Serious Games for Cyber Security - The Human Factor

This document discusses Generali Group, an international insurance company, and its efforts to detect insurance fraud. It provides an overview of Generali Group, describing it as one of the leading insurers in the world with operations in over 60 countries. It then discusses the problem of insurance fraud and some common types. It outlines Generali's solution to fraud detection, which involves using a graph database and applying techniques like rule-based analysis, social network analysis, and machine learning to processed insurance claims data.

Real-Time Fraud Detection in Payment Transactions

Christian Gügi

This document discusses building a real-time fraud detection system using big data technologies. It outlines the cyber threat landscape, what anomalies and fraud detection are, and proposes an architecture with a data layer to integrate various sources and an analytics layer using stream processing, rules engines, and machine learning to score transactions in real-time and detect fraud. The system aims to scalably and reliably detect threats for increased security.

New fraud protection solutions

The document discusses new requirements for fraud prevention across multiple channels as attacks are expanding due to increased mobile and online banking usage. It summarizes a presentation about an omni-channel fraud prevention solution from Guardian Analytics that provides a 360 degree view of customers and activities across channels through integrated data and advanced behavioral analytics. The solution aims to improve fraud detection and reduce customer friction by consolidating risk scoring and providing real-time visibility of customer behaviors and risks across all channels in a single system.

Guardian analytics vs. actimize 2016

This document summarizes the capabilities of Guardian Analytics' machine learning and behavioral analytics solutions for financial fraud detection compared to Actimize. It states that Guardian Analytics offers omni-channel visibility, behavioral analytics that require no rules, and machine learning that continuously updates models without human intervention. It also provides rapid deployment, flexible hosting options, visual analytics, and integrates risk data from multiple sources. In contrast, it describes Actimize as having poor user interfaces, requiring extensive rule maintenance, long deployments, and high costs.

Big Data Analytics to Enhance Security

Data Science Thailand

Op tijd klaar voor de naderende gdpr avg privacywet - Janus de Visser

Netprofiler

Same day ach bec fraud detection prevention webinar 3 1-18

The document discusses how to detect and prevent same day ACH BEC fraud. It provides an agenda that includes an introduction, why this matters, dissecting the fraud scheme, and why the company is unique in analyzing this type of fraud. It then describes the fraud scheme, including how hackers target executive emails, validate the emails, and fingerprint the victim's digital profile. It outlines the process from the BEC scam to fraudulent same day ACH batches. It discusses key risk factors the company looks for and how it uses machine learning and behavioral analytics to automatically establish baselines and risk score ACH batches.

The document discusses user and entity behavior analytics (UEBA), which analyzes user and system behavior to detect threats and anomalies. UEBA goes beyond traditional security information and event management (SIEM) tools by using machine learning instead of rule-based detection. UEBA vendors study behaviors at the user, application, device and server levels to create profiles and detect deviations that could indicate insider threats, data exfiltration or compromised accounts. The UEBA market is growing as organizations increasingly need to detect complex, unknown threats like insider threats. UEBA has limitations but can be a valuable part of a security analytics platform when integrated with other tools.

Graph Intelligence: The Essentials for Cybersecurity

This document discusses how graph intelligence and graph analytics can help with cybersecurity investigations. It argues that defenders currently think in lists while attackers think in graphs, putting defenders at a disadvantage. Using graph databases and visualization tools like Linkurious Enterprise allows security teams to analyze data across systems, identify complex attack patterns, and speed up investigations. The document provides examples of how graph analysis has helped organizations reduce fraud and detect phishing attacks. It presents Linkurious as a solution to help organizations shift from siloed data approaches to using graphs to gain critical context and a more comprehensive view of security risks and attacks.

Leveraging Threat Intelligence to Guide Your Hunts

Sqrrl 2.0 Launch Webinar

Pgatss slide deck june 7, 2018

Greg Wartes, MCP

This document discusses cybersecurity threats and strategies for protection. It begins with definitions of internal and external environments, then lists common threat vectors like email links, wireless access, and human error. The document advocates using a combination of security technologies like machine learning, sandboxing, encryption, and more. Examples are given of quick attacks on an exposed "cloud" and the need for around-the-clock protection of data. The conclusion emphasizes performing risk assessments and having a plan to address potential vulnerabilities across the network.

How Walmart is Combating Fraud and Saving Consumers Millions

Elasticsearch

Real-time fraud detection in credit card transactions

Mariusz Rafało

This document discusses approaches for real-time fraud detection in credit card transactions. It compares batch processing to stream processing, noting that stream processing allows for shorter reaction times but requires more complex architectures. The document then outlines an example architecture with a data warehouse and scoring engine to analyze transaction data. It also discusses challenges in analyzing unbalanced fraud data and techniques like SMOTE for oversampling minority classes. Finally, the document evaluates supervised and unsupervised models on a credit card transaction dataset, finding accuracies around 90% for fraud detection.

