Streamline your endpoint security stack and your team's workload with predictive, AI based, pre-execution malware protection plus prevention based EDR. CylancePROTECT combined with CylanceOPTICS = real-time, predictive threat prevention.
Artificial intelligence and machine learning approaches provide radically new and improved endpoint protection. But not all companies' claims of using machine learning add up to a threat prevention strategy. Know the difference."
The cyberattacks of 2017 proved more numerous, sophisticated, and ruthless than in years past. Threat actors, armed with knowledge stolen from the CIA and tools lifted from the NSA, demonstrated an elevated level of proficiency. WannaCry and NotPetya, two prominent threats from last year, successfully exploited these stolen assets in their assault on systems worldwide. As 2017 progressed, new opportunities developed in ransomware-as-a-service (RaaS), opening the gates of malware-for-profit to everyone. Advancements in fileless attacks provided new ways for threats to hide from once reliable detection methods. Malware features such as polymorphism continued to play a powerful role in evading traditional defenses. The victims of cybercrime ranged from private businesses to the fundamental practices of democracy. France and the United States saw significant data breaches during their recent presidential elections. Several high-profile companies lost their customers’ personally identifiable information to cyberattacks, blemishing their brands and costing them untold millions in recovery operations. This report contains an overview of the threat trends and malware families Cylance's customers faced in 2017. This information is shared with the goal of assisting security practitioners, researchers, and individuals in our collective battle against emerging and evolving cyberthreats.
Artificial intelligence (AI) seems to be on everyone’s mind. It powers natural language recognition within voice-powered assistants like Siri and Alexa, beats world-class Go players, and enables hyper-targeted e-commerce and content recommendations across the web, as we see with Amazon and Netflix. But recently, AI has begun actively expanding its footprint within the enterprise. Executives are trying to more fully comprehend what AI is and how they can use its insights into their data to better capitalize on business opportunities. This additional information can enable engaging with customers more productively and efficiently, forming an edge against the competition. Read more in our AI survey summary.
Cylance commissioned AV-TEST to perform an advanced threat prevention test of enterprise endpoint protection software. The testing methodology was jointly developed to provide additive testing to the commodity antivirus protection tests currently produced by AV-TEST. CylancePROTECT® was tested against five competitor endpoint products from Kaspersky, McAfee, Sophos, Symantec, and Trend Micro. The tests were performed in December 2016 and January 2017. This report contains the results of four test cases. The primary goal was to show the detection and prevention capabilities of new and unknown malicious executables. Read more in the AV-TEST report.
During NSS Labs’ 2018 Advanced Endpoint Protection (AEP) Group Test, CylancePROTECT® and CylanceOPTICS™ v2.0.1450 failed to initiate part of the CylanceOPTICS engine, which primarily impacted the exploit and blended threats test categories. This affected the Cylance® position on the Security Value Map (SVM)™. After working closely with NSS, Cylance rolled out a new version of its software (v2.2.1011) for CylanceOPTICS. Cylance submitted this updated product for follow-on testing using the AEP Test Methodology v2.0, the same methodology used in the AEP Group Test. The product improved its Block Rate by 6.9% and its Additional Detection Rate by 0.2%. Learn more about the results in the NSS Labs testing report.
SE Labs tested CylancePROTECT® in an offline environment against major threats that subsequently appeared in the wild. The test explores the product’s ability to prevent new threats from attacking endpoint systems successfully. CylancePROTECT contains technology designed to identify and block malware using what it claims to be an “artificial intelligence” (AI) model. This model can be updated over time. However, in this test we used the model created in May 2015 and did not permit further updates so that the software was unable to receive new models or edit the existing one. The test exposed systems protected by this older version of CylancePROTECT to very impactful threats discovered and reported widely after May 2015. In this way, the test shows to what extent the product was able to predict how future threats would appear. This “Predictive Advantage” (PA), the advantage that users of the product have against future adversaries, is presented in this report.
When selecting a new cybersecurity vendor, Cylance® recommends that you review your options carefully. Here are 4 things to consider before making a selection: Effectiveness, Simplicity, Performance, Vendor Viability. See the infographic for more details.
With cybercriminals threatening nations globally, cybersecurity is taking a front seat in many regions. Most notably, the European Union (EU) has adopted regulations to combat the threats. Against the backdrop of increasingly sophisticated cyberattacks, the EU has set forth rules and procedures for enhanced cybersecurity, along with penalties for noncompliance, in the form of the General Data Protection Regulation (GDPR). This new body of mandated policies and procedures aims to protect EU member personal information collected and/or stored by organizations. Read more in the GDPR business brief.
