{"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\/da\/2024\/01\/the-nist-publishes-paper-on-four-possible-types-of-generative-ai-attacks\/","title":{"rendered":"NIST udgiver artikel om fire mulige typer af generative AI-angreb"},"content":{"rendered":"

Det amerikanske National Institute of Standards and Technology (NIST) har udtrykt bekymring for sikkerheden i pr\u00e6diktive og generative AI-systemer.<\/b><\/p>\n

If\u00f8lge Apostol Vassilev, der er datalog ved NIST, er disse teknologier trods fremskridt inden for sikkerhed stadig s\u00e5rbare over for en r\u00e6kke forskellige angreb.<\/span><\/p>\n

I en samarbejdsdokument<\/a> med titlen \"<\/span>Adversarial maskinl\u00e6ring: En taksonomi og terminologi for angreb og afv\u00e6rgeforanstaltninger<\/span>\" Vassilev kategoriserer sammen med kolleger fra Northeastern University og Robust Intelligence de sikkerhedsrisici, som AI-systemer udg\u00f8r.\u00a0<\/span><\/p>\n

Vassilev sagde: \"P\u00e5 trods af de betydelige fremskridt, som AI og maskinl\u00e6ring har gjort, er disse teknologier s\u00e5rbare over for angreb, der kan for\u00e5rsage spektakul\u00e6re fejl med alvorlige konsekvenser.\"\u00a0<\/span><\/p>\n

Han advarede ogs\u00e5 mod enhver virksomhed, der h\u00e6vder at tilbyde \"fuldt sikker AI\".<\/span><\/p>\n

Dette er en del af <\/span>NIST's initiativ for p\u00e5lidelig og ansvarlig AI<\/span><\/a>Det er i overensstemmelse med den amerikanske regerings m\u00e5l for AI-sikkerhed. Den unders\u00f8ger kontradiktoriske maskinl\u00e6ringsteknikker med fokus p\u00e5 fire hovedsikkerhedsproblemer: undvigelse, forgiftning, privatliv og misbrugsangreb.<\/span><\/p>\n

Undvigelsesangreb sker efter udrulning, hvor man \u00e6ndrer input for at forvirre AI-systemer. For eksempel ved at \u00e6ndre stopskilte, s\u00e5 autonome k\u00f8ret\u00f8jer fejll\u00e6ser dem som fartgr\u00e6nseskilte, eller ved at lave vildledende k\u00f8rebanemarkeringer for at lede k\u00f8ret\u00f8jerne p\u00e5 afveje.<\/p>\n

Ved forgiftningsangreb indf\u00f8res korrupte data under tr\u00e6ningen. Det kan indeb\u00e6re indlejring af hyppigt upassende sprog i tr\u00e6ningsdatas\u00e6t, hvilket f\u00e5r en chatbot til at anvende dette sprog i kundeinteraktioner.<\/p>\n

Angreb p\u00e5 privatlivets fred har til form\u00e5l at udtr\u00e6kke f\u00f8lsomme oplysninger om den kunstige intelligens eller dens tr\u00e6ningsdata, ofte gennem reverse-engineering-metoder. Det kan indeb\u00e6re, at man bruger en chatbots svar til at finde frem til dens tr\u00e6ningskilder og svagheder.<\/p>\n

Misbrugsangreb manipulerer legitime kilder, som f.eks. websider, og fodrer AI-systemer med falske oplysninger for at \u00e6ndre deres funktion. Dette adskiller sig fra forgiftningsangreb, som \u00f8del\u00e6gger selve tr\u00e6ningsprocessen.<\/p>\n

Undvigelsesangreb indeb\u00e6rer, at man skaber modstridende eksempler for at narre AI-systemer under udrulningen, som f.eks. at fejlidentificere stopskilte i selvk\u00f8rende biler.\u00a0<\/span><\/p>\n

Alina Oprea fra Northeastern University, som var involveret i projektet unders\u00f8gelse<\/a>, <\/span>\"De fleste af disse angreb er ret nemme at gennemf\u00f8re og kr\u00e6ver et minimum af viden om AI-systemet og begr\u00e6nsede evner hos modstanderen.\"<\/p>\n

NIST kritiseres for links til AI-t\u00e6nketank<\/h2>\n

Hver for sig, <\/span>Der er blevet udtrykt bekymring<\/span><\/a> over et planlagt AI-forskningspartnerskab mellem NIST og RAND Corp.<\/span><\/p>\n

RAND, der er kendt for sine forbindelser til tech-milliard\u00e6rer og <\/span>bev\u00e6gelse for effektiv altruisme<\/span><\/a>spillede en vigtig r\u00e5dgivende rolle i udformningen af<\/span> Bekendtg\u00f8relse om AI-sikkerhed<\/span><\/a>.\u00a0<\/span><\/p>\n

Medlemmer af House Committee on Science, Space and Technology, herunder Frank Lucas og Zoe Lofgren, kritiserede den manglende gennemsigtighed i dette partnerskab.\u00a0<\/span><\/p>\n

Udvalgets bekymringer er todelt: For det f\u00f8rste s\u00e6tter de sp\u00f8rgsm\u00e5lstegn ved, hvorfor der ikke var en konkurrencepr\u00e6get proces i forbindelse med udv\u00e6lgelsen af RAND til denne forskning i AI-sikkerhed.\u00a0<\/span><\/p>\n

N\u00e5r regeringsorganer som NIST giver forskningsbevillinger, giver de normalt forskellige organisationer mulighed for at ans\u00f8ge, hvilket sikrer en fair udv\u00e6lgelsesproces. Men i dette tilf\u00e6lde ser det ud til, at RAND blev valgt uden en s\u00e5dan proces.<\/span><\/p>\n

For det andet er der en vis uro omkring RAND's fokus p\u00e5 AI-forskning. RAND har v\u00e6ret involveret i studier af AI og biosikkerhed og har for nylig modtaget betydelige midler til dette arbejde fra kilder, der er t\u00e6t knyttet til tech-industrien.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"

Det amerikanske National Institute of Standards and Technology (NIST) har udtrykt bekymring for sikkerheden i pr\u00e6diktive og generative AI-systemer. If\u00f8lge Apostol Vassilev, der er datalog ved NIST, er disse teknologier trods fremskridt inden for sikkerhed stadig s\u00e5rbare over for en r\u00e6kke angreb. I et samarbejdspapir med titlen \"Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations\" kategoriserer Vassilev sammen med kolleger fra Northeastern University og Robust Intelligence de sikkerhedsrisici, som AI-systemer udg\u00f8r. Vassilev sagde: \"P\u00e5 trods af de betydelige fremskridt, AI og maskinl\u00e6ring har gjort, er disse teknologier s\u00e5rbare over for angreb, der kan for\u00e5rsage spektakul\u00e6re fejl<\/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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