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This research paper concludes that we’ll be eating more squid in the future.
As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.
Read my blog posting guidelines here.
This story nicely illustrates the arms race between technologies to create fake videos and technologies to detect fake videos:
These fakes, while convincing if you watch a few seconds on a phone screen, aren’t perfect (yet). They contain tells, like creepily ever-open eyes, from flaws in their creation process. In looking into DeepFake’s guts, Lyu realized that the images that the program learned from didn’t include many with closed eyes (after all, you wouldn’t keep a selfie where you were blinking, would you?). “This becomes a bias,” he says. The neural network doesn’t get blinking. Programs also might miss other “physiological signals intrinsic to human beings,” says Lyu’s paper on the phenomenon, such as breathing at a normal rate, or having a pulse. (Autonomic signs of constant existential distress are not listed.) While this research focused specifically on videos created with this particular software, it is a truth universally acknowledged that even a large set of snapshots might not adequately capture the physical human experience, and so any software trained on those images may be found lacking.
Lyu’s blinking revelation revealed a lot of fakes. But a few weeks after his team put a draft of their paper online, they got anonymous emails with links to deeply faked YouTube videos whose stars opened and closed their eyes more normally. The fake content creators had evolved.
I don’t know who will win this arms race, if there ever will be a winner. But the problem with fake videos goes deeper: they affect people even if they are later told that they are fake, and there always will be people that will believe they are real, despite any evidence to the contrary.
This is a long—and somewhat technical—paper by Chris C. Demchak and Yuval Shavitt about China’s repeated hacking of the Internet Border Gateway Protocol (BGP): “China’s Maxim Leave No Access Point Unexploited: The Hidden Story of China Telecom’s BGP Hijacking.”
BGP hacking is how large intelligence agencies manipulate Internet routing to make certain traffic easier to intercept. The NSA calls it “network shaping” or “traffic shaping.” Here’s a document from the Snowden archives outlining how the technique works with Yemen.
EDITED TO ADD (10/27): Boing Boing post.
If you’re an American of European descent, there’s a 60% chance you can be uniquely identified by public information in DNA databases. This is not information that you have made public; this is information your relatives have made public.
Research paper:
“Identity inference of genomic data using long-range familial searches.”
Abstract: Consumer genomics databases have reached the scale of millions of individuals. Recently, law enforcement authorities have exploited some of these databases to identify suspects via distant familial relatives. Using genomic data of 1.28 million individuals tested with consumer genomics, we investigated the power of this technique. We project that about 60% of the searches for individuals of European-descent will result in a third cousin or closer match, which can allow their identification using demographic identifiers. Moreover, the technique could implicate nearly any US-individual of European-descent in the near future. We demonstrate that the technique can also identify research participants of a public sequencing project. Based on these results, we propose a potential mitigation strategy and policy implications to human subject research.
A good news article.
Interesting research paper: “Fear the Reaper: Characterization and Fast Detection of Card Skimmers“:
Abstract: Payment card fraud results in billions of dollars in losses annually. Adversaries increasingly acquire card data using skimmers, which are attached to legitimate payment devices including point of sale terminals, gas pumps, and ATMs. Detecting such devices can be difficult, and while many experts offer advice in doing so, there exists no large-scale characterization of skimmer technology to support such defenses. In this paper, we perform the first such study based on skimmers recovered by the NYPD’s Financial Crimes Task Force over a 16 month period. After systematizing these devices, we develop the Skim Reaper, a detector which takes advantage of the physical properties and constraints necessary for many skimmers to steal card data. Our analysis shows the Skim Reaper effectively detects 100% of devices supplied by the NYPD. In so doing, we provide the first robust and portable mechanism for detecting card skimmers.
Boing Boing post.
From Kashmir Hill:
Facebook is not content to use the contact information you willingly put into your Facebook profile for advertising. It is also using contact information you handed over for security purposes and contact information you didn’t hand over at all, but that was collected from other people’s contact books, a hidden layer of details Facebook has about you that I’ve come to call “shadow contact information.” I managed to place an ad in front of Alan Mislove by targeting his shadow profile. This means that the junk email address that you hand over for discounts or for shady online shopping is likely associated with your account and being used to target you with ads.