The information security world is rich with information. From reviewing logs to analyzing malware, information is everywhere and in vast quantities, more than the workforce can cover. Artificial intelligence (AI) is a field of study that is adept at applying intelligence to vast amounts of data and deriving meaningful results. In this book, we will cover machine learning techniques in practical situations to improve your ability to thrive in a data driven world. With clustering, we will explore grouping items and identifying anomalies. With classification, we’ll cover how to train a model to distinguish between classes of inputs. In probability, we’ll answer the question “What are the odds?” and make use of the results. With deep learning, we’ll dive into the powerful biology inspired realms of AI that power some of the most effective methods in machine learning today. Learn more about AI in this eBook.
How did you choose your anti-malware solution? Did you put it through the same rigorous process as your other security solutions? Or, did you simply renew your current product licensing? Perhaps you went with something you had used at a previous job. Maybe you even went so far as to read a few product reviews and third-party test results or evaluations. But, did you test the anti-malware solution yourself? In this book, we explain how artificial intelligence (AI) can help your enterprise combat malware threats in a more preventative, proactive, and radically better way than legacy anti-malware products. We explain why you shouldn't just believe a vendor's marketing. Instead, you should test different solutions for yourself, just as you would with any other major security investment. Read more in this eBook.
VolitionRx Limited is a multi-national company which develops new ways to detect cancer. Their ideal product needed to be reliable, efficient, and easily manageable for their modestly-sized IT department. Additionally, the solution had to be readily deployable to their operations in four separate countries. According to Daniel Halter, Group IT Manager at Volition, traditional antivirus vendors were “offering the same old solution only slightly jazzier. The model they were offering, although new, was and is the same thing that has been around for a while.” Daniel also stated that Volition had little time to determine which vendors are “selling the truth and which ones are selling the dreams.” Seeking an ideal match, Daniel reached out to Khipu Networks for their security recommendation. Khipu Networks suggested CylancePROTECT®, Cylance’s artificial intelligence endpoint security product. Read the full case study to learn about the results Cylance was able to deliver.
Matthew Coy, Safelite’s Vice President of Information Technology, is responsible for overseeing all aspects of the company’s IT infrastructure, including selecting, administering, and supporting technology products. The company handles personally identifiable information, including credit card information and insurance data collected from several sources, and must comply with insurance industry regulations and the Payment Card Industry Data Security Standard. Safelite is the target of constant external attacks. The organization experienced ongoing security issues stemming from infected software, drivebys and other malicious downloads. According to Matthew, “A lot of malware and email viruses were making it through the environment, all bypassing our email security and AV.” Not only were the security controls ineffective, the previous AV platform required nearly 150 hours per week to manage. Matthew knew Safelite needed to make a change, and fast. Having worked with Cylance® at two previous companies, he was confident CylancePROTECT® could significantly improve Safelite’s endpoint security. Read the full case study to learn about the results Cylance was able to deliver.
Phoenix Children’s CISO, Daniel Shuler, and its IT security team are responsible for protecting 5,000 endpoints in the hospital and across more than 20 clinics in the region. Endpoints include physician and staff laptops and desktops, nursing stations, servers, Windows-based clinical devices, credit card payment processors, and point-of-sale terminals. These endpoints are used to store and/or process personal health information (PHI), and payment and credit card information. They must comply with HIPAA for PHI and voluntarily comply with the Payment Card Industry Data Security Standard (PCI-DSS) for credit card data. The IT security team’s existing industry-leading AV solution claimed to provide visibility into malicious activity aimed at the endpoints. It continuously reported all endpoints were safe, sound, and secure. This caused Daniel to be suspicious. He knew from experience that such low levels of endpoint malicious activity was highly unlikely. Read the full case study to learn about the results Cylance was able to deliver.
DatacenterDynamics is a brand of DCD Group, a global B2B media and publishing company that develops products to help senior professionals in the world's most ICT dependent organizations make risk-based infrastructure and capacity decisions.
Our portfolio of live events, online and print publishing, business intelligence and professional development brands are centred on the complexities of technology convergence. Operating in 42 different countries, we have developed a unique global knowledge and networking platform, which is trusted by over 30,000 ICT, engineering and technology professionals.
Data Centre Dynamics Ltd.
102-108 Clifton Street
London EC2A 4HW