小型金融机构采用混合 DDoS 防护措施来保护其网络
公司规模
11-200
地区
- America
国家
- United States
产品
- Arbor Edge Defense® (AED)
- Arbor Cloud®
技术栈
- DDoS Protection
- Cloud Solution
- Traffic Analysis
实施规模
- Enterprise-wide Deployment
技术
- 基础设施即服务 (IaaS) - 云计算
- 基础设施即服务 (IaaS) - 混合云
适用行业
- 金融与保险
适用功能
- 商业运营
用例
- 网络安全
服务
- 云规划/设计/实施服务
- 网络安全服务
关于客户
客户是一家提供短期金融解决方案的区域性金融机构。他们采用先进的技术来管理各种在线、移动和基于分支机构的消费者金融和贷款服务以及应用程序。该组织着手开展流量分析项目，旨在了解可能穿越其网络的恶意流量。他们最初的决定是聘请我们的竞争对手之一，该竞争对手专门提供通过服务提供商提供的始终在线的云解决方案。
挑战
该金融机构正在应对应用层和 TCP 洪水 DDoS 攻击，而其服务提供商的始终在线云解决方案无法有效识别和管理这些攻击。他们着手开展流量分析项目，以了解流经其网络的恶意流量。他们最初采用服务提供商提供的始终在线云解决方案。该解决方案足以识别和缓解大流量 DDoS 攻击，但它难以应对其他 DDoS 攻击媒介。云解决方案通常设计和配置为在流量峰值时触发缓解，这意味着它难以识别低速和慢速第 7 层应用程序攻击以及针对有状态设备中的 TCP 表的攻击。
解决方案
NETSCOUT 团队建议采用混合方法，在每个数据中心内部署 Arbor Edge Defense (AED)，以保护网络边缘和有状态设备免受低容量但有效的攻击，同时与 Arbor Cloud 协作以缓解容量攻击。这将覆盖复杂的多向量 DDoS 攻击。该解决方案旨在识别和缓解应用程序堆栈中每个级别的 DDoS 攻击。混合解决方案提供了识别和缓解应用程序堆栈中每个级别的 DDoS 攻击的能力。
运营影响
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
相关案例.
Case Study
Real-time In-vehicle Monitoring
The telematic solution provides this vital premium-adjusting information. The solution also helps detect and deter vehicle or trailer theft – as soon as a theft occurs, monitoring personnel can alert the appropriate authorities, providing an exact location.“With more and more insurance companies and major fleet operators interested in monitoring driver behaviour on the grounds of road safety, efficient logistics and costs, the market for this type of device and associated e-business services is growing rapidly within Italy and the rest of Europe,” says Franco.“The insurance companies are especially interested in the pay-per-use and pay-as-you-drive applications while other organisations employ the technology for road user charging.”“One million vehicles in Italy currently carry such devices and forecasts indicate that the European market will increase tenfold by 2014.However, for our technology to work effectively, we needed a highly reliable wireless data network to carry the information between the vehicles and monitoring stations.”
Case Study
Safety First with Folksam
The competitiveness of the car insurance market is driving UBI growth as a means for insurance companies to differentiate their customer propositions as well as improving operational efficiency. An insurance model - usage-based insurance ("UBI") - offers possibilities for insurers to do more efficient market segmentation and accurate risk assessment and pricing. Insurers require an IoT solution for the purpose of data collection and performance analysis
Case Study
Smooth Transition to Energy Savings
The building was equipped with four end-of-life Trane water cooled chillers, located in the basement. Johnson Controls installed four York water cooled centrifugal chillers with unit mounted variable speed drives and a total installed cooling capacity of 6,8 MW. Each chiller has a capacity of 1,6 MW (variable to 1.9MW depending upon condenser water temperatures). Johnson Controls needed to design the equipment in such way that it would fit the dimensional constraints of the existing plant area and plant access route but also the specific performance requirements of the client. Morgan Stanley required the chiller plant to match the building load profile, turn down to match the low load requirement when needed and provide an improvement in the Energy Efficiency Ratio across the entire operating range. Other requirements were a reduction in the chiller noise level to improve the working environment in the plant room and a wide operating envelope coupled with intelligent controls to allow possible variation in both flow rate and temperature. The latter was needed to leverage increased capacity from a reduced number of machines during the different installation phases and allow future enhancement to a variable primary flow system.
Case Study
Automated Pallet Labeling Solution for SPR Packaging
SPR Packaging, an American supplier of packaging solutions, was in search of an automated pallet labeling solution that could meet their immediate and future needs. They aimed to equip their lines with automatic printer applicators, but also required a solution that could interface with their accounting software. The challenge was to find a system that could read a 2D code on pallets at the stretch wrapper, track the pallet, and flag any pallets with unread barcodes for inspection. The pallets could be single or double stacked, and the system needed to be able to differentiate between the two. SPR Packaging sought a system integrator with extensive experience in advanced printing and tracking solutions to provide a complete traceability system.
Case Study
Transforming insurance pricing while improving driver safety
The Internet of Things (IoT) is revolutionizing the car insurance industry on a scale not seen since the introduction of the car itself. For decades, premiums have been calculated using proxy-based risk assessment models and historical data. Today, a growing number of innovative companies such as Quebec-based Industrielle Alliance are moving to usage-based insurance (UBI) models, driven by the advancement of telematics technologies and smart tracking devices.
Case Study
MasterCard Improves Customer Experience Through Self-Service Data Prep
Derek Madison, Leader of Business Financial Support at MasterCard, oversees the validation of transactions and cash between two systems, whether they’re MasterCard owned or not. He was charged with identifying new ways to increase efficiency and improve MasterCard processes. At the outset, the 13-person team had to manually reconcile system interfaces using reports that resided on the company’s mainframe. Their first order of business each day was to print 20-30 individual, multi-page reports. Using a ruler to keep their place within each report, they would then hand-key the relevant data, line by line, into Excel for validation. “We’re talking about a task that took 40-80 hours each week,” recalls Madison, “As a growing company with rapidly expanding product offerings, we had to find a better way to prepare this data for analysis.”
