The Future of Machine Learning and Cybersecurity

The Center for Security and Emerging Technology has a new report: “Machine Learning and Cybersecurity: Hype and Reality.” Here’s the bottom line:

The report offers four conclusions:

  • Machine learning can help defenders more accurately detect and triage potential attacks. However, in many cases these technologies are elaborations on long-standing methods — not fundamentally new approaches — that bring new attack surfaces of their own.
  • A wide range of specific tasks could be fully or partially automated with the use of machine learning, including some forms of vulnerability discovery, deception, and attack disruption. But many of the most transformative of these possibilities still require significant machine learning breakthroughs.
  • Overall, we anticipate that machine learning will provide incremental advances to cyber defenders, but it is unlikely to fundamentally transform the industry barring additional breakthroughs. Some of the most transformative impacts may come from making previously un- or under-utilized defensive strategies available to more organizations.
  • Although machine learning will be neither predominantly offense-biased nor defense-biased, it may subtly alter the threat landscape by making certain types of strategies more appealing to attackers or defenders.

Posted on June 21, 2021 at 6:31 AM8 Comments

Intentional Flaw in GPRS Encryption Algorithm GEA-1

General Packet Radio Service (GPRS) is a mobile data standard that was widely used in the early 2000s. The first encryption algorithm for that standard was GEA-1, a stream cipher built on three linear-feedback shift registers and a non-linear combining function. Although the algorithm has a 64-bit key, the effective key length is only 40 bits, due to “an exceptional interaction of the deployed LFSRs and the key initialization, which is highly unlikely to occur by chance.”

GEA-1 was designed by the European Telecommunications Standards Institute in 1998. ETSI was — and maybe still is — under the auspices of SOGIS: the Senior Officials Group, Information Systems Security. That’s basically the intelligence agencies of the EU countries.

Details are in the paper: “Cryptanalysis of the GPRS Encryption Algorithms GEA-1 and GEA-2.” GEA-2 does not have the same flaw, although the researchers found a practical attack with enough keystream.

Hacker News thread.

EDITED TO ADD (6/18): News article.

Posted on June 17, 2021 at 1:51 PM40 Comments

VPNs and Trust

TorrentFreak surveyed nineteen VPN providers, asking them questions about their privacy practices: what data they keep, how they respond to court order, what country they are incorporated in, and so on.

Most interesting to me is the home countries of these companies. Express VPN is incorporated in the British Virgin Islands. NordVPN is incorporated in Panama. There are VPNs from the Seychelles, Malaysia, and Bulgaria. There are VPNs from more Western and democratic countries like the US, Switzerland, Canada, and Sweden. Presumably all of those companies follow the laws of their home country.

And it matters. I’ve been thinking about this since Trojan Shield was made public. This is the joint US/Australia-run encrypted messaging service that lured criminals to use it, and then spied on everything they did. Or, at least, Australian law enforcement spied on everyone. The FBI wasn’t able to because the US has better privacy laws.

We don’t talk about it a lot, but VPNs are entirely based on trust. As a consumer, you have no idea which company will best protect your privacy. You don’t know the data protection laws of the Seychelles or Panama. You don’t know which countries can put extra-legal pressure on companies operating within their jurisdiction. You don’t know who actually owns and runs the VPNs. You don’t even know which foreign companies the NSA has targeted for mass surveillance. All you can do is make your best guess, and hope you guessed well.

Posted on June 16, 2021 at 6:17 AM53 Comments

Andrew Appel on New Hampshire’s Election Audit

Really interesting two part analysis of the audit conducted after the 2020 election in Windham, New Hampshire.

Based on preliminary reports published by the team of experts that New Hampshire engaged to examine an election discrepancy, it appears that a buildup of dust in the read heads of optical-scan voting machines (possibly over several years of use) can cause paper-fold lines in absentee ballots to be interpreted as votes… New Hampshire (and other states) may need to maintain the accuracy of their optical-scan voting machines by paying attention to three issues:

  • Routine risk-limiting audits to detect inaccuracies if/when they occur.
  • Clean the dust out of optical-scan read heads regularly; pay attention to the calibration of the optical-scan machines.
  • Make sure that the machines that automatically fold absentee ballots (before mailing them to voters) don’t put the fold lines over vote-target ovals. (Same for election workers who fold ballots by hand.)

Posted on June 15, 2021 at 10:45 AM23 Comments

Upcoming Speaking Engagements

This is a current list of where and when I am scheduled to speak:

The list is maintained on this page.

Posted on June 14, 2021 at 11:55 AM2 Comments

TikTok Can Now Collect Biometric Data

This is probably worth paying attention to:

A change to TikTok’s U.S. privacy policy on Wednesday introduced a new section that says the social video app “may collect biometric identifiers and biometric information” from its users’ content. This includes things like “faceprints and voiceprints,” the policy explained. Reached for comment, TikTok could not confirm what product developments necessitated the addition of biometric data to its list of disclosures about the information it automatically collects from users, but said it would ask for consent in the case such data collection practices began.

Posted on June 14, 2021 at 10:11 AM29 Comments

Sidebar photo of Bruce Schneier by Joe MacInnis.