{"id":58101,"date":"2025-07-01T08:19:32","date_gmt":"2025-07-01T15:19:32","guid":{"rendered":"https:\/\/www.kochava.com\/?p=58101"},"modified":"2025-07-02T17:24:50","modified_gmt":"2025-07-03T00:24:50","slug":"decloaking-ad-fraud-answers-to-your-top-questions","status":"publish","type":"post","link":"https:\/\/www.kochava.com\/ko\/blog\/decloaking-ad-fraud-answers-to-your-top-questions\/","title":{"rendered":"Decloaking Ad Fraud: Answers to Your Top Questions"},"content":{"rendered":"[vc_row type=”in_container” full_screen_row_position=”middle” column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” scene_position=”center” text_color=”dark” text_align=”left” row_border_radius=”none” row_border_radius_applies=”bg” overflow=”visible” overlay_strength=”0.3″ gradient_direction=”left_to_right” shape_divider_position=”bottom” bg_image_animation=”none”][vc_column column_padding=”no-extra-padding” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” column_element_direction_desktop=”default” column_element_spacing=”default” desktop_text_alignment=”default” tablet_text_alignment=”default” phone_text_alignment=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_backdrop_filter=”none” column_shadow=”none” column_border_radius=”none” column_link_target=”_self” column_position=”default” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/1″ tablet_width_inherit=”default” animation_type=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid”][vc_row_inner equal_height=”yes” content_placement=”middle” column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” text_align=”left” row_position=”default” row_position_tablet=”inherit” row_position_phone=”inherit” overflow=”visible” pointer_events=”all”][vc_column_inner column_padding=”no-extra-padding” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” column_element_direction_desktop=”default” column_element_spacing=”default” desktop_text_alignment=”default” tablet_text_alignment=”default” phone_text_alignment=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_backdrop_filter=”none” column_shadow=”none” column_border_radius=”none” column_link_target=”_self” overflow=”visible” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/2″ tablet_width_inherit=”default” animation_type=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid”][vc_column_text css=”” text_direction=”default”]\r\n

From webinar to action: expert insights to safeguard your ad dollars<\/h2>\r\nYour mobile game\u2019s UA dashboard lights up with exciting metrics. A new campaign is delivering app installs at an impressive $2.50 CPA\u2014half the cost of your established networks. The attributed users seem immediately engaged with your game, triggering in-app purchases within hours of downloading. You and your colleagues are thrilled. Some time later, you discover that 94% of these \u201cusers\u201d came from jailbroken devices, the purchases were scripted events that never cleared actual payment processors, and your shiny new traffic partner systematically deployed automated install farms to defraud dozens of advertisers. What looked like marketing gold was actually fool\u2019s pyrite\u2014and you were certainly not alone in falling for the deception.[\/vc_column_text][\/vc_column_inner][vc_column_inner column_padding=”padding-4-percent” column_padding_tablet=”no-extra-padding” column_padding_phone=”no-extra-padding” column_padding_position=”left” column_element_direction_desktop=”default” column_element_spacing=”default” desktop_text_alignment=”default” tablet_text_alignment=”default” phone_text_alignment=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_backdrop_filter=”none” column_shadow=”none” column_border_radius=”none” column_link_target=”_self” overflow=”visible” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/2″ tablet_width_inherit=”default” animation_type=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid” column_padding_type=”default” gradient_type=”default”][image_with_animation image_url=”58130″ image_size=”full” animation_type=”entrance” animation=”None” animation_movement_type=”transform_y” hover_animation=”none” alignment=”” border_radius=”none” box_shadow=”none” image_loading=”default” max_width=”100%” max_width_mobile=”default”][\/vc_column_inner][\/vc_row_inner][vc_row_inner column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” text_align=”left” row_position=”default” row_position_tablet=”inherit” row_position_phone=”inherit” overflow=”visible” pointer_events=”all”][vc_column_inner column_padding=”no-extra-padding” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” column_element_direction_desktop=”default” column_element_spacing=”default” desktop_text_alignment=”default” tablet_text_alignment=”default” phone_text_alignment=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_backdrop_filter=”none” column_shadow=”none” column_border_radius=”none” column_link_target=”_self” overflow=”visible” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/1″ tablet_width_inherit=”default” animation_type=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid”][vc_column_text css=”” text_direction=”default”]\r\n

