Intelligenza artificiale e sicurezza: opportunità, rischi e raccomandazioni

L'IA (o intelligenza artificiale) è una disciplina in forte espansione negli ultimi anni e lo sarà sempre più nel prossimo futuro: tuttavia è dal 1956 che l’IA studia l’emulazione dell’intelligenza da parte delle macchine, intese come software e in certi casi hardware. L’IA è nata dall’idea di costruire macchine che - ispirandosi ai processi legati all’intelligenza umana - siano in grado di risolvere problemi complessi, per i quali solitamente si ritiene che sia necessario un qualche tipo di ragionamento intelligente. La principale area di ricerca e applicazione attuale dell’IA è il machine learning (algoritmi che imparano e si adattano in base ai dati che ricevono), che negli ultimi anni ha trovato ampie applicazioni grazie alle reti neurali (modelli matematici composti da neuroni artificiali) che a loro volta hanno consentito la nascita del deep learning (reti neurali di maggiore complessità). Appartengono al mondo dell’IA anche i sistemi esperti, la visione artificiale, il riconoscimento vocale, l’elaborazione del linguaggio naturale, la robotica avanzata e alcune soluzioni di cybersecurity. Quando si parla di IA c'è chi ne è entusiasta pensando alle opportunità, altri sono preoccupati poiché temono tecnologie futuristiche di un mondo in cui i robot sostituiranno l'uomo, gli toglieranno il lavoro e decideranno al suo posto. In realtà l'IA è ampiamente utilizzata già oggi in molti campi, ad esempio nei cellulari, negli oggetti smart (IoT), nelle industry 4.0, per le smart city, nei sistemi di sicurezza informatica, nei sistemi di guida autonoma (drive o parking assistant), nei chat bot di vari siti web; questi sono solo alcuni esempi basati tutti su algoritmi tipici dell’intelligenza artificiale. Grazie all'IA le aziende possono avere svariati vantaggi nel fornire servizi avanzati, personalizzati, prevedere trend, anticipare le scelte degli utenti, ecc. Ma non è tutto oro quel che luccica: ci sono talvolta problemi tecnici, interrogativi etici, rischi di sicurezza, norme e legislazioni non del tutto chiare. Le organizzazioni che già adottano soluzioni basate sull’IA, o quelle che intendono farlo, potrebbero beneficiare di questa pubblicazione per approfondirne le opportunità, i rischi e le relative contromisure. La Community for Security del Clusit si augura che questa pubblicazione possa fornire ai lettori un utile quadro d’insieme di una realtà, come l’intelligenza artificiale, che ci accompagnerà sempre più nella vita personale, sociale e lavorativa.AI (or artificial intelligence) is a booming discipline in recent years and will be increasingly so in the near future.However, it is since 1956 that AI has been studying the emulation of intelligence by machines, understood as software and in some cases hardware. AI arose from the idea of building machines that-inspired by processes related to human intelligence-are able to solve complex problems, for which it is usually believed that some kind of intelligent reasoning is required. The main current area of AI research and application is machine learning (algorithms that learn and adapt based on the data they receive), which has found wide applications in recent years thanks to neural networks (mathematical models composed of artificial neurons), which in turn have enabled the emergence of deep learning (neural networks of greater complexity). Also belonging to the AI world are expert systems, computer vision, speech recognition, natural language processing, advanced robotics and some cybersecurity solutions. When it comes to AI there are those who are enthusiastic about it thinking of the opportunities, others are concerned as they fear futuristic technologies of a world where robots will replace humans, take away their jobs and make decisions for them. In reality, AI is already widely used in many fields, for example, in cell phones, smart objects (IoT), industries 4.0, for smart cities, cybersecurity systems, autonomous driving systems (drive or parking assistant), chat bots on various websites; these are just a few examples all based on typical artificial intelligence algorithms. Thanks to AI, companies can have a variety of advantages in providing advanced, personalized services, predicting trends, anticipating user choices, etc. But not all that glitters is gold: there are sometimes technical problems, ethical questions, security risks, and standards and legislation that are not entirely clear. Organizations already adopting AI-based solutions, or those planning to do so, could benefit from this publication to learn more about the opportunities, risks, and related countermeasures. Clusit's Community for Security hopes that this publication will provide readers with a useful overview of a reality, such as artificial intelligence, that will increasingly accompany us in our personal, social and working lives

In vitro effects of tyrosine kinase inhibitor imatinib on glioblastoma cell proliferation

