- nexa - server-nexa.polito.it

saluti Intelligence e università

by Mauro Alovisio

Gent.mi segnalo articolo di interesse del Prof. Roberto Caso su un disegno di legge su obbligo di collaborazione delle università e ielle società pubbliche con i servizi segreti https://www.agendadigitale.eu/sicurezza/privacy/ddl-sicurezza-e-intelligenc… Cordiali saluti

Jan. 30, 2025

Re: [nexa] "OpenAI Furious DeepSeek Might Have Stolen All the Data OpenAI Stole From Us"

by GC F

Immagino si lamentino di violazione di segreti industriali (teoricamente il dataset può essere oggetto di protezione da SI) e competizione sleale, non di violazione dei diritti autoriali di cui invece si è discusso molto finora. Giancarlo On Thu, Jan 30, 2025 at 7:14 AM J.C. DE MARTIN < juancarlos.demartin(a)polito.it> wrote: > *OpenAI Furious DeepSeek Might Have Stolen All the Data OpenAI Stole From > Us* > > *OpenAI shocked that an AI company would train on someone else's data > without permission or compensation.* > > Jason Koebler > > Jan 29, 2025 at 9:43 AM > > The narrative that OpenAI, Microsoft, and freshly minted White House “AI > czar” David Sacks are now pushing to explain why DeepSeek was able to > create a large language model that outpaces OpenAI’s while spending orders > of magnitude less money and using older chips is that DeepSeek used > OpenAI’s data unfairly and without compensation. Sound familiar? > > Both Bloomberg and the Financial Times are reporting that Microsoft and > OpenAI have been probing whether DeepSeek improperly trained the R1 model > that is taking the AI world by storm on the outputs of OpenAI models. > > [...] > > continua qui: > https://www.404media.co/openai-furious-deepseek-might-have-stolen-all-the-d… >

Jan. 30, 2025

Re: [nexa] Nuovo Community Article "Anticipare il rischio: come il foresight può supportare la normativa in ambito digitale"

by Alfredo Bregni

Saluti a tutti. Io stesso una volta ero per anticipare il futuro, ...poi ho incrociato a) Nassim Nicholas Taleb (mi pare "Giocati dal caso", non "Il cigno nero") e b) i fondi per la ricerca della UE: - Il primo dice: "Il vero rischio è quello che non ti aspetti."; - La seconda prevede la possibile innovazione con il microdettaglio di un microscopio elettronico (dimenticando che "la vera innovazione è quella che non ti aspetti"). - Si noti la precisa assonanza... Quindi ben venga preoccuparci di quanto pensiamo ci aspetti (e spingere il pensiero più oltre possibile, a immaginare quello che non riusciamo a pensare ci possa accadere, ...che è un ossimoro plateale), però ricordiamoci che la cosa presenta dei "robustissimi" limiti. Invalicabili. E magari diciamo alla UE -- io ci ho provato, e l'interlocutore non sapeva cosa dire (...ma poi non ha alzato una paglia) -- di destinare il 40% dei fondi di ricerca ad "unexpected innovation", con tre saggi che decidono senza tanti parametri e parametrini inutili. Tanto, è sempre l'innovazione che ci toglie dal guano in cui ci siamo messi (o ci metteremo) da soli, ...per riprendere -- letteralmente -- l'esempio di New York. ----- Original Message ----- From: Nexa - Media To: nexa(a)server-nexa.polito.it Sent: Thursday, January 30, 2025 12:23 PM Subject: [nexa] Nuovo Community Article "Anticipare il rischio: come il foresight può supportare la normativa in ambito digitale" Gentilissime, gentilissimi, Vi segnaliamo con piacere la pubblicazione di un nuovo Community Article, dal titolo "Anticipare il rischio: come il foresight può supportare la normativa in ambito digitale", a cura di Stefano Leucci e Giuseppe Vaciago, entrambi Fellow del Centro Nexa. L'articolo è consultabile al seguente link: https://nexa.polito.it/anticipare-il-rischio/ Vi ringraziamo per l'attenzione, Un saluto cordiale, -- Valeria Bergantino Communication Manager Nexa Center for Internet & Society Politecnico di Torino - DAUIN Via Pier Carlo Boggio, 65/A - 10138 Torino web: https://nexa.polito.it/ mail: valeria.bergantino(a)polito.it tel: 3473443585

