August 2021 - nexa - server-nexa.polito.it

Non solo cyber, così riformiamo l’intelligence. Parla Franco Gabrielli
by don Luca Peyron Aug. 14, 2021

Aug. 14, 2021

Una intervista, non un paper, ma comunque capace di fornire indicazioni utili alla nostra riflessione, penso. Buona lettura dl https://formiche.net/2021/08/non-solo-cyber-cosi-riformiamo-lintelligence-p… _________________________ don Luca Peyron Direttore Ufficio per la Pastorale Universitaria Arcidiocesi di Torino www.universitari.to.it via XX settembre 83, Torino tel. 011 5156239

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Young People Have More Faith in Algorithms than Politicians
by don Luca Peyron Aug. 12, 2021

Aug. 12, 2021

Young people champion an open internet but are concerned about misuse young people would be more likely to trust a system run by artificial intelligence than humans The Youth Recovery Plan is an initiative of the World Economic Forum Global Shapers Community, a network created to ensure that the next generation – people between the ages of 20 and 30 – are empowered to help shape our common future. They are active in more than 450 cities in 150 countries world, and together they implement local and global projects to improve the state of the world. Considerazioni quanto mai interessanti, buona lettura dl https://www.weforum.org/press/2021/08/young-people-have-more-faith-in-algor… _________________________ don Luca Peyron Direttore Ufficio per la Pastorale Universitaria Arcidiocesi di Torino www.universitari.to.it via XX settembre 83, Torino tel. 011 5156239

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Researchers Create 'Master Faces' to Bypass Facial Recognition
by Alberto Cammozzo Aug. 12, 2021

Aug. 12, 2021

<https://www.vice.com/en/article/k78ygn/researchers-create-master-faces-to-b…> Researchers Create 'Master Faces' to Bypass Facial Recognition According to the paper, their findings imply that facial recognition systems are “extremely vulnerable.” Researchers have demonstrated a method to create "master faces," computer generated faces that act like master keys for facial recognition systems, and can impersonate several identities with what the researchers claim is a high probability of success. In their paper <https://arxiv.org/pdf/2108.01077.pdf>, researchers at the Blavatnik School of Computer Science and the School of Electrical Engineering in Tel Aviv detail how they successfully created nine "master key" faces that are able to impersonate almost half the faces in a dataset of three leading face recognition systems. The researchers say their results show these master faces can successfully impersonate over 40 percent of the population in these systems without any additional information or data of the person they are identifying. The paper cites previous research which showed a similar method for creating master fingerprints <https://ieeexplore.ieee.org/document/7893784>. According to the paper, their findings imply that facial recognition systems are “extremely vulnerable.” The "master key" faces tended to be older, and didn't have glasses or facial hair. The researchers tested their methods against three deep face recognition systems–Dlib, FaceNet, and SphereFace. Lead author Ron Shmelkin told Motherboard that they used these systems because they are capable of recognizing “high-level semantic features” of the faces that are more sophisticated than just skin color or lighting effects. The researchers used a StyleGAN to generate the faces and then used an evolutionary algorithm and neural network to optimize and predict their success. The evolutionary strategy then creates iterations, or generations, of candidates of varying success rates. The researchers then used the algorithm to train a neural network, to classify the best candidates as the most promising ones. This is what teaches it to predict candidates’ success and, in turn, direct the algorithm to generate better candidates with a higher probability of passing. “We are interested in further exploring the possibility of using the master faces generated by our method in order to help protect existing facial recognition systems from such attacks,” Shmelkin told Motherboard. The researchers even predict that their master faces could be animated using deepfake technology to bypass liveness detection, which is used to determine whether a biometric sample is real or fake. The paper also notes that white males over the age of 60 in the University of Massachusetts’ Labeled Faces in the Wild (LFW) dataset tended to be less varied compared to younger groups, so much of that group could be covered by a single older master face. Additionally, only two of the nine master faces created were female, which the paper notes matches the “much lower frequency” of female faces in the LFW dataset (22 percent.) The success of their findings shows how facial recognition software can be flawed and biased. Its continued use by law enforcement has resulted in multiple wrongful arrests <https://www.vice.com/en/article/xgx5gd/man-wrongfully-arrested-by-facial-re…>, even when it has proven to be easy to tamper with <https://www.vice.com/en/article/m7e9qv/hackers-fool-facial-recognition-into…>.

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EvilModel: Hiding Malware Inside of Neural Network Models
by 380° Aug. 10, 2021

