Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

August 8, 2017

When You Say “Google,” You Mean #GCensor

Filed under: Censorship,Free Speech,Searching — Patrick Durusau @ 3:47 pm

Google Blocking Key Search Terms For Left Websites by Andre Damon.

From the post:

Note: In a previous article we reported that Popular Resistance had also seen more than a 60% drop in visits to our website since April when Google changed its search functions. This report goes further into how Google is blocking key search terms. See Google’s New Search Protocol Restricting Access To Leading Leftist Web Sites. KZ

Google blocked every one of the WSWS’s 45 top search terms

An intensive review of Internet data has established that Google has severed links between the World Socialist Web Site and the 45 most popular search terms that previously directed readers to the WSWS. The physical censorship implemented by Google is so extensive that of the top 150 search terms that, as late as April 2017, connected the WSWS with readers, 145 no longer do so.

These findings make clear that the decline in Google search traffic to the WSWS is not the result of some technical issue, but a deliberate policy of censorship. The fall took place in the three months since Google announced on April 25 plans to promote “authoritative web sites” above those containing “offensive” content and “conspiracy theories.”

Because of these measures, the WSWS’s search traffic from Google has fallen by two-thirds since April.

The WSWS has analyzed tens of thousands of search terms, and identified those key phrases and words that had been most likely to place the WSWS on the first or second page of search results. The top 45 search terms previously included “socialism,” “Russian revolution,” “Flint Michigan,” “proletariat,” and “UAW [United Auto Workers].” The top 150 results included the terms “UAW contract,” “rendition” and “Bolshevik revolution.” All of these terms are now blocked.
… (emphasis in original)

In addition to censoring “hate speech” and efforts such as: Google Says It Will Do More to Suppress Terrorist Propaganda, now there is evidence that Google is tampering with search results for simply left-wing websites.

Promote awareness of the censorship by Google, Facebook and Twitter, by using #GCensor, #FCensor, and #TCensor, respectively, for them.

I don’t expect to change the censorship behavior of #GCensor, #FCensor, and #TCensor. The remedy is non-censored alternatives.

All three have proven themselves untrustworthy guardians of free speech.

August 7, 2017

BuzzFeed News Searches For Hidden Spy Planes

Filed under: Journalism,Machine Learning,News,Reporting — Patrick Durusau @ 8:52 pm

BuzzFeed News Trained A Computer To Search For Hidden Spy Planes. This Is What We Found.

From the post:

Data and R code for the analysis supporting this August 7, 2017 BuzzFeed News post on identifying potential surveillance aircraft. Supporting files are in this GitHub repository.

Awesome! This is what data journalism is about!

While Musk and others are wringing their hands over AI, BuzzFeed uses machine learning to out government spy planes. How cool is that?

So, what are some of the headlines from The New York Times today?

  1. Scientists Fear Trump Will Dismiss Climate Change Report
  2. What Music Do Americans Love the Most? 50 Detailed Fan Maps
  3. Partisan C.I.A. Chief Heartens Trump and Worries the Agency
  4. North Korea Warns U.S. of Retaliation Over Sanctions
  5. Industries Are Left in the Lurch by Trump’s Stalled Trade Plans
  6. White House Won’t Say Who Is on Its Deregulation Teams
  7. Wells Fargo Faces New Inquiry Over Insurance Refunds
  8. Take the Generic, Patients Are Told. Until They Are Not.
  9. $78,000 of Debt for a Harvard Theater Degree
  10. Investigators in Israel Turn Up the Heat on Netanyahu

Four out of ten stories are about our accidental president (1, 3, 5, 6) The other six (2, 4, 7, 8, 9, 10), offer no actionable information.

Not a word about government spy planes.

Why isn’t The New York Times pressing the government hard?

Or perhaps the easier question: Why are you still reading The New York Times?