Jan. 30, 2025

[CfP COMNET SI] [SHORT FINAL DEADLINE EXTENSION - February 14, 2025] Elsevier COMNET Special Issue on Generative and Explainable AI for Internet Traffic and Network Architectures

by Antonio Montieri

Dear colleagues, Our apologies if you receive multiple copies of this message. ********************************************************************** CALL FOR PAPERS Special Issue on Generative and Explainable AI for Internet Traffic and Network Architectures Elsevier Computer Networks https://www.sciencedirect.com/journal/computer-networks/about/call-for-pape… *(EXTENDED Submission deadline: February 14, 2025)* ********************************************************************** We are pleased to announce a call for papers for a special issue of Elsevier Computer Networks journal, focusing on the transformative potential of generative and explainable AI in Internet traffic analysis and network architectures. As Internet-connected devices multiply and traffic data grows exponentially, traditional methods are increasingly challenged. This special issue aims to highlight how generative AI can synthesize realistic traffic data, automate network configurations, and enhance security measures. Additionally, explainable AI can provide deeper insights into network behaviors, improving transparency, trust, and overall network performance. We invite you to contribute to this pioneering special issue and lead the advancement of AI-driven innovations in Internet traffic analysis and network architectures. Key Topics of Interest include but are not limited to the following: ----------------------- - Generative AI methods to synthesize realistic and diverse traffic data - Automatic network configuration and management utilizing Generative AI - Applications of Large Language Models (LLMs) in network traffic generation - Prompt Engineering for LLMs in network traffic analysis, management, and security - Generative AI for enhancing network security and intrusion detection - Assessing the robustness and reliability of Generative AI in network management, including standardized benchmarks and datasets - Explainable AI techniques for network traffic analysis and management tools - Human-in-the-loop AI and the integration of interpretability into AI-driven traffic analysis - Ensuring fairness, accountability, and transparency in AI applications for networking - Real-world applications and case studies showcasing Generative and Explainable AI in network traffic analysis, management, and security - Bridging the gap between network data explanation and actionable interpretability - Techniques for improving the trust and practical use of data-driven network analysis methods Guest Editors: -------------- - Antonio Montieri, PhD - Università degli Studi di Napoli Federico II, Napoli, Italy (antonio.montieri(a)unina.it) - Danilo Giordano, PhD - Politecnico di Torino, Torino, Italy (danilo.giordano(a)polito.it) - Claudio Fiandrino, PhD - IMDEA Networks Institute, Madrid, Spain (claudio.fiandrino(a)imdea.org) - Jonatan Krolikowski, PhD - Huawei Technologies France SAS, Boulogne Billancourt, France (jonatan.krolikowski(a)huawei.com) Important Dates: ---------------- - Submission Open Date: July 1, 2024 - Final Manuscript Submission Deadline: February 14, 2025 (EXTENDED) - Editorial Acceptance Deadline: May 15, 2025 Manuscript Submission Information: ----------------------------------- The journal's submission platform (https://www.editorialmanager.com/comnet/default.aspx) is available for receiving submissions to this Special Issue from July 1st, 2024. Authors are advised to follow the Guide for Authors to prepare their manuscripts and select the article type “VSI: GenXAI for Internet” when submitting online. More information about the Special Issue, the Guide for Authors, and the submission portal are available at the following link: https://www.sciencedirect.com/journal/computer-networks/about/call-for-pape… ********************************************************************** SPECIAL ISSUE DETAILS ********************************************************************** In the realm of Internet traffic analysis, the advent of Artificial Intelligence (AI) has marked a significant paradigm shift. With the proliferation of Internet-connected devices and the exponential growth of traffic data, traditional traffic analysis methods are struggling to cope with the sheer volume and complexity of modern networks. Moreover, the dynamic nature of Internet traffic patterns and the emergence of sophisticated cyber threats further exacerbate the challenges faced by network operators and cybersecurity professionals. In response, there is a pressing need for advanced analytical tools that can provide accurate Internet traffic “visibility”, enable actionable insights into traffic behavior, identify anomalies and intrusions, and ultimately enhance network security and performance. On the other hand, the collection, segmentation, and labeling of traffic datasets are cumbersome processes, often requiring human experts to guide the different stages. Additionally, factors like the dynamic nature of traffic, privacy concerns, and the limited samples of certain traffic types (e.g., network attacks, IoT devices) further challenge data collection. Moreover, while data-driven techniques have the potential for outstanding performance and adaptability, they often operate as black-box systems, making it difficult to understand their behavior, improve their performance, or protect them from potential attacks. This limits the interpretability and trust in these methods, affecting their practical use. The integration of generative and explainable AI techniques presents a promising avenue for addressing these challenges. By harnessing the power of AI to generate realistic traffic data and provide interpretable insights, researchers and practitioners can overcome the limitations of traditional traffic analysis methods. Generative AI models enable the creation of diverse and representative traffic datasets, facilitating the training of AI-driven models for intrusion detection and network optimization. Meanwhile, explainable AI techniques enhance the transparency and trustworthiness of AI-driven traffic analysis, enabling network operators to understand and interpret the decisions made by AI methods. This special issue aims to delve into the methodological, technical, and practical aspects of leveraging generative and explainable AI for Internet traffic analysis and network architectures. By focusing on these cutting-edge topics, we seek to provide a platform for researchers and practitioners to explore innovative approaches, share insights, and advance state of the art. The special issue will encompass a wide range of themes, including AI-driven generation of standardized traffic datasets, network management aided by generative AI, interpretable and trustworthy AI solutions for Internet traffic analysis, and real-world applications of generative and explainable AI in network optimization and security. ********************************************************************** -- *Antonio Montieri, Ph.D.* *Assistant Professor (RTDa)* *Dipartimento di Ingegneria Elettrica e delle Tecnologie dell'Informazione (DIETI)University of Napoli Federico IIVia Claudio 21 -- 80125 Napoli (Italy)Phone: +39 081 76 83821 - Fax: +39 081 76 83816Email: antonio.montieri(a)unina.it <antonio.montieri(a)unina.it> <antonio.montieri(a)unina.it>WWW: http://wpage.unina.it/antonio.montieri <http://wpage.unina.it/antonio.montieri> <http://wpage.unina.it/antonio.montieri>* *Skype ID: antmontieri*

