Small world with high risks: a study of security threats in the npm ecosystem

Small world with high risks: a study of security threats in the npm ecosystem Zimmermann et al., USENIX Security Symposium 2019 This is a fascinating study of the npm ecosystem, looking at the graph of maintainers and packages and its evolution over time. It’s packed with some great data, and also helps us quantify something … Continue reading Small world with high risks: a study of security threats in the npm ecosystem

Wireless attacks on aircraft instrument landing systems

Wireless attacks on aircraft instrument landing systems Sathaye et al., USENIX Security Symposium 2019 It’s been a while since we last looked at security attacks against connected real-world entities (e.g., industrial machinery, light-bulbs, and cars). Today’s paper is a good reminder of just how important it is becoming to consider cyber threat models in what … Continue reading Wireless attacks on aircraft instrument landing systems

50 ways to leak your data: an exploration of apps’ circumvention of the Android permissions system

50 ways to leak your data: an exploration of apps’ circumvention of the Android permissions system Reardon et al., USENIX Security Symposium 2019 The problem is all inside your app, she said to me / The answer is easy if you take it logically / I’d like to help data in its struggle to be … Continue reading 50 ways to leak your data: an exploration of apps’ circumvention of the Android permissions system

The secret-sharer: evaluating and testing unintended memorization in neural networks

The secret sharer: evaluating and testing unintended memorization in neural networks Carlini et al., USENIX Security Symposium 2019 This is a really important paper for anyone working with language or generative models, and just in general for anyone interested in understanding some of the broader implications and possible unintended consequences of deep learning. There’s also … Continue reading The secret-sharer: evaluating and testing unintended memorization in neural networks

Even more amazing papers at VLDB 2019 (that I didn’t have space to cover yet)

We’ve been covering papers from VLDB 2019 for the last three weeks, and next week it will be time to mix things up again. There were so many interesting papers at the conference this year though that I haven’t been able to cover nearly as many as I would like. So today’s post is a … Continue reading Even more amazing papers at VLDB 2019 (that I didn’t have space to cover yet)

Updating graph databases with Cypher

Updating graph databases with Cypher Green et al., VLDB'19 This is the story of a great collaboration between academia, industry, and users of the Cypher graph querying language as created by Neo4j. Beyond Neo4j, Cypher is also supported in SAP HANA Graph, RedisGraph, Agnes Graph, and Memgraph. Cypher for Apache Spark, and Cypher over Gremlin … Continue reading Updating graph databases with Cypher

Fine-grained, secure and efficient data provenance on blockchain systems

Fine-grained, secure and efficient data provenance on blockchain systems Ruan et al., VLDB'19 We haven’t covered a blockchain paper on The Morning Paper for a while, and today’s choice won the best paper award at VLDB’19. The goal here is to enable smart contracts to be written in which the contract logic depends on the … Continue reading Fine-grained, secure and efficient data provenance on blockchain systems