Applications of Topic Models [Monograph, Free Until 12 August 2017]

Filed under: Latent Dirichlet Allocation (LDA),Text Mining,Topic Models (LDA) — Patrick Durusau @ 10:48 am

Applications of Topic Models by Jordan Boyd-Graber, Yuening Hu,David Mimno. (Jordan Boyd-Graber, Yuening Hu and David Mimno (2017), “Applications of Topic Models”, Foundations and Trends® in Information Retrieval: Vol. 11: No. 2-3, pp 143-296. http://dx.doi.org/10.1561/1500000030)

Abstract:

How can a single person understand what’s going on in a collection of millions of documents? This is an increasingly common problem: sifting through an organization’s e-mails, understanding a decade worth of newspapers, or characterizing a scientific field’s research. Topic models are a statistical framework that help users understand large document collections: not just to find individual documents but to understand the general themes present in the collection.

This survey describes the recent academic and industrial applications of topic models with the goal of launching a young researcher capable of building their own applications of topic models. In addition to topic models’ effective application to traditional problems like information retrieval, visualization, statistical inference, multilingual modeling, and linguistic understanding, this survey also reviews topic models’ ability to unlock large text collections for qualitative analysis. We review their successful use by researchers to help understand fiction, non-fiction, scientific publications, and political texts.

The authors discuss the use of topic models for, 4. Historical Documents, 5. Understanding Scientific Publications, 6. Fiction and Literature, 7. Computational Social Science, 8. Multilingual Data and Machine Translation, and provide further guidance in: 9. Building a Topic Model.

If you have haystacks of documents to mine, Applications of Topic Models is a must have on your short reading list.

August 6, 2017

New spearphishing technique – Phishing for Leaks

Filed under: Cybersecurity,Journalism,News,Phishing for Leaks,Reporting,Security — Patrick Durusau @ 8:30 pm

Timo Steffens tweeted:

New spearphishing technique: Targeted mail contains no links or exploits, but mentions report title. Googling title leads to exploit site.

Good news for wannabe government/industry leakers.

This spearphishing technique avoids question about your cybersecurity competence in evaluating links in a phishing email.

You did a search relevant to your position/task and Google delivered an exploit site.

Hard to fault you for that!

The success of phishing for leaks depends on non-leak/spoon-fed journalists.



August 5, 2017

Overlap – Attacking on Machine Learning Models

Filed under: Machine Learning,XML — Patrick Durusau @ 4:48 pm

Robust Physical-World Attacks on Machine Learning Models by Ivan Evtimov, et al.

Abstract:

Deep neural network-based classifiers are known to be vulnerable to adversarial examples that can fool them into misclassifying their input through the addition of small-magnitude perturbations. However, recent studies have demonstrated that such adversarial examples are not very effective in the physical world–they either completely fail to cause misclassification or only work in restricted cases where a relatively complex image is perturbed and printed on paper. In this paper we propose a new attack algorithm–Robust Physical Perturbations (RP2)– that generates perturbations by taking images under different conditions into account. Our algorithm can create spatially-constrained perturbations that mimic vandalism or art to reduce the likelihood of detection by a casual observer. We show that adversarial examples generated by RP2 achieve high success rates under various conditions for real road sign recognition by using an evaluation methodology that captures physical world conditions. We physically realized and evaluated two attacks, one that causes a Stop sign to be misclassified as a Speed Limit sign in 100% of the testing conditions, and one that causes a Right Turn sign to be misclassified as either a Stop or Added Lane sign in 100% of the testing conditions.

I was struck by the image used for this paper in a tweet:

I recognized this as an “overlapping” markup problem before discovering the authors were attacking machine learning models. On overlapping markup, see: Towards the unification of formats for overlapping markup by Paolo Marinelli, Fabio Vitali, Stefano Zacchiroli, or more recently, It’s more than just overlap: Text As Graph – Refining our notion of what text really is—this time for sure! by Ronald Haentjens Dekker and David J. Birnbaum.