Jan. 30, 2025

Apple chips can be hacked to leak secrets from Gmail, iCloud, and more

by Giacomo Tesio

Apple-designed chips powering Macs, iPhones, and iPads contain two newly discovered vulnerabilities that leak credit card information, locations, and other sensitive data from the Chrome and Safari browsers as they visit sites such as iCloud Calendar, Google Maps, and Proton Mail. The vulnerabilities, affecting the CPUs in later generations of Apple A- and M-series chip sets, open them to side channel attacks, a class of exploit that infers secrets by measuring manifestations such as timing, sound, and power consumption. Both side channels are the result of the chips’ use of speculative execution, a performance optimization that improves speed by predicting the control flow the CPUs should take and following that path, rather than the instruction order in the program. continua su <https://arstechnica.com/security/2025/01/newly-discovered-flaws-in-apple-ch…> se usate iCosi, attenti ai siti che visitate. Giacomo

Jan. 30, 2025

Nuovo Community Article "Anticipare il rischio: come il foresight può supportare la normativa in ambito digitale"

by Nexa - Media

Gentilissime, gentilissimi, Vi segnaliamo con piacere la pubblicazione di un nuovo Community Article, dal titolo "Anticipare il rischio: come il foresight può supportare la normativa in ambito digitale", a cura di Stefano Leucci e Giuseppe Vaciago, entrambi Fellow del Centro Nexa. L'articolo è consultabile al seguente link: https://nexa.polito.it/anticipare-il-rischio/ Vi ringraziamo per l'attenzione, Un saluto cordiale, -- Valeria Bergantino Communication Manager Nexa Center for Internet & Society Politecnico di Torino - DAUIN Via Pier Carlo Boggio, 65/A - 10138 Torino web: https://nexa.polito.it/ mail: valeria.bergantino(a)polito.it<mailto:valeria.bergantino@polito.it> tel: 3473443585

