{"id":8944,"date":"2024-01-06T20:37:14","date_gmt":"2024-01-06T20:37:14","guid":{"rendered":"https:\/\/dailyai.com\/?p=8944"},"modified":"2024-01-06T23:30:16","modified_gmt":"2024-01-06T23:30:16","slug":"the-nist-publishes-paper-on-four-possible-types-of-generative-ai-attacks","status":"publish","type":"post","link":"https:\/\/dailyai.com\/nb\/2024\/01\/the-nist-publishes-paper-on-four-possible-types-of-generative-ai-attacks\/","title":{"rendered":"NIST publiserer en artikkel om fire mulige typer generative AI-angrep"},"content":{"rendered":"

Det amerikanske National Institute of Standards and Technology (NIST) har uttrykt bekymring for sikkerheten til prediktive og generative AI-systemer.<\/b><\/p>\n

If\u00f8lge Apostol Vassilev, dataforsker ved NIST, er disse teknologiene fortsatt s\u00e5rbare for en rekke ulike angrep, til tross for fremskritt innen sikkerhet.<\/span><\/p>\n

I en samarbeidsdokument<\/a> med tittelen \"<\/span>Adversarial maskinl\u00e6ring: En taksonomi og terminologi for angrep og avb\u00f8tende tiltak<\/span>Vassilev, sammen med kolleger fra Northeastern University og Robust Intelligence, kategoriserer sikkerhetsrisikoen som AI-systemer utgj\u00f8r.\u00a0<\/span><\/p>\n

Vassilev uttalte: \"Til tross for de betydelige fremskrittene AI og maskinl\u00e6ring har gjort, er disse teknologiene s\u00e5rbare for angrep som kan for\u00e5rsake spektakul\u00e6re feil med alvorlige konsekvenser.\"\u00a0<\/span><\/p>\n

Han advarte ogs\u00e5 mot alle selskaper som hevder \u00e5 tilby \"fullstendig sikker AI\".<\/span><\/p>\n

Dette er en del av <\/span>NIST-initiativet for p\u00e5litelig og ansvarlig AI<\/span><\/a>, i tr\u00e5d med amerikanske myndigheters m\u00e5l for KI-sikkerhet. Den tar for seg teknikker for kontradiktorisk maskinl\u00e6ring, med fokus p\u00e5 fire hovedsikkerhetsproblemer: omg\u00e5else, forgiftning, personvern og misbruksangrep.<\/span><\/p>\n

Unnvikelsesangrep skjer etter utplassering, ved at man endrer inndata for \u00e5 forvirre AI-systemene. For eksempel ved \u00e5 endre stoppskilt slik at autonome kj\u00f8ret\u00f8y feiltolker dem som fartsgrenseskilt, eller ved \u00e5 lage villedende kj\u00f8refeltmarkeringer for \u00e5 lede kj\u00f8ret\u00f8yene p\u00e5 villspor.<\/p>\n

Ved forgiftningsangrep introduseres korrupte data under oppl\u00e6ringen. Dette kan inneb\u00e6re at det ofte legges inn upassende spr\u00e5k i oppl\u00e6ringsdatasettene, noe som f\u00f8rer til at en chatbot tar i bruk dette spr\u00e5ket i kundeinteraksjoner.<\/p>\n

Personvernangrep har som m\u00e5l \u00e5 hente ut sensitiv informasjon om den kunstige intelligensen eller oppl\u00e6ringsdataene, ofte ved hjelp av omvendt manipulering. Dette kan inneb\u00e6re \u00e5 bruke chatbotens svar for \u00e5 finne ut hvor den er oppl\u00e6rt og hvilke svakheter den har.<\/p>\n

Misbruksangrep manipulerer legitime kilder, for eksempel nettsider, og gir AI-systemer falsk informasjon for \u00e5 endre hvordan de fungerer. Dette skiller seg fra forgiftningsangrep, som \u00f8delegger selve oppl\u00e6ringsprosessen.<\/p>\n

Unnvikelsesangrep inneb\u00e6rer \u00e5 skape eksempler som kan lure AI-systemer under utplassering, for eksempel ved \u00e5 feilidentifisere stoppskilt i selvkj\u00f8rende kj\u00f8ret\u00f8y.\u00a0<\/span><\/p>\n

Alina Oprea fra Northeastern University, som var involvert i arbeidet med studie<\/a>, <\/span>\"De fleste av disse angrepene er ganske enkle \u00e5 gjennomf\u00f8re og krever et minimum av kunnskap om AI-systemet og begrensede motstanderegenskaper\", forklarer han.<\/p>\n

NIST kritiseres for koblinger til AI-tenketank<\/h2>\n

Separat, <\/span>Det har blitt reist bekymringer<\/span><\/a> om et planlagt AI-forskningssamarbeid mellom NIST og RAND Corp.<\/span><\/p>\n

RAND, kjent for sine forbindelser til teknologimilliard\u00e6rer og <\/span>effektiv altruisme-bevegelse<\/span><\/a>spilte en viktig r\u00e5dgivende rolle i utformingen av<\/span> Bekendtg\u00f8relse om AI-sikkerhed<\/span><\/a>.\u00a0<\/span><\/p>\n

Medlemmer av komiteen for vitenskap, romfart og teknologi i Representantenes hus, deriblant Frank Lucas og Zoe Lofgren, kritiserte mangelen p\u00e5 \u00e5penhet i dette partnerskapet.\u00a0<\/span><\/p>\n

Komiteens bekymringer er todelt: For det f\u00f8rste stiller de sp\u00f8rsm\u00e5l ved hvorfor RAND ikke ble valgt ut til \u00e5 utf\u00f8re denne forskningen p\u00e5 kunstig intelligens.\u00a0<\/span><\/p>\n

N\u00e5r offentlige etater som NIST gir forskningsstipend, \u00e5pner de vanligvis opp for at ulike organisasjoner kan s\u00f8ke, noe som sikrer en rettferdig utvelgelsesprosess. Men i dette tilfellet ser det ut til at RAND ble valgt uten en slik prosess.<\/span><\/p>\n

For det andre er det en viss uro knyttet til RANDs fokus p\u00e5 AI-forskning. RAND har v\u00e6rt involvert i studier av kunstig intelligens og biosikkerhet, og har nylig mottatt betydelige midler til dette arbeidet fra kilder som er n\u00e6rt knyttet til teknologibransjen.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"

Det amerikanske National Institute of Standards and Technology (NIST) har uttrykt bekymring for sikkerheten til prediktive og generative AI-systemer. If\u00f8lge Apostol Vassilev, informatiker ved NIST, er disse teknologiene fortsatt s\u00e5rbare for en rekke ulike angrep, til tross for fremskritt innen sikkerhet. I en samarbeidsartikkel med tittelen \"Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations\" kategoriserer Vassilev, sammen med kolleger fra Northeastern University og Robust Intelligence, sikkerhetsrisikoen som AI-systemer utgj\u00f8r. Vassilev uttalte: \"Til tross for de betydelige fremskrittene AI og maskinl\u00e6ring har gjort, er disse teknologiene s\u00e5rbare for angrep som kan for\u00e5rsake spektakul\u00e6re feil<\/p>","protected":false},"author":2,"featured_media":8945,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[512],"class_list":["post-8944","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-nist"],"yoast_head":"\nThe NIST publishes paper on four possible types of generative AI attacks | DailyAI<\/title>\n<meta name=\"description\" content=\"The US National Institute of Standards and Technology (NIST) has released a new paper on the risks of generative AI.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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