User and Entity Behavior Analytics using the Sqrrl Behavior Graph

UEBA leverages advanced statistical techniques and machine learning to surface subtle behaviors that are indicative of attacker presence. In this presentation, Sqrrl's Director of Data Science, Chris McCubbin, and Sqrrl's Director of Products, Joe Travaglini, provide an overview of how machine learning and UEBA can be used to detect cyber threats using Sqrrl's Behavior Graph. Watch the presentation with audio here: http://info.sqrrl.com/april-2016-ueba-webinar-on-demand

The Case for a Turnkey Approach to Fraud Operations

The document discusses the benefits of a turnkey approach to fraud operations managed by Guardian Analytics. It outlines their managed services model which includes leveraging people, infrastructure, processes, and technology. Case studies demonstrate how their services have helped clients reduce fraudulent transactions by 90%, lower callbacks by 80%, and realize quicker time to value. The presentation emphasizes the importance of infrastructure, advanced technology, holistic processes, and knowledgeable people in delivering an efficient and effective fraud management program.

GraphTour 2020 - Allianz: Empower your business with Graph Analytics

This document provides an agenda for a Graph Analytics presentation by Allianz. It will discuss how Allianz is using graph analytics to empower customer centricity and fraud detection. Specifically, it will cover how Allianz is creating golden customer profiles using graph analytics to integrate customer data from multiple sources and domains. This allows them to provide personalized customer care and recommendations. It will also discuss how graph analytics helps Allianz detect fraud rings and alerts by analyzing relationships between parties and objects involved in insurance claims. The presentation will provide examples of concrete outcomes from these applications of graph analytics.

Operationalizing Big Data Security Analytics - IANS Forum Toronto Keynote

Interset

Modernizing Your SOC: A CISO-led Training

North Texas Chapter of the ISSA

Today's threats demand a more active role in detecting and isolating sophisticated attacks. This must-see presentation provides practical guidance on modernizing your SOC and building out an effective threat hunting program. Ed Amoroso and David Bianco discuss best practices for developing and staffing a modern SOC, including the essential shifts in how to think about threat detection. Watch the presentation with audio here: http://info.sqrrl.com/webinar-modernizing-your-security-operations

NTXISSACSC4 - Cyber Insurance – Did You Know?

Cyber Insurance – Did You Know? We present a brief discussion of risk and the ways that risk can be handled by an organization, one of which mechanisms is the transfer of risk via insurance. We describe key terms and concepts related to business insurance generally and cyber insurance specifically. These concepts will include brief descriptions of duties to indemnify, duties to defend, limits, sublimits, exclusions, and retentions, as well as different types of insurance, including CGL policies, Crime policies, E&O, D&O, PGL, and cyber policies. We present an introduction to the domain of cyber insurance, discussing how cyber events may or may not be covered by traditional insurance products as well as by cyber insurance products. We will talk about the role of “standardized” contracts supplied by the ISO (Insurance Services Office), how these are changing in the cyber age, and the need for customized contracts. We will also present a general discussion of the cost of cyber insurance, the market penetration of cyber insurance in the US, and the cost of cyber events, citing data from public sources as well as reports from NetDiligence® Heather Goodnight-Hoffmann Over 20 years as Global Sales and Business Development Consultant Cofounder and President, Risk Centric Security, Inc. Ponemon Institute RIM Council (Responsible Information Council) Business Development Manager at Navilogic, Inc. Cofounder and Partner, Cyber Breach Response Partners, LLC Co-author & co-analyst, NetDiligence® 2016 Cyber Claims Study Patrick Florer 37 years in Information Technology 17 year parallel career in evidence-based medicine Cofounder and CTO, Risk Centric Security, Inc. Member, Ponemon Institute RIM council Distinguished Fellow, Ponemon Institute. Cofounder and Partner, Cyber Breach Response Partners, LLC. Co-author & co-analyst, NetDiligence® 2016 Cyber Claims Study

iScan_Amanda

Amanda Wilber

This document provides contact information for Unistar-Sparco Computers and discusses a Data Discovery report and Risk Intelligence tool. The Data Discovery report identifies where sensitive data like credit card numbers and bank accounts are stored on a network and who has access to it. Risk Intelligence calculates a "security number", representing a company's liability in dollars, based on unprotected data in the network, vulnerabilities, and unauthorized access to data. It helps companies understand their security risks.

Sqrrl and IBM: Threat Hunting for QRadar Users

This document discusses threat hunting using IBM QRadar and Sqrrl analytics. It introduces threat hunting, the threat hunting process, and the Sqrrl behavior graph for visualizing and exploring linked security data. Use cases for threat hunting with Sqrrl analytics on the QRadar platform are presented, along with a reference architecture showing how Sqrrl integrates with QRadar. A demonstration of the Sqrrl threat hunting platform concludes the document.