The $100+ Billion Problem<\/h2>\r\nThe digital advertising ecosystem harbors a $100+ billion problem that most marketers would prefer not to think about. Left unchecked, mobile advertising fraud\u2014now the second-largest organized criminal enterprise on the planet\u2014quietly siphons upwards of 40% of advertising budgets. Unlike other forms of marketing waste, fraud actively disguises itself as legitimate performance, creating compelling dashboards that mask devastating losses.\r\n\r\nWhat makes mobile ad fraud particularly insidious is its sophistication. Gone are the days of crude bot farms and obvious click flooding. Today\u2019s fraudsters deploy intelligent algorithms that attune to device activity, simulate realistic user journeys, and exploit attribution windows with surgical precision. They understand your measurement infrastructure better than many of your marketing colleagues do, crafting schemes that satisfy every technical requirement.\r\n\r\nThe stakes extend beyond immediate budget impact. Plain and simple, ad fraud is serious criminal activity. On top of that, fraudulent traffic skews optimization algorithms, corrupts audience insights, and undermines strategic decision-making across marketing operations. When fraud masquerades as high-performing inventory, it bleeds budgets and may mislead teams into doubling down on fundamentally worthless traffic sources.[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_row_inner column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” text_align=”left” row_position=”default” row_position_tablet=”inherit” row_position_phone=”inherit” overflow=”visible” pointer_events=”all” css=”.vc_custom_1751383064775{margin-bottom: 0px !important;}”][vc_column_inner column_padding=”no-extra-padding” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” column_element_direction_desktop=”default” column_element_spacing=”default” desktop_text_alignment=”default” tablet_text_alignment=”default” phone_text_alignment=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_backdrop_filter=”none” column_shadow=”none” column_border_radius=”none” column_link_target=”_self” overflow=”visible” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/1″ tablet_width_inherit=”default” animation_type=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid”][vc_column_text css=”” text_direction=”default”]\r\n

