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Adobe: Adobe Reduces Fake Account Risk and Improves User Experience with Arkose Labs
Arkose Labs’ Defense-in-Depth Detection
While new attack signatures arise everyday, they all have one thing in common — they’re motivated by profit. By analyzing attacks for telltale signs of fraudulent intent, companies are empowered to undermine attacks that are caught in the web of early and accurate detection. With a defense-in-depth approach that turns intent data into actionable decisions, fraud & security teams can fight proactively against fraud and shift from mitigation to long-term deterrence.
Arkose Labs believes digital businesses need to be armed with a combination of real-time risk decisioning, machine learning & human analysis to uncover high-risk activity in real-time, while optimizing rapidly with attack patterns.
The right defence-in-depth solution provides long term firepower for fraud and security teams.
Resilience to Spoofing
Detects sophisticated bots & spoofing earlier without disrupting good customer experience
Provides actionable risk insights to allow companies to make better, faster response decisions
Validates the accuracy of risk classifications, becoming smarter with each attack
Relieves internal resources from having to constantly manage rules engines and fraud tools
Real-time Risk Assessments Powered by Machine Learning
Arkose Detect empowers security and fraud teams to root out large-scale persistent attacks with real-time traffic risk classifications powered by multi-faceted machine learning and 24/7 analysis from our Security Operations Center. The detection engine uses a combination of real time aggregation, IP and device intelligence, traffic shaping, and behavioral analysis to identify good vs. malicious users and ensure attackers don’t go unnoticed.
Unlike black box solutions, our ‘clear box’ approach focuses on delivering actionable insights with clear explanations for risk classifications and a clear path to remediation. This goes beyond solutions that provide probabilistic risk scores, which often require a great deal of resources to integrate, fine-tune and define downstream authentication workflows. Our unique risk classification model uses insights from across our global network of telltales to distinguish between good and bad traffic with maximum accuracy, allowing companies to keep the occurrence of false positives and negatives to a minimum.
Each transaction is collected and compared in real time to a globally shared list of telltales and device IDs.
A risk score is determined based on historical insights from malicious and unusual patterns
Arkose Detect uncovers and aggregates the latest anomalies to provide a future-proof solution
Arkose Detect: Key Features
Arkose Detect carries out deep analysis of behavior and device heuristics to uncover subtle signs of fraud and allow companies to develop a response best-suited for their business and fraud-fighting strategy. This combination of real-time assessment works behind the scenes with shared intelligence from previous attacks to ensure accurate detection across a wide range of growing threats. Machine learning models carry out advanced anomaly detection to uncover subtle signs of malicious behavior.
Arkose Labs detects high-risk activity using network data and analysis adapted to a business’ specific ecosystem. Our forecasting method is based on historical trends and powered by machine learning to help us achieve the greatest accuracy in detecting fraud.
Device ID & Intelligence
Our positive-security learning system identifies digital fingerprints and compares traffic with known attack IDs. By creating a list of good fingerprint patterns and IDs, traffic is associated in real-time with each pattern & ID to predict whether an attack is at play.
A detection tool that provides network, geolocation, and reputation information associated with any IP address. The metadata is then used to further evaluate the origin of the traffic and feed the risk score.
Attackers often change IP and fingerprints to evade detection. Our platform analyzes behavioral patterns of global device data and uses self-learning models to identify outlier signatures of volumetric attacks, as well as low and slow attacks.
Customer Data Exchange
Our flexible APIs can ingest data from proprietary or third-party risk engines to improve risk assessment accuracy.
AI-Powered Platform Intelligence
Arkose Labs empowers companies with an enriched set of global rules we call telltales which accurately detects ever-evolving attacks. Our decision engine uses globally shared intelligence that is rapidly calibrated with historical and network data for accurate decisioning about risky traffic.
Arkose Global Network
Each year, we detect & stop nearly 3B attacks and share anonymized intel of attacks discovered with our global network of customers.
Arkose Detect comes with 150 rules of known fraud patterns and are customized to each business by SOC analysts to maximize fraud detection.
User session data can be uploaded to the Arkose platform to learn from users identified as bad actors downstream.
With access to rich first-party data across our global network, our mature ML platform adapts fast to stay one step ahead of attackers.
24/7 Security Operations Center
Arkose Labs customers receive added value through proactive traffic monitoring and tuning by security experts and data scientists in our global SOC.
Transparent Risk Insights
Understanding increasingly sophisticated attacks depends on more than risk scores from a blackbox approach. Arkose Labs provides transparent access to its insights through two-way data exchange and dashboards for more informed decisions.
Our advanced ML models aggregate all anomalous signals from a session into a risk score to streamline the complexity of detection.
We share 70+ session attributes to help you better understand our risk classification and augment your risk models.
Customer Data Exchange
Open API platform interoperates with other third party risk classification, common attack patterns, and identity solutions to enhance decisioning with insights unique to your business.
Customer dashboard provides end-to-end visibility into risk classification, attack patterns, and session details on each workflow.
The Arkose Advantage
Long-Term Fraud Detection & Actionable Insight
Transparent detection gives businesses superior insight data to enhance risk models. Our detection capabilities allow for a stronger security posture and offer flexibility in response technique.
- Early detection of fraudulent intent
- Secondary screening for suspicious traffic
- Secondary screening for suspicious traffic
- Resilience to emerging attacks
Deep Insights for Trust & Transparency
We believe teams need to be powered with real-time insights and data sharing to make sense of and strengthen decisions, rather than blindly following a machine-given score
- Use Arkose-collected data in your models
- Ingest in real-time for flexible attack response
- Anonymized global attack pattern intelligence
- Increase confidence with truth data feedback loop
Instant Time-to-Value with Simple Deployment
Arkose Labs is the fastest enterprise-ready risk detection available on the market, with businesses seeing actionable intelligence in days, not months.
- Support for Web, iOS, and Android
- Integrated on any user action
- Results within days
Unparalleled Commitment to Uncovering Attackers
While other risk solutions take a lot of internal resources to implement, tune, and monitor, Arkose Labs does that for you with an unparalleled commitment staying ahead of attackers.
- Maximum protection, effortless management
- Supported by 24/7 SOC & Managed Services
- Accurate detection that scales with you
- A true partner in delivering actionable insights
We needed a more robust solution; we weren’t getting any insights into the data with our old solution. Arkose Labs provided us with custom data and insights that we can share across teams internally
Chief Information Security Officer
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