estimates of the capacities of the relays. They compute these estimates based on the bandwidths of probes sent to the relays. These estimates are necessary for better load balancing.

FAIXID: A Framework for Enhancing AI Explainability of Intrusion Detection Results Using Data Cleaning Techniques

Submitted by Anonymous on

Organizations depend on heavy use of various cyber defense technologies, including intrusion detection and prevention systems, to monitor and protect networks and devices from malicious activities. However, large volumes of false alerts from such technologies challenge cybersecurity analysts in isolating credible alerts from false positives for further investigations.

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