Expert Intelligence: Key Insights from Kochava\u2019s Fraud Detection Webinar<\/h2>\r\nKochava recently hosted a technical deep-dive webinar<\/a> to cut through fraud\u2019s elaborate disguises, spotlighting detection methodologies refined through hundreds of investigations. Led by Grant Simmons<\/a>, VP of Kochava Foundry<\/a>, and Tyler Levasseur, Manager of Foundry Data Analytics, the session unpacked how statistical analysis can expose even the most cleverly crafted fraud schemes.\r\n\r\nThe duo walked through real-world detection cases, from basic click injection to advanced \u201csmart click flooding\u201d that selectively targets iOS devices using cellular IP addresses for more efficient attribution gaming. Their collective experience and success leverages a key reality: While individual fraudulent events may appear legitimate, fraudsters struggle to randomize every variable simultaneously<\/strong>. This inherent limitation creates statistical patterns that reveal themselves at scale\u2014a foundation of effective fraud detection.[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_row_inner equal_height=”yes” content_placement=”middle” column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” text_align=”left” row_position=”default” row_position_tablet=”inherit” row_position_phone=”inherit” overflow=”visible” pointer_events=”all”][vc_column_inner column_padding=”padding-3-percent” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” column_element_direction_desktop=”default” column_element_spacing=”default” desktop_text_alignment=”default” tablet_text_alignment=”default” phone_text_alignment=”default” background_color=”#fbfbfb” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_backdrop_filter=”none” column_shadow=”none” column_border_radius=”20px” column_link_target=”_self” overflow=”visible” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/3″ tablet_width_inherit=”default” animation_type=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”1px” column_border_color=”#e6e6e6″ column_border_style=”solid” column_padding_type=”default” gradient_type=”default”][nectar_single_testimonial testimonial_style=”small_modern” image=”53035″ color=”Accent-Color” quote=”Fraudsters have a hard time manufacturing everything that needs to get randomized.” name=”Grant Simmons” subtitle=”VP, Kochava Foundry”][\/vc_column_inner][vc_column_inner column_padding=”padding-2-percent” column_padding_tablet=”no-extra-padding” column_padding_phone=”no-extra-padding” column_padding_position=”left” column_element_direction_desktop=”default” column_element_spacing=”default” desktop_text_alignment=”default” tablet_text_alignment=”default” phone_text_alignment=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_backdrop_filter=”none” column_shadow=”none” column_border_radius=”none” column_link_target=”_self” overflow=”visible” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”2\/3″ tablet_width_inherit=”default” animation_type=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid” column_padding_type=”default” gradient_type=”default”][vc_column_text css=”” text_direction=”default”]For example, Levasseur demonstrated how falsified transparency shows up in data, including cases where thousands of different site IDs move in exact unison\u2014a clear indicator of manufactured traffic \u201crandomization\u201d rather than genuine inventory diversity. His explanation of time-to-install (TTI) anomalies showed how fraudsters attempt to avoid detection by spacing out install timing, creating unnatural distribution patterns that expose scripted behavior.\r\n\r\nThe session emphasized that effective fraud mitigation requires both detection and customization. As Simmons notes, \u201cWe want to build you a chainmail suit here, and we can build one custom for you.\u201d<\/strong> This involves configuring verification rules around specific geos, device types, and timing parameters tailored to each advertiser\u2019s platforms and traffic patterns.[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_row_inner column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” top_padding=”15″ text_align=”left” row_position=”default” row_position_tablet=”inherit” row_position_phone=”inherit” overflow=”visible” pointer_events=”all”][vc_column_inner column_padding=”no-extra-padding” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” column_element_direction_desktop=”default” column_element_spacing=”default” desktop_text_alignment=”default” tablet_text_alignment=”default” phone_text_alignment=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_backdrop_filter=”none” column_shadow=”none” column_border_radius=”none” column_link_target=”_self” overflow=”visible” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/1″ tablet_width_inherit=”default” animation_type=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid”][vc_column_text css=”” text_direction=”default”]\r\n

Your Pressing Questions Answered<\/h2>\r\nFollowing the webinar, the Foundry Team gathered questions from attendees seeking to apply these principles to specific challenges. Read on for detailed answers provided by Simmons to help marketers identify, investigate, and mitigate fraud across their campaigns.[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_row_inner column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” text_align=”center” row_position=”default” row_position_tablet=”inherit” row_position_phone=”inherit” overflow=”visible” pointer_events=”all”][vc_column_inner column_padding=”padding-3-percent” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” column_element_direction_desktop=”default” column_element_spacing=”default” desktop_text_alignment=”default” tablet_text_alignment=”default” phone_text_alignment=”default” background_color=”#00165c” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_backdrop_filter=”none” font_color=”#ffffff” column_shadow=”none” column_border_radius=”20px” column_link_target=”_self” overflow=”visible” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/1″ tablet_width_inherit=”default” animation_type=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid” column_padding_type=”default” gradient_type=”default”][vc_column_text css=”” text_direction=”default” max_width=”675″]\r\n

Suspect fraud in your campaigns? Request an Ad Fraud Audit<\/strong><\/a> to uncover any nefarious patterns.<\/p>\r\n[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_row_inner column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” top_padding=”15″ text_align=”left” row_position=”default” row_position_tablet=”inherit” row_position_phone=”inherit” overflow=”visible” pointer_events=”all”][vc_column_inner column_padding=”no-extra-padding” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” column_element_direction_desktop=”default” column_element_spacing=”default” desktop_text_alignment=”default” tablet_text_alignment=”default” phone_text_alignment=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_backdrop_filter=”none” column_shadow=”none” column_border_radius=”none” column_link_target=”_self” overflow=”visible” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/1″ tablet_width_inherit=”default” animation_type=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid”][vc_column_text css=”” text_direction=”default”]\r\n