Jan. 30, 2025

Re: [nexa] centrali-nucleari-per-lintelligenza-artificiale.pdf

by maurizio lana

Eric Schmidt alla fine dell'anno scorso (6 ottobre 2024) l'aveva detto: gli obiettivi di contenimento del riscaldamento globale non possono essere raggiunti a causa dei consumi elettrici dei sistemi di IA (sviluppo+uso), quindi diamoci dentro con lo sviluppo dei sistemi di IA perché ci daranno la risposta al problema se ne è parlato ad esempio qui: Pivot to AI. «Eric Schmidt: ‘We’re not going to hit the climate goals. I’d rather bet on AI solving the problem.’», 6 ottobre 2024. https://pivot-to-ai.com/2024/10/06/eric-schmidt-were-not-going-to-hit-the-c…. e qui il video di Schmidt (che nel sito della sua fondazione non c'è più; viva san Youtube) /[Erich Schmidt on AI and energy]/. SCSP’s inaugural AI+Energy Summit, s.d. https://www.youtube.com/watch?v=oC46CzxT750. Maurizio Il 30/01/25 09:36, Norberto Patrignani ha scritto: > da ilmanifesto di oggi ------------------------------------------------------------------------ dialogare tra di noi per costruire una democrazia, l’unica istituzione di vita comune che non sia fondata sulla paura di morire michel dardenne ------------------------------------------------------------------------ Maurizio Lana Università del Piemonte Orientale Dipartimento di Studi Umanistici Piazza Roma 36 - 13100 Vercelli

Jan. 30, 2025

Re: [nexa] "OpenAI Furious DeepSeek Might Have Stolen All the Data OpenAI Stole From Us"

by Enrico Nardelli

Il 30/01/2025 08:14, J.C. DE MARTIN ha scritto: > /... an AI company would train on someone else's data without > permission or compensation./ Hanno la faccia come ... <CENSORED> -- -- EN https://www.hoepli.it/libro/la-rivoluzione-informatica/9788896069516.html ====================================================== Prof. Enrico Nardelli Past President di "Informatics Europe" Direttore del Laboratorio Nazionale "Informatica e Scuola" del CINI Dipartimento di Matematica - Università di Roma "Tor Vergata" Via della Ricerca Scientifica snc - 00133 Roma home page: https://www.mat.uniroma2.it/~nardelli blog: https://link-and-think.blogspot.it/ tel: +39 06 7259.4204 fax: +39 06 7259.4699 mobile: +39 335 590.2331 e-mail: nardelli(a)mat.uniroma2.it online meeting: https://blue.meet.garr.it/b/enr-y7f-t0q-ont ====================================================== --

Jan. 30, 2025

centrali-nucleari-per-lintelligenza-artificiale.pdf

by Norberto Patrignani

da ilmanifesto di oggi un caro saluto Norberto

Jan. 30, 2025

"OpenAI Furious DeepSeek Might Have Stolen All the Data OpenAI Stole From Us"

by J.C. DE MARTIN

*OpenAI Furious DeepSeek Might Have Stolen All the Data OpenAI Stole From Us* /OpenAI shocked that an AI company would train on someone else's data without permission or compensation./ Jason Koebler Jan 29, 2025 at 9:43 AM The narrative that OpenAI, Microsoft, and freshly minted White House “AI czar” David Sacks are now pushing to explain why DeepSeek was able to create a large language model that outpaces OpenAI’s while spending orders of magnitude less money and using older chips is that DeepSeek used OpenAI’s data unfairly and without compensation. Sound familiar? Both Bloomberg and the Financial Times are reporting that Microsoft and OpenAI have been probing whether DeepSeek improperly trained the R1 model that is taking the AI world by storm on the outputs of OpenAI models. [...] continua qui: https://www.404media.co/openai-furious-deepseek-might-have-stolen-all-the-d…

Jan. 30, 2025