From the conclusion:

…
In this paper, we introduced Robust Physical Perturbations (RP2), an algorithm that generates robust, physically realizable adversarial perturbations. Previous algorithms assume that the inputs of DNNs can be modified digitally to achieve misclassification, but such an assumption is infeasible, as an attacker with control over DNN inputs can simply replace it with an input of his choice. Therefore, adversarial attack algorithms must apply perturbations physically, and in doing so, need to account for new challenges such as a changing viewpoint due to distances, camera angles, different lighting conditions, and occlusion of the sign. Furthermore, fabrication of a perturbation introduces a new source of error due to a limited color gamut in printers.

We use RP2 to create two types of perturbations: subtle perturbations, which are small, undetectable changes to the entire sign, and camouflage perturbations, which are visible perturbations in the shape of graffiti or art. When the Stop sign was overlayed with a print out, subtle perturbations fooled the classifier 100% of the time under different physical conditions. When only the perturbations were added to the sign, the classifier was fooled by camouflage graffiti and art perturbations 66.7% and 100% of the time respectively under different physical conditions. Finally, when an untargeted poster-printed camouflage perturbation was overlayed on a Right Turn sign, the classifier was fooled 100% of the time. In future work, we plan to test our algorithm further by varying some of the other conditions we did not consider in this paper, such as sign occlusion.

Excellent work but my question: Is the inability of the classifier to recognize overlapping images similar to the issues encountered as overlapping markup?

To be sure overlapping markup is in part an artifice of unimaginative XML rules, since overlapping texts are far more common than non-overlapping texts. Especially when talking about critical editions or even differing analysis of the same text.

But beyond syntax, there is the subtlety of treating separate “layers” or stacks of a text as separate and yet tracking the relationship between two or more such stacks, when arbitrary additions or deletions can occur in any of them. Additions and deletions that must be accounted for across all layers/stacks.

I don’t have a solution to offer but pose the question of layers of recognition in hopes that machine learning models can capitalize on the lessons learned about a very similar problem with overlapping markup.

Neuroscience-Inspired Artificial Intelligence

Filed under: Artificial Intelligence,Machine Learning,Neural Information Processing,Neural Networks,Neuroinformatics — Patrick Durusau @ 1:06 pm

Neuroscience-Inspired Artificial Intelligence by Demis Hassabis, Dharshan Kumaran, Christopher Summerfield, and Matthew Botvinick.

Abstract:

The fields of neuroscience and artificial intelligence (AI) have a long and intertwined history. In more recent times, however, communication and collaboration between the two fields has become less commonplace. In this article, we argue that better understanding biological brains could play a vital role in building intelligent machines. We survey historical interactions between the AI and neuroscience fields and emphasize current advances in AI that have been inspired by the study of neural computation in humans and other animals. We conclude by highlighting shared themes that may be key for advancing future research in both fields.

Extremely rich article with nearly four (4) pages of citations.

Reading this paper closely and chasing the citations is a non-trivial task but you will be prepared understand and/or participate in the next big neuroscience/AI breakthrough.

Enjoy!

No Fault Leaking (Public Wi-Fi, File Sharing)

Filed under: Cybersecurity,Journalism,News,Reporting,Security — Patrick Durusau @ 10:51 am

Attorney General Sessions and his League of Small Minds (LSM) seek to intimidate potential leakers into silence. Leakers who are responsible for what transparency exists for unfavorable information about current government policies and actions.

FOIA requests can and do uncover unfavorable information about government policies and actions, but far too often after the principals have sought the safety of the grave.

It’s far better to expose and stop ill-considered, even criminal activities in real time, before government adds more blighted lives and deaths to its record.

Traditional leaking involves a leaker, perhaps you, delivering physical or digital copies of data/documents to a reporter. That is it requires some act on your part, copying, email, smail, etc., which offers the potential to trace the leak back to you.