Foundation & Assessment<\/h2>\r\n[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][toggles style=”minimal”][toggle color=”Default” heading_tag=”h3″ heading_tag_functionality=”default” title=”What range of fraud percentages from data sources is considered \u201cacceptable\u201d in digital advertising?”][vc_column_text css=”” text_direction=”default”]Without rigorous preventative measures, upwards of 40% of ad budgets may be lost<\/strong> to fraud. This estimate, drawn from industry analysis and Kochava\u2019s extensive fraud investigation experience, represents the potential impact when advertisers operate without capable detection systems.\r\n\r\nWhile advertisers are generally resigned to accepting moderate levels of fraud (single- to low double-digit percentages), the aspiration should always be to minimize this to the lowest feasible rate through vigilant detection and mitigation systems rather than writing off a set percentage as \u201cnormal.\u201d The goal is to create an environment where fraud becomes economically unviable for bad actors.[\/vc_column_text][\/toggle][toggle color=”Default” heading_tag=”h3″ heading_tag_functionality=”default” title=”What simple metrics can CMOs use to quickly estimate their ad fraud losses and actionable next steps?”][vc_column_text css=”” text_direction=”default”]CMOs should monitor click flooding indicators, install validation failure rates, percentage of jailbroken or rooted devices receiving attribution from specific publishers, and time-to-install (TTI) distributions. These metrics serve as early warning systems that don\u2019t require deep technical expertise to interpret.\r\n\r\nUnusually high concentrations of jailbroken devices (anything approaching double digits from a single source), disproportionate TTI clustering (installs occurring within seconds of clicks), and high authentication failure rates signal fraud risks. For perspective, Kochava\u2019s install authentication disqualifies about 1.8% of all install traffic, but some individual networks show install authentication failure rates as high as 40%\u2014a clear red flag warranting immediate investigation.\r\n\r\nEstablishing verification rules and regularly reviewing violation reports are recommended first steps for rapid detection and action.[\/vc_column_text][\/toggle][toggle color=”Default” heading_tag=”h3″ heading_tag_functionality=”default” title=”What CTR levels should be treated as suspicious?”][vc_column_text css=”” text_direction=”default”]Click-through-rate (CTR) values above 10% warrant investigation. In legitimate advertising environments, CTRs rarely exceed single digits consistently, as genuine user engagement follows predictable patterns based on creative quality, audience targeting, and placement context.\r\n\r\nCTRs above 100% represent a mathematical impossibility in legitimate advertising\u2014indicating either gross errors in measurement or deliberate manipulation wherein impressions are underreported and\/or clicks are fraudulently manufactured without legitimate ad views. Always investigate campaigns with abnormally high CTR for data integrity issues, as they often reveal broader fraud schemes affecting multiple metrics.[\/vc_column_text][\/toggle][\/toggles][vc_row_inner column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” top_padding=”15″ text_align=”left” row_position=”default” row_position_tablet=”inherit” row_position_phone=”inherit” overflow=”visible” pointer_events=”all”][vc_column_inner column_padding=”no-extra-padding” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” column_element_direction_desktop=”default” column_element_spacing=”default” desktop_text_alignment=”default” tablet_text_alignment=”default” phone_text_alignment=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_backdrop_filter=”none” column_shadow=”none” column_border_radius=”none” column_link_target=”_self” overflow=”visible” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/1″ tablet_width_inherit=”default” animation_type=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid”][vc_column_text css=”” text_direction=”default”]\r\n

Detection Fundamentals<\/h2>\r\n[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][toggles style=”minimal”][toggle color=”Default” heading_tag=”h3″ heading_tag_functionality=”default” title=”How can fraudulent conversions like app installs be reliably detected?”][vc_row_inner column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” text_align=”left” row_position=”default” row_position_tablet=”inherit” row_position_phone=”inherit” overflow=”visible” pointer_events=”all”][vc_column_inner column_padding=”no-extra-padding” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” column_element_direction_desktop=”default” column_element_spacing=”default” desktop_text_alignment=”default” tablet_text_alignment=”default” phone_text_alignment=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_backdrop_filter=”none” column_shadow=”none” column_border_radius=”none” column_link_target=”_self” overflow=”visible” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/1″ tablet_width_inherit=”default” animation_type=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid”][vc_column_text css=”” text_direction=”default”]Several techniques help expose fraudulent installs, ranging from technical verification to behavioral pattern analysis:\r\n