How do we get more visibility into attacks across our environments, improve our response, and reduce response time? SANS Analyst, James Tarala, provides insight on the solution by automating functions that should be automated and connecting the dots between detection systems and response. Connecting these dots and applying intelligence provides responders rich context into the observed behaviors for taking action. Integrating these processes improves accuracy, while reducing time, manpower, and costs involved in detecting and managing events. This white paper explores how to achieve this.
In the age of information, staying on top of emerging threats requires IT teams to leverage existing tools in innovative ways, such as applying deep packet inspection and analysis from performance monitoring solutions for advanced security forensics.
Based on recent insight gathered from 322 network engineers, IT directors and CIOs around the world, 85 percent of enterprise network teams are now involved with security investigations, indicating a major shift in the role of those teams within enterprises. Large-scale and high-profile security breaches have become more common as company data establishes itself as a valuable commodity on the black market. As such, enterprises are now dedicating more IT resources than ever before to protect data integrity.
Security breaches can happen anywhere in an organization, and having the ability to analyze any form of data can give you the edge against fraud, theft, and infiltration by pinpointing abnormal behavior patterns. Understanding your security vulnerabilities requires rapid, deep analytics against business data, machine data, and unstructured human information.
Published By: LogRhythm
Published Date: Jun 19, 2018
Security and risk management leaders considering UEBA will find that the market has fragmented, with a few pure-play vendors and a wide set of traditional security products that embed core UEBA technologies and features to benefit from advanced analytics capabilities.
The FICO® Enterprise Security Score measures the likelihood that you will suffer a data breach in the coming 12 months. To deliver the FICO Enterprise Security Score, we access billions of external data points at internet scale and apply our analytics to give you an empirically derived score.
You can measure the cybersecurity risk of your organization, or any organization you want to work with, to see the risk you are inheriting from your supply chain. We provide the information behind your cybersecurity score so you can see where you need to take action, and you can measure the effect of improvements on your overall cybersecurity posture.
As we have said through this paper, it is no longer an either/or choice between security analytics and SIEM. Or even between insourcing and outsourcing security monitoring. You need to establish a team with complimentary capabilities, skills, and resources; then leverage each part for what it does best. It is frustrating to use a technology for something it’s not built to do, and just as frustrating to expect a service provider to do things beyond their capability — regardless of their claims during the sales cycle. So don’t do that — build your security monitoring program to give all parties the best chance of success.
The status quo approach of collecting more logs from more sources won't help in detecting and responding to advanced threats. Logs are inherently limited in the level security visibility that they provide. Consider a new way of looking at SIEM.
To develop the visibility, agility and speed to deal with advanced threats, security information and event management (SIEM) systems need to evolve into a central nervous system for large-scale security analytics.
Starting with a foundational set of data management and analytic capabilities enables organizations to effectively build and scale security management as the enterprise evolves to meet Big Data challenges.
Mid-size enterprises face the challenges of managing advanced threats plus staff and budget constraints. This on-demand webcast explains how RSA Security Analytics provides visibility, threat intelligence, and analytics – and how you can start small.
Is your IT organization taking the proper steps toward successful cloud adoption?
Legacy networking technology is hampering IT agility. Cloud providers have initiated an agility revolution but secure inter- and intra-cloud network connectivity are still very challenging. Easier alternatives are either expensive, worsen application performance and/or hamper network efficiency. Riverbed’s unique SD-WAN solution helps unlock agility across the complete enterprise network allowing for easier deployment and management of cloud-centric networks. This cloud adoption Use Case outlines challenges and solutions for cloud-centric enterprise architectures including:
· Unlocking cloud agility through simple workflows in the WAN such as single-click secure connectivity to cloud and branch networks
· The importance of bandwidth reduction and application acceleration to ensure cloud adoption
· Distinguishing between application and network problems through enhanced visibility
Traditional data processing infrastructures—especially those that support applications—weren’t designed for our mobile, streaming, and online world. However, some organizations today are building real-time data pipelines and using machine learning to improve active operations.
Learn how to make sense of every format of log data, from security to infrastructure and application monitoring, with IT Operational Analytics--enabling you to reduce operational risks and quickly adapt to changing business conditions.
Mobile is the new normal for users to connect and consume content, you need to consider apps, mobile integration,security, analytics, development tools, life-cycle management, various mobile stakeholders, and the overall enterprise mobile ecosystem.
Read this white paper from IBM to learn about applying predictive analytics to claims management, including the typical ROI achieved, how embedded analytics improves decision making, and technology components of a predictive analytics solution.
Tax fraud is already prevalent, and fraudsters are more sophisticated and automated than ever. To get ahead of the game in detecting fraud and protecting revenue, tax agencies need to leverage more advanced and predictive analytics. Legacy processes, systems, and attitudes need not stand in the way. To explore the challenges, opportunities, and value of tax fraud analytics, IIA spoke with Deborah Pianko, a Government Fraud Solutions Architect within the SAS Security Intelligence practice.
This white paper, sponsored by SAS, examines the interplay between the
challenges and opportunities afforded by the growing breadth of digital channels
offered by financial institutions. Mobile wallets, real-time peer-to-peer (P2P), and
digital account opening all require the right mix of security solutions, background
analytics, and personnel to balance positive customer experience with robust
fraud protection. JAVELIN independently produced this whitepaper and maintains
complete independence in its data collection, findings, and analysis.
Financial organizations are deploying artificial intelligence and machine learning in the fight against financial crimes. David Stewart, Director of Pre-Sales for the Global Security Intelligence Practice at SAS, offers tips to help separate fact from market hype when reviewing new data analytics tools. You’ll learn about:
• The new industry intrigue with artificial intelligence and machine learning.
• How these emerging solutions can benefit financial institutions.
• The SAS approach of “crawl, walk, run” when it comes to adopting new analytics tools.