Have you considered No Fault Leaking? (NFL)

No Fault Leaking requires only a public Wi-Fi and appropriate file sharing permissions on your phone, laptop, tablet.

Public Wi-Fi: Potential Washington, DC based leakers can consult Free Wi-Fi Hotspot Locations in Washington, DC by Rachel Cooper, updated 7/28/2017. Similar listings exist for other locations.

File Sharing Permissions: Even non-techies should be able to follow the screen shots in One mistake people make using public Wi-Fi that lets everyone see their files by Francis Navarro. (Pro tip: Don’t view this article on your device or save a copy there. Memorize the process of turning file sharing on and off.)

After arriving at a Public Wi-Fi location, turn file sharing on. It’s as simple as that. You don’t know who if anyone has copied any files. Before you leave the location, turn file sharing off. (This works best if you have legitimate reasons to have the files in question on your laptop, etc.)

No Fault Leaking changes the role of the media from spoon-fed recipients of data/documents into more active participants in the leaking process.

To that end, ask yourself: Am I a fair weather (no risk) advocate of press freedom or something more?

August 4, 2017

“This culture of leaking must stop.” Taking up Sessions’ Gage

Filed under: Cybersecurity,Government,Government Data,Security — Patrick Durusau @ 4:12 pm

Jeff Sessions, the current (4 August 2017) Attorney General of the United States, wants to improve on Barack Obama‘s legacy as the most secretive presidency of the modern era.

Sessions has announced a tripling Justice Department probes into leaks and a review of guidelines for subpoenas for members of the news media. Attorney General says Justice Dept. has tripled the number of leak probes. (Media subpoenas are an effort to discover media sources and hence to plug the “leaks.”)

Sessions has thrown down his gage, declaring war on occasional transparency from government leakers. Indirectly, that war will include members of the media as casualties.

Shakespeare penned the best response for taking up Sessions’ gage:

Cry ‘Havoc,’ and let slip the dogs of war;

In case you don’t know the original sense of “Havoc:”

The military order Havoc! was a signal given to the English military forces in the Middle Ages to direct the soldiery (in Shakespeare’s parlance ‘the dogs of war’) to pillage and chaos. Cry havoc and let slip the dogs of war

It’s on all of us to create enough chaos to protect leakers and members of the media who publish their leaks.

Observations – Not Instructions

Data access: Phishing emails succeed 33% of the time. Do they punish would-be leakers who fall for phishing emails?

Exflitration: Tracing select documents to a leaker is commonplace. How do you trace an entire server disk? The larger and more systematic the data haul, the greater the difficulty in pinning the leak on particular documents. (Back to school specials often include multi-terabyte drives.)

Protect the Media: Full drive leaks posted a Torrent or Dark Web server means media can answer subpoenas with: go to: https://some-location. 😉

BTW, full drive leaks provide transparency for the relationship between the leaked data and media reports. Accountability is as important for the media as the government.

One or more of my observations may constitute crimes depending upon your jurisdiction.

Which I guess is why Nathan Hale is recorded as saying:

Gee, that sounds like a crime. You know, I could get arrested, even executed. None for me please!

Not!

Nathan Hale volunteered to be a spy, was caught and executed, having said:

I only regret, that I have but one life to lose for my country.

Question for you:

Are you a ‘dog of war’ making the government bleed data?

PS: As a security measure, don’t write that answer down or tell anyone. When you read about leaks, you can inwardly smile and know you played your part.

August 3, 2017

DMCA Complaint As Finding Aid

Filed under: Intellectual Property (IP),Library,Searching — Patrick Durusau @ 6:18 pm

Credit where credit is due, I saw this idea in How to Get Past DMCA Take-Downs in Google Search and report it here, sans the video.

The gist of the idea is that DMCA complaints, found at: Lumen, specify in the case of search engines, links that should not be displayed to users.

