BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/Chicago BEGIN:DAYLIGHT DTSTART:20260308T030000 TZOFFSETFROM:-0600 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:CDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20261101T010000 TZOFFSETFROM:-0500 TZOFFSETTO:-0600 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:CST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260424T163939Z UID:E1B7693C-FF1C-4D92-A095-42FDD05048FA DTSTART;TZID=America/Chicago:20260424T120000 DTEND;TZID=America/Chicago:20260424T130000 DESCRIPTION:The growth of information and communication technology is const antly revolutionizing various domains\, e.g.\, energy & utility systems\, healthcare\, the Internet of Things\, etc. This\ninception of widespread c yber technology enables reliability and first operability of the system\,\ nyet simultaneously imposes a risk of significant impact due to disruption of safe and secure operation. The attack surface is expanding\, creating a cyber exposure gap\, which indicates a higher\nthreat landscape and incr eased risk of compromise. This research is motivated by this increased\nth reat exposure\, seeking an efficient modeling paradigm in order to initiat e threat-informed defense. We aim to analyze multistage\, multi-host attac ks with diverse behavioral artifacts. First\,\nwe describe the different l evels of indicators and their effectiveness to understand the adversary\na ctivity. Next\, we integrate static network information with dynamic attac k strategy by mapping\nattack graphs into the attacker’s techniques and tactics. This contextual integration provides\ninsights into the attacker ’s stealthy behavior. Following the enumeration of complexity and effort \nfor attack progression\, we will investigate and explore recent and more updated attacker behavior\nthrough threat report analysis.\n\nVirtual: ht tps://events.vtools.ieee.org/m/556253 LOCATION:Virtual: https://events.vtools.ieee.org/m/556253 ORGANIZER:shuvalaxmi.dass@louisiana.edu SEQUENCE:10 SUMMARY:Cyber Threat Analysis based on Characterizing Adversarial Behavior URL;VALUE=URI:https://events.vtools.ieee.org/m/556253 X-ALT-DESC:Description: <br /><div class="elementToProof">The growth of inf ormation and communication technology is constantly revolutionizing variou s domains\, e.g.\, energy &amp\; utility systems\, healthcare\, the Intern et of Things\, etc. This</div>\n<div class="elementToProof">inception of w idespread cyber technology enables reliability and first operability of th e system\,</div>\n<div class="elementToProof">yet simultaneously imposes a risk of significant impact due to disruption of safe and secure operation . The attack surface is expanding\, creating a cyber exposure gap\, which indicates a higher</div>\n<div class="elementToProof">threat landscape and increased risk of compromise. This research is motivated by this increase d</div>\n<div class="elementToProof">threat exposure\, seeking an efficien t modeling paradigm in order to initiate threat-informed defense. We aim t o analyze multistage\, multi-host attacks with diverse behavioral artifact s. First\,</div>\n<div class="elementToProof">we describe the different le vels of indicators and their effectiveness to understand the adversary</di v>\n<div class="elementToProof">activity. Next\, we integrate static netwo rk information with dynamic attack strategy by mapping</div>\n<div class=" elementToProof">attack graphs into the attacker&rsquo\;s techniques and ta ctics. This contextual integration provides</div>\n<div class="elementToPr oof">insights into the attacker&rsquo\;s stealthy behavior. Following the enumeration of complexity and effort</div>\n<div class="elementToProof">fo r attack progression\, we will investigate and explore recent and more upd ated attacker behavior</div>\n<div class="elementToProof">through threat r eport analysis.</div> END:VEVENT END:VCALENDAR