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VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
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TZID:Asia/Kolkata
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DTSTART:19451014T230000
TZOFFSETFROM:+0630
TZOFFSETTO:+0530
TZNAME:IST
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BEGIN:VEVENT
DTSTAMP:20260813T112444Z
UID:3B54ADF5-A3C4-44E9-A781-58820217C007
DTSTART;TZID=Asia/Kolkata:20260821T190000
DTEND;TZID=Asia/Kolkata:20260821T200000
DESCRIPTION:Artificial Intelligence (AI) and Large Language Models (LLMs) a
 re rapidly\ntransforming industries\, enabling unprecedented levels of aut
 omation\,\ndecision-making\, and business innovation. However\, the widesp
 read\nadoption of AI technologies introduces new security challenges that\
 norganizations must address to protect sensitive data\, maintain trust\, a
 nd\nensure regulatory compliance.\nThis technical talk explores the evolvi
 ng cybersecurity landscape in the age\nof AI\, highlighting key threats su
 ch as prompt injection\, model manipulation\,\ndata poisoning\, adversaria
 l attacks\, insecure AI integrations\, and privacy\nrisks associated with 
 generative AI platforms. The session will provide\npractical insights into
  securing AI applications\, APIs\, cloud environments\,\nand enterprise sy
 stems while aligning with industry best practices and\nemerging regulatory
  requirements.\nParticipants will gain an understanding of AI threat model
 ing\, secure AI\ndevelopment practices\, AI red teaming\, LLM security ass
 essment\nmethodologies\, and strategies for building resilient and trustwo
 rthy AI\nsystems. Real-world case studies and practical recommendations wi
 ll be\ndiscussed to help organizations securely embrace AI-driven transfor
 mation.\n\nSpeaker(s): Rupesh Kumar Meher\, \n\nVirtual: https://events.vt
 ools.ieee.org/m/572453
LOCATION:Virtual: https://events.vtools.ieee.org/m/572453
ORGANIZER:amiya87@gmail.com
SEQUENCE:10
SUMMARY:Securing the AI Era: Cybersecurity Challenges\, LLM Risks\, and Ent
 erprise Defense Strategies
URL;VALUE=URI:https://events.vtools.ieee.org/m/572453
X-ALT-DESC:Description: <br /><p>Artificial Intelligence (AI) and Large Lan
 guage Models (LLMs) are rapidly<br>transforming industries\, enabling unpr
 ecedented levels of automation\,<br>decision-making\, and business innovat
 ion. However\, the widespread<br>adoption of AI technologies introduces ne
 w security challenges that<br>organizations must address to protect sensit
 ive data\, maintain trust\, and<br>ensure regulatory compliance.<br>This t
 echnical talk explores the evolving cybersecurity landscape in the age<br>
 of AI\, highlighting key threats such as prompt injection\, model manipula
 tion\,<br>data poisoning\, adversarial attacks\, insecure AI integrations\
 , and privacy<br>risks associated with generative AI platforms. The sessio
 n will provide<br>practical insights into securing AI applications\, APIs\
 , cloud environments\,<br>and enterprise systems while aligning with indus
 try best practices and<br>emerging regulatory requirements.<br>Participant
 s will gain an understanding of AI threat modeling\, secure AI<br>developm
 ent practices\, AI red teaming\, LLM security assessment<br>methodologies\
 , and strategies for building resilient and trustworthy AI<br>systems. Rea
 l-world case studies and practical recommendations will be<br>discussed to
  help organizations securely embrace AI-driven transformation.</p>
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