In a Google search result, content subject to a DMCA complaint will appear as:

In response to multiple complaints we received under the US Digital Millennium Copyright Act, we have removed 2 results from this page. If you wish, you may read the DMCA complaints that caused the removals at LumenDatabase.org: Complaint, Complaint.

If you follow the complaint links, knowing Google is tracking your following of those links, the complaints list the URLs to be removed from search results.

You can use the listed URLs to verify the presence of illegal content, compile lists of sites with such content, etc.

Enjoy!

PS: I’m adding their RSS feed of new notices. You should too.

Sophisticated, Chilling, Alarming, Nefarious, Vicious … HBO Hack 2017

Filed under: Cybersecurity,Security — Patrick Durusau @ 4:44 pm

Sophisticated, chilling, alarming, nefarious, vicious, are all terms used to describe the recent HBO hack.

For your reading pleasure, try HBO Hack: Insiders Fear Leaked Emails as FBI Joins Investigation by Tatiana Siegel, or HBO Security Contractor: Hackers Stole ‘Thousands of Internal Documents’ (EXCLUSIVE) by Janko Roettgers

There’s a shortage of facts available concerning this hack of HBO (Home Box Office) but 1.5 terabytes is being thrown around as a scary number for the data loss.

While everyone else oohs and aahs over 1.5 terabytes of data, you can smile knowing that a new Dell XPS 27 sells pre-configured with a 2 terabyte drive for $1899.99, shipping, taxes, blah, blah extra. That’s a mid to low range desktop.

Hackers may have gotten 1.5 terabytes of data but that’s no indication of its worth. How do you count emails with dozens of people on the cc: line? Or multiple versions of the same video?

I don’t have time to watch the majority of HBO content on my legitimate subscription so I’m not interested in the stolen content, assuming it includes anything worth watching.

Of greater interest is forensic analysis of how the hack was performed, because post-Sony, one expects HBO avoided the obvious faults that led to the Sony hack. If they did, perhaps there is something to be learned here.

Unlike the Podesta “hack,” which consisted of losing his email password in a phishing attack. That’s not really a hack, that’s just dumb

Watch your favorite sites for alleged HBO content.

Alleged HBO content with viruses, malware and ransomeware! Oh, my!

Foreign Intelligence Gathering Laws (and ethics)

Filed under: Ethics,Government,Intelligence — Patrick Durusau @ 10:47 am

Foreign Intelligence Gathering Laws from the Law Library of the Library of Congress.

From the webpage:

This report offers a review of laws regulating the collection of intelligence in the European Union (EU) and Belgium, France, Germany, Netherlands, Portugal, Romania, Sweden, and the United Kingdom. This report updates a report on the same topic issued from 2014. Because issues of national security are under the jurisdiction of individual EU Member States and are regulated by domestic legislation, individual country surveys provide examples of how the European nations control activities of their intelligence agencies and what restrictions are imposed on information collection. All EU Member States follow EU legislation on personal data protection, which is a part of the common European Union responsibility.

If you are investigating or reporting on breaches of intelligence gathering laws in “the European Union (EU) and Belgium, France, Germany, Netherlands, Portugal, Romania, Sweden, and the United Kingdom,” this will be useful. Otherwise, for the other one hundred and eighty-eight (188), you are SOL.

Other than as a basis for outrage, it’s not clear how useful intelligence gathering laws are in fact. The secrecy of intelligence operations makes practical oversight impossible and if leaks are to be credited, no known intelligence agency obeys such laws other than accidentally.

Moreover, as the U.S. Senate report on torture demonstrates, even war criminals are protected from prosecution in the name of intelligence gathering.

I take my cue from the CIA‘s position, as captured by Bob Dylan in Tweeter and the Monkey Man:

“It was you to me who taught
In Jersey anything’s legal as long as you don’t get caught.”

Disarming yourself with law or ethics in any encounter with an intelligence agency, which honors neither, means you will lose.