Aug. 10, 2021

Buongiorno, mi sono sempre chiesto /se/, essendo «poorly explainable» (assimilabili a codice binario o solo troppo complessi?), i modelli di machine learning non fossero un vettore di infezione ideale. «EvilModel: Hiding Malware Inside of Neural Network Models» Submitted on 19 Jul 2021 (v1), last revised 5 Aug 2021 (this version, v4) --8<---------------cut here---------------start------------->8--- Abstract: Delivering malware covertly and evasively is critical to advanced malware campaigns. In this paper, we present a new method to covertly and evasively deliver malware through a neural network model. Neural network models are poorly explainable and have a good generalization ability. By embedding malware in neurons, the malware can be delivered covertly, with minor or no impact on the performance of neural network. Meanwhile, because the structure of the neural network model remains unchanged, it can pass the security scan of antivirus engines. Experiments show that 36.9MB of malware can be embedded in a 178MB-AlexNet model within 1% accuracy loss, and no suspicion is raised by anti-virus engines in VirusTotal, which verifies the feasibility of this method. With the widespread application of artificial intelligence, utilizing neural networks for attacks becomes a forwarding trend. We hope this work can provide a reference scenario for the defense on neural network-assisted attacks. --8<---------------cut here---------------end--------------->8--- Non ho letto il paper, solo l'abstract, e capisco perché un semplice antivirus (porello) non è in grado di distinguere il virus dagli altri neuroni; una possibile soluzione non potrebbe essere quella di fornire anche un hash (chessò un sha512) che garantisca che il modello non sia stato alterato? Oltre questo, non /dovrebbe/ comunque essere messa a disposizione tutta la catena di build e gli input per poter riprodurre il modello bit-per-bit, ala "reproducible build"? Oltre a questo, l'intero sistema generato con tecniche ML non dovrebbe essere completamente bootstrappable? Esagero? Saluti, 380° -- 380° (Giovanni Biscuolo public alter ego) «Noi, incompetenti come siamo, non abbiamo alcun titolo per suggerire alcunché» Disinformation flourishes because many people care deeply about injustice but very few check the facts. Ask me about <https://stallmansupport.org>.

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Virus laziale
by TEV S.r.L. Aug. 10, 2021

Aug. 10, 2021

Avete notizie precise dal fronte Virus Laziale? A me pare tutta una montatura. Enzo Viscuso

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Climate Change 2021: The Physical Science Basis
by don Luca Peyron Aug. 10, 2021

Aug. 10, 2021

Una tecnologia per il pianeta, questa certamente un'urgenza. Quanto ci preoccupiamo di una tecnica che risolva problemi tecnici, come il ponte sullo stretto, ed intanto si muore ancora di fame? Che il clima torrido scaldi anche il cuore e riattivi sinapsi sociali addormentate da un sistema tecnico che ha alimentato anche troppo se stesso. Buona lettura dl https://www.ipcc.ch/report/sixth-assessment-report-working-group-i/ _________________________ don Luca Peyron Direttore Ufficio per la Pastorale Universitaria Arcidiocesi di Torino www.universitari.to.it via XX settembre 83, Torino tel. 011 5156239

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Riforma diritto d’autore ed equo compenso: cosa cambia in Italia per gli editori
by don Luca Peyron Aug. 10, 2021

Aug. 10, 2021

Cominciato l'iter di ricezione della normativa europea, un primo sunto Buona lettura dl https://www.money.it/Riforma-diritto-autore-equo-compenso-cosa-cambia-Itali… _________________________ don Luca Peyron Direttore Ufficio per la Pastorale Universitaria Arcidiocesi di Torino www.universitari.to.it via XX settembre 83, Torino tel. 011 5156239

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Apple's Plan to "Think Different" About Encryption Opens a Backdoor to Your Private Life
by J.C. DE MARTIN Aug. 10, 2021

Aug. 10, 2021

Spero di sbagliarmi, ma ho la sensazione che stiano cadendo tutti gli argini residui. jc *Apple's Plan to "Think Different" About Encryption Opens a Backdoor to Your Private Life** * By India McKinney and Erica Portnoy August 5, 2021 Apple has announced impending changes to its operating systems that include new “protections for children” features in iCloud and iMessage. If you’ve spent any time following the Crypto Wars <https://www.vice.com/en/article/wjwpmn/ahhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhh…>, you know what this means: Apple is planning to build a backdoor into its data storage system and its messaging system. Child exploitation is a serious problem, and Apple isn't the first tech company to bend its privacy-protective stance in an attempt to combat it. But that choice will come at a high price for overall user privacy. Apple can explain at length <https://www.apple.com/child-safety/>how its technical implementation will preserve privacy and security in its proposed backdoor, but at the end of the day, even a thoroughly documented, carefully thought-out, and narrowly-scoped backdoor is still a backdoor. […] Continua qui: https://www.eff.org/deeplinks/2021/08/apples-plan-think-different-about-enc…

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Apple plans to scan US iPhones for child sexual abuse images | Apple | The Guardian
by Alberto Cammozzo Aug. 9, 2021

Aug. 9, 2021

<https://www.theguardian.com/technology/2021/aug/06/apple-plans-to-scan-us-i…> Apple will scan photo libraries stored on iPhones in the US for known images of child sexual abuse, the company says, drawing praise from child protection groups but crossing a line that privacy campaigners warn could have dangerous ramifications. The company will also examine the contents of end-to-end encrypted messages for the first time. Sign up to Alex Hern’s weekly technology newsletter, TechScape. Apple’s tool, called neuralMatch, will scan images before they are uploaded to the company’s iCloud Photos online storage, comparing them against a database of known child abuse imagery. If a strong enough match is flagged, then Apple staff will be able to manually review the reported images, and, if child abuse is confirmed, the user’s account will be disabled and the National Center for Missing and Exploited [...]

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Una tavoletta babilonese riscrive la storia della matematica
by don Luca Peyron Aug. 9, 2021

Aug. 9, 2021

Tecnica, matematica, storia: cielo e terra si confermano a vicenda. Notizia estiva che ci aiuta a guardare avanti senza smettere di studiare le nostre radici. Buona lettura a chi lo desidera dl https://www.ansa.it/canale_scienza_tecnica/notizie/ragazzi/news/2021/08/06/… _________________________ don Luca Peyron Direttore Ufficio per la Pastorale Universitaria Arcidiocesi di Torino www.universitari.to.it via XX settembre 83, Torino tel. 011 5156239

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