BSides Delhi 2018: Securing Supply Chain- A Risk Based Assessment Framework

BSides Delhi

Presenter: Prithvinder Singh & Prashanth Sulegaon Abstract: What is supply chain security? Supply Chain is a system of organizations, people, process, information, technology and resources involved in moving a product or service from a supplier to the intended customer. An unsecured supply chain can introduce great risk to any organization and if vendors, solutions or hardware aren’t properly vetted, it can lead to huge data loss. Why is it required? An unsecured supply chain can introduce great risk to an organization. If vendor aren’t properly vetted, or if we purchase software that does not meet our security standards, we can lose data. These days several companies have had data breaches that allowed hundreds of millions of customer records to be compromised. On average, it takes 229 days after a breach for it to be detected. Often, these breaches were caused by a vulnerability in third-party software or services being exploited, costing companies tens of millions of dollars and damaging customers’ confidence. In this Session: Everyone knows, 3rd party softwares bring lot of risk to an organization. However does traditional vetting of supplier solutions work? Will it really reduce the risk? can we perform effective assessments? Is it scalable? Can we do continuous monitoring? In this session we will talk about what are the risks currently associated with the 3rd Party Softwares and how to surface them for effective risk reduction. This session will focus on securing supply chain using risk based 3rd party framework which encompasses integration of multiple security checkpoints at various stages of solution life cycle We will talk about: * Supply Chain Universe * Current challenges in Supply Chain Security * Secure life-cycle of 3rd party software from on-boarding till termination. * Supplier Risk Profiling * Point in time vs Continuous Assurance

MITRE ATT&CKcon 2.0: ATT&CK Updates - ICS; Otis Alexander, MITRE

MITRE - ATT&CKcon

This document discusses updates to the ATT&CK framework for industrial control systems (ICS). It notes that ICS ATT&CK was created because ICS environments have unique adversary goals, technologies, and defenses compared to enterprise environments. The document outlines current and future use cases for ICS ATT&CK, challenges in its development, newly added tactics, and plans for its upcoming release in December 2019.

Threat Hunting Platforms (Collaboration with SANS Institute)

Traditional security measures like firewalls, IDS, endpoint protection, and SIEMs are only part of the network security puzzle. Threat hunting is a proactive approach to uncovering threats that lie hidden in your network or system, that can evade more traditional security tools. Go in-depth with Sqrrl and SANS Institute to learn how hunting platforms work. Watch the recording with audio here: http://info.sqrrl.com/sans-sqrrl-threat-hunting-webcast

Threat Hunting vs. UEBA: Similarities, Differences, and How They Work Together

Embracing Threat Intelligence and Finding ROI in Your Decision

Cylance

Threat intelligence has long existed but is now recognized as a distinct discipline. Tradecraft and technology in threat intelligence are rapidly maturing, along with industry expectations. Choosing how to invest in threat intelligence programs should be driven by business risk, though any organization can be targeted. Providing context increases the value of threat intelligence, and the strongest programs understand the return on investment of sharing intelligence externally.

Getting the best out of management consultants

Gordon Perchthold

Kari's Law Update & Making MLTS PBX E911 Work Presentation

Mark Fletcher, ENP

What's hot

UserEntityandBehaviorAnalyticsFriedman

Aaron Friedman

Graph Intelligence: The Essentials for Cybersecurity

Leveraging Threat Intelligence to Guide Your Hunts

Sqrrl 2.0 Launch Webinar

Pgatss slide deck june 7, 2018

Greg Wartes, MCP

How Walmart is Combating Fraud and Saving Consumers Millions

Elasticsearch

Real-time fraud detection in credit card transactions

Mariusz Rafało

User and Entity Behavior Analytics using the Sqrrl Behavior Graph

The Case for a Turnkey Approach to Fraud Operations

GraphTour 2020 - Allianz: Empower your business with Graph Analytics

Operationalizing Big Data Security Analytics - IANS Forum Toronto Keynote

Interset

Modernizing Your SOC: A CISO-led Training

North Texas Chapter of the ISSA

NTXISSACSC4 - Cyber Insurance – Did You Know?

iScan_Amanda

Amanda Wilber

Sqrrl and IBM: Threat Hunting for QRadar Users

BSides Delhi 2018: Securing Supply Chain- A Risk Based Assessment Framework

BSides Delhi

MITRE ATT&CKcon 2.0: ATT&CK Updates - ICS; Otis Alexander, MITRE

MITRE - ATT&CKcon

Threat Hunting Platforms (Collaboration with SANS Institute)

Threat Hunting vs. UEBA: Similarities, Differences, and How They Work Together