Here’s the research paper. Hill again:
They found that when a user gives Facebook a phone number for two-factor authentication or in order to receive alerts about new log-ins to a user’s account, that phone number became targetable by an advertiser within a couple of weeks. So users who want their accounts to be more secure are forced to make a privacy trade-off and allow advertisers to more easily find them on the social network.
Interesting research:
In the team’s experiments, one WiFi transmitter and one WiFi receiver are behind walls, outside a room in which a number of people are present. The room can get very crowded with as many as 20 people zigzagging each other. The transmitter sends a wireless signal whose received signal strength (RSSI) is measured by the receiver. Using only such received signal power measurements, the receiver estimates how many people are inside the room an estimate that closely matches the actual number. It is noteworthy that the researchers do not do any prior measurements or calibration in the area of interest; their approach has only a very short calibration phase that need not be done in the same area.
Academic paper.
This is interesting research: “On the Security of the PKCS#1 v1.5 Signature Scheme“:
Abstract: The RSA PKCS#1 v1.5 signature algorithm is the most widely used digital signature scheme in practice. Its two main strengths are its extreme simplicity, which makes it very easy to implement, and that verification of signatures is significantly faster than for DSA or ECDSA. Despite the huge practical importance of RSA PKCS#1 v1.5 signatures, providing formal evidence for their security based on plausible cryptographic hardness assumptions has turned out to be very difficult. Therefore the most recent version of PKCS#1 (RFC 8017) even recommends a replacement the more complex and less efficient scheme RSA-PSS, as it is provably secure and therefore considered more robust. The main obstacle is that RSA PKCS#1 v1.5 signatures use a deterministic padding scheme, which makes standard proof techniques not applicable.
We introduce a new technique that enables the first security proof for RSA-PKCS#1 v1.5 signatures. We prove full existential unforgeability against adaptive chosen-message attacks (EUF-CMA) under the standard RSA assumption. Furthermore, we give a tight proof under the Phi-Hiding assumption. These proofs are in the random oracle model and the parameters deviate slightly from the standard use, because we require a larger output length of the hash function. However, we also show how RSA-PKCS#1 v1.5 signatures can be instantiated in practice such that our security proofs apply.
In order to draw a more complete picture of the precise security of RSA PKCS#1 v1.5 signatures, we also give security proofs in the standard model, but with respect to weaker attacker models (key-only attacks) and based on known complexity assumptions. The main conclusion of our work is that from a provable security perspective RSA PKCS#1 v1.5 can be safely used, if the output length of the hash function is chosen appropriately.
I don’t think the protocol is “provably secure,” meaning that it cannot have any vulnerabilities. What this paper demonstrates is that there are no vulnerabilities under the model of the proof. And, more importantly, that PKCS #1 v1.5 is as secure as any of its successors like RSA-PSS and RSA Full-Domain.
Lots of people are e-mailing me about this new result on the distribution of prime numbers. While interesting, it has nothing to do with cryptography. Cryptographers aren’t interested in how to find prime numbers, or even in the distribution of prime numbers. Public-key cryptography algorithms like RSA get their security from the difficulty of factoring large composite numbers that are the product of two prime numbers. That’s completely different.
This is really interesting research: “BlackIoT: IoT Botnet of High Wattage Devices Can Disrupt the Power Grid“:
Abstract: We demonstrate that an Internet of Things (IoT) botnet of high wattage devices—such as air conditioners and heaters—gives a unique ability to adversaries to launch large-scale coordinated attacks on the power grid. In particular, we reveal a new class of potential attacks on power grids called the Manipulation of demand via IoT (MadIoT) attacks that can leverage such a botnet in order to manipulate the power demand in the grid. We study five variations of the MadIoT attacks and evaluate their effectiveness via state-of-the-art simulators on real-world power grid models. These simulation results demonstrate that the MadIoT attacks can result in local power outages and in the worst cases, large-scale blackouts. Moreover, we show that these attacks can rather be used to increase the operating cost of the grid to benefit a few utilities in the electricity market. This work sheds light upon the interdependency between the vulnerability of the IoT and that of the other networks such as the power grid whose security requires attention from both the systems security and power engineering communities.
I have been collecting examples of surprising vulnerabilities that result when we connect things to each other. This is a good example of that.
Wired article.
Sidebar photo of Bruce Schneier by Joe MacInnis.