Choose your strategies accordingly.

August 2, 2017

Security Leadership by the Uninformed

Filed under: Cybersecurity,Government — Patrick Durusau @ 5:05 pm

The first two paragraphs of Senators Want A Hack-Proof Internet Of Government Things are sufficient to establish the authors of the Internet of Things Cybersecurity Improvements Act as deeply uninformed:

Internet-connected smart devices purchased by the federal government would have to meet strict security standards under bipartisan legislation introduced Tuesday.

Those devices would have to accept software patches to remove vulnerabilities and allow users to change default passwords, according to the Internet of Things Cybersecurity Improvements Act.
…

Sigh, “…allow users to change default passwords….”

That’s section 3, (a)(1)(A)(i)(IV):

…does not include any fixed or hard-coded credentials used for remote administration, the delivery of updates, or communication.

Yeah! Getting users to change default passwords is a step towards …. 91% insecurity.

If you have the top 1,000 passwords by popularity, you are close to 91% of the “changed” passwords you will encounter. (That link leads to the top 10,000 passwords if you are looking for completeness.)

You could argue that improving the security of the Internet of Things by 9 percentage points (maybe) isn’t nothing.

True but it is so nearly nothing as to not be worth the effort.

PS: There are solutions to the IoT password issue but someone needs to pay money to spark that discussion.

Potential NSA Leak Stream

Filed under: Cybersecurity,Government,NSA — Patrick Durusau @ 4:09 pm

The Government Accounting Office (GAO) has publicly identified a potential source of NSA technology leaks. The cumbersome title: DOD’s Monitoring of Progress in Implementing Cyber Strategies Can Be Strengthened (GAO-17-512) begins with this summary:

Officials from Department of Defense (DOD) components identified advantages and disadvantages of the “dual-hat” leadership of the National Security Agency (NSA)/Central Security Service (CSS) and Cyber Command (CYBERCOM) (see table). Also, DOD and congressional committees have identified actions that could mitigate risks associated with ending the dual-hat leadership arrangement, such as formalizing agreements between NSA/CSS and CYBERCOM to ensure continued collaboration, and developing a persistent cyber training environment to provide a realistic, on-demand training capability. As of April 2017, DOD had not determined whether it would end the dual-hat leadership arrangement.
…

At first I thought it said “ass-hat” leadership and went back to check. 😉

You can read the recommendations if you are in charge of improving that situation (an unlikely outcome) or take the GAO at its word as a place to mine for leaks.

Are dual-hat arrangements “leak patterns” much like “design patterns” in programming languages?

I ask because identifying “leak patterns,” whether in software (buffer overflows) or recurrent organizational security failures, could be a real boon to hounds and hares alike.

Continue Flash? As what? Example of insecure coding?

Filed under: Cybersecurity,Open Source — Patrick Durusau @ 1:34 pm

Some People Want Adobe Flash to Continue as an Open Source Project by Derick Sullivan M. Lobga.

From the post:

Last week we heard the good news that Adobe is officially killing Flash in 2020.

This news was well received by developers and end users alike. Well, at least most people liked the demise of Adobe Flash. But it seems that Adobe Flash has still some fans left.

A group of developers at GitHub have come up with a petition to “save Adobe Flash”. Just a few days after the announcement by Adobe, Juha Linstedt, a web developer with username “Pakastin” on GitHub started a petition calling on Adobe to allow for open source Flash, which he thinks is part of Internet history.
…

Losing Flash altogether will impair access to resources developed using Flash but even as open source, preserving Flash strikes me as the equivalent of preserving small pox for later study.

If Adobe does open source the necessary components, it could have value as examples of how not to code an application. Or for testing of code auditing tools.

It’s more than just overlap: Text As Graph

Filed under: Graphs,Humanities,Hyperedges,Hypergraphs,Texts,XML — Patrick Durusau @ 12:57 pm

It’s more than just overlap: Text As Graph – Refining our notion of what text really is—this time for sure! by Ronald Haentjens Dekker and David J. Birnbaum.