Glioblastoma (GBL) is the most malignant brain tumour in adults, causing the death of most patients within 9-12 months of diagnosis. Treatment is based on a combination of surgery, radiation therapy, and chemotherapy. With these treatment modalities, however, responses are extremely poor, so identification of novel treatment strategies is highly warranted. Platelet-derived growth factors (PDGF) and their receptors are commonly coexpressed in GBL, suggesting that stimulation of autocrine PDGF receptors may contribute to their growth. Interest in these receptors as drug target for glioblastoma treatment has increased with the clinical availability of the PDGFR kinase inhibitor antagonist imatinib mesylate (STI571). In this study, T98G and A172 human GBL cell lines were analysed for their sensitivity to treatment with imatinib. In particular, we focussed our attention on analysis of DNA distribution by flow cytometry at different times of incubation with different imatinib concentrations (1-30 microM: ). Our results show that imatinib induces growth arrest in T98G and A172 cells in the G(0)/G(1) phase of the cell cycle, at all the concentrations tested, as early as 24 h after treatment. However we have also seen, by means of annexin V staining, that at 20 and 30 microM: concentrations, in concomitance with a significant growth arrest in the G(0)/G(1) phase, there is an increase of apoptotic cells 48 h after treatment, suggesting that imatinib at low concentrations (1-10 microM: ) could act as a cytostatic agent whereas at high concentrations (20, 30 microM: ) it mainly behaves as a cytotoxic agent

Radiation induced perturbation of cell-to-cell signaling and communication

The investigation of the bystander phenomena (i.e. the induction of damage in cells not directly traversed by radiation) is strictly related to the study of the mechanisms of intercellular communication and of the perturbative effects of radiation. A new possible way to try to solve the bystander puzzle is through a ‘systems radiation biology’ approach with the total integration of experimental and theoretical activities. In particular, this contribution will focus on: (1) ‘ad hoc’ experiments designed to quantify key parameters involved in intercellular signalling (focusing, as a pilot study, on release, decay and internalization of interleukine-6 molecules, their modulation by radiation, and possible differences between in vivo/in vitro behaviour); (2) the implementation and the development of two different modelling approaches: a stochastic model (based on a Monte Carlo code) that takes account of the local mechanisms of release and internalization of signalling molecules (e.g. cytokines) and an analytical model where signal molecules are treated as a population and their temporal behaviour is described by differential equations. This approach provided instruments to investigate the complex phenomena of signal transmission and the role of cell communication to guarantee (maintain) the robustness of the in vitro experimental systems against the effects of perturbations

Systèmes d'information sur les marchés agricoles en Afrique 6: Choisir et collaborer avec des partenaires

Cette fiche fait partie d'une série de fiches d'information destinées aux personnes concevant et mettant en oeuvre des systèmes d'information sur les marchés en Afriqu

Investigation of the mechanisms underpinning IL-6 cytokine release in bystander phenomena: the roles of radiation dose, radiation quality and specific ROS/RNS scavengers.

Purpose: To investigate the mechanisms regulating the pathways of the bystander transmission in vitro, focusing on the radiation-perturbed signalling (via Interleukine 6, IL-6) of the irradiated cells after exposure to low doses of different radiation types. Materials and methods: An integrated 'systems radiation biology' approach was adopted. Experimentally the level of the secreted cytokine from human fibroblasts was detected with ELISA (Enzyme-Linked ImmunoSorbent Assay) method and subsequently the data were analyzed and coupled with a phenomenological model based on differential equations to evaluate the single-cell release mechanisms. Results: The data confirmed the important effect of radiation on the IL-6 pathway, clearly showing a crucial role of the ROS (Reactive Oxygen Species) in transducing the effect of initial radiation exposure and the subsequent long-term release of IL-6. Furthermore, a systematic investigation of radiation dose/radiation quality dependence seems to indicate an increasing efficiency of high LET (Linear Energy Transfer) irradiation in the release of the cytokine. Basic hypotheses were tested, on the correlation between direct radiobiological damage and signal release and on the radiation target for this endpoint (secretion of IL-6) Conclusions: The results demonstrate the role of reactive oxygen and nitrogen species in the signaling pathways of IL-6. Furthermore the systems radiation biology approach here adopted, allowed us to test and verify hypotheses on the behavior of the single cell in the release of cytokine, after the exposure to different doses and different qualities of ionizing radiation