Abstract:

The XML tree paradigm has several well-known limitations for document modeling and processing. Some of these have received a lot of attention (especially overlap), and some have received less (e.g., discontinuity, simultaneity, transposition, white space as crypto-overlap). Many of these have work-arounds, also well known, but—as is implicit in the term “work-around”—these work-arounds have disadvantages. Because they get the job done, however, and because XML has a large user community with diverse levels of technological expertise, it is difficult to overcome inertia and move to a technology that might offer a more comprehensive fit with the full range of document structures with which researchers need to interact both intellectually and programmatically. A high-level analysis of why XML has the limitations it has can enable us to explore how an alternative model of Text as Graph (TAG) might address these types of structures and tasks in a more natural and idiomatic way than is available within an XML paradigm.

Hyperedges, texts and XML, what more could you need? 😉

This paper merits a deep read and testing by everyone interested in serious text modeling.

You can’t read the text but here is a hypergraph visualization of an excerpt from Lewis Carroll’s “The hunting of the Snark:”

The New Testament, the Hebrew Bible, to say nothing of the Rabbinic commentaries on the Hebrew Bible and centuries of commentary on other texts could profit from this approach.

Put your text to the test and share how to advance this technique!

“But it feels better when I sneak”

Filed under: Cybersecurity,FOIA,Government,Government Data — Patrick Durusau @ 10:37 am

Email prankster tricks White House officials by Graham Cluley is ample evidence for why you should abandon FOIA requests in favor of phishing/hacking during the reign of Donald Trump.

People can and do obtain mountains of information using FOIA requests, but in the words of Parker Ray, “The Other Woman,”:

“Now I hate to have to cheat
But it feels better when I sneak”

In addition to feeling better, not using FOIA requests during the Trump regime results in:

  1. Access to competitor’s data deposited with the government
  2. Avoids the paperwork and delay of the FOIA process
  3. Bidding and contract data
  4. Develop long-term stealth access than spans presidencies
  5. Incompetence of staff gives broad and deep access across agencies
  6. Mine papers of extremely secretive prior presidents, like Obama
  7. Transparency when least expected and most inconvenient

If that sounds wishful, remember Cluley reports the “technique” used by the prankster was: 1) create an email account in the name of a White House staffer, 2) send an email from that account. This has to be a new low bar for “fake” emails.

Can you afford to be a goody two shoes?

August 1, 2017

Why Learn OpenAI? In a word, Malware!

Filed under: Artificial Intelligence,Cybersecurity,Malware — Patrick Durusau @ 6:46 pm

OpenAI framework used to create undetectable malware by Anthony Spadafora.

Spadafora reports on Endgame‘s malware generating software, Malware Env for OpenAI Gym.

From the Github page:

This is a malware manipulation environment for OpenAI’s gym. OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms. This makes it possible to write agents that learn to manipulate PE files (e.g., malware) to achieve some objective (e.g., bypass AV) based on a reward provided by taking specific manipulation actions.
… (highlight in original)

Introducing OpenAI is a good starting place to learn more about OpenAI.

The value of the OpenAI philosophy:

We believe AI should be an extension of individual human wills and, in the spirit of liberty, as broadly and evenly distributed as possible. The outcome of this venture is uncertain and the work is difficult, but we believe the goal and the structure are right. We hope this is what matters most to the best in the field.

will vary depending upon your objectives.

From my perspective, it’s better for my AI to decide to reach out or stay its hand, as opposed to relying upon ethical behavior of another AI.

You?

Decentralization and Linked Data: Open Review for DeSemWeb2017 at ISWC2017

Filed under: Decentralized Internet,Linked Data — Patrick Durusau @ 6:16 pm

A recent email from the organizers of DeSemWeb2017 reads:

Below are 14 contributions on the topic of decentralization and Linked Data. These were shared in reply to the call for contributions of DeSemWeb2017, an ISWC2017 workshop on Decentralizing the Semantic Web.

We invite everyone to add open reviews to any of these contributions. This ensures fair feedback and transparency of the process.

Semantic Web in the Fog of Browsers by Pascal Molli, Hala Skaf-Molli https://openreview.net/forum?id=ByFHXFy8W&noteId=ByFHXFy8W

Decentralizing the Semantic Web: Who will pay to realize it? by Tobias Grubenmann, Daniele Dell’Aglio, Abraham Bernstein, Dmitry Moor, Sven Seuken https://openreview.net/forum?id=ryrkDpyIW&noteId=ryrkDpyIW

On a Web of Data Streams by Daniele Dell’Aglio, Danh Le Phuoc, Anh Le-Tuan, Muhammad Intizar Ali, Jean-Paul Calbimonte https://openreview.net/forum?id=HyU_JWLU-&noteId=HyU_JWLU-

Towards VoIS: a Vocabulary of Interlinked Streams by Yehia Abo Sedira, Riccardo Tommasini, Emanuele Della Valle https://openreview.net/forum?id=H1ODzYPLZ&noteId=H1ODzYPLZ

Agent Server: Semantic Agent for Linked Data by Teofilo Chambilla, Claudio Gutierrez https://openreview.net/forum?id=H1aftW_Lb&noteId=H1aftW_Lb

The tripscore Linked Data client: calculating specific summaries over large time series by David Chaves Fraga, Julian Rojas, Pieter-Jan Vandenberghe, Pieter Colpaer, Oscar Corcho https://openreview.net/forum?id=H16ZExYLb&noteId=H16ZExYLb

Agreements in a De-Centralized Linked Data Based Messaging System by Florian Kleedorfer, Heiko Friedrich, Christian Huemer https://openreview.net/forum?id=B1AK_bKL-&noteId=B1AK_bKL-

Specifying and Executing User Agent Behaviour with Condition-Action Rules by Andreas Harth, Tobias Käfer https://openreview.net/forum?id=BJ67PfFLZ&noteId=BJ67PfFLZ

VisGraph^3: a web tool for RDF visualization and creation by Dominik Tomaszuk, Przemysław Truchan https://openreview.net/forum?id=rka5DGt8Z&noteId=rka5DGt8Z

Identity and Blockchain by Joachim Lohkamp, Eugeniu Rusu, Fabian Kirstein https://openreview.net/forum?id=HJ94gXtUZ&noteId=HJ94gXtUZ

LinkChains: Exploring the space of decentralised trustworthy Linked Data by Allan Third and John Domingue https://openreview.net/forum?id=HJhwZNKIb&noteId=HJhwZNKIb

Decentralizing the Persistence and Querying of RDF Datasets Through Browser-Based Technologies by Blake Regalia https://openreview.net/forum?id=B1PRiIK8-&noteId=B1PRiIK8-

Attaching Semantic Metadata to Cryptocurrency Transactions by Luis-Daniel Ibáñez, Huw Fryer, Elena Simperl https://openreview.net/forum?id=S18mSwKUZ&noteId=S18mSwKUZ

Storage Balancing in P2P Based Distributed RDF Data Stores by Maximiliano Osorio, Carlos Buil-Aranda https://openreview.net/forum?id=rJn8cDtIb&noteId=rJn8cDtIb

Full list: https://openreview.net/group?id=swsa.semanticweb.org/ISWC/2017/DeSemWeb About the workshop: http://iswc2017.desemweb.org/

You and I know that “peer review” as practiced by pay-per-view journals is nearly useless.

Here, instead of an insider group of mutually supportive colleagues, there is the potential for non-insiders to participate.

Key word is “potential.” It won’t be more than “potential” to participate unless you step up to offer a review.

Well?

Further questions?

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