Learn how ransomware is evolving - and which industries are the most susceptible to attacks.
Ransomware is a legitimate threat, with estimates from the U.S. Justice Department showing that over 4,000 of these attacks have occurred every day since the beginning of the 2016. As ransomware infections evolve, attacks have become more common across all industries. In this BitSight Insights Report, researchers analyzed the growing trend of ransomware across nearly 20,000 companies to identify common strains of this malware, and identify which industries are targeted most.
Read this BitSight Insights report to learn:
- How the rate of ransomware infections has grown over the past year
- Which industries have exhibited the most ransomware infections
- How businesses can directly mitigate the threat of ransomware infections, as well as infections originating from third party vendors and suppliers
Download the latest BitSight Insight report to find out how ransomware affects each industry, and what organizations can do to prevent it.
Continuous monitoring (CM) begets a process of continuous improvement that works to reduce attack surface and improve security posture, according to the 2016 SANS survey on CM conducted during the months of July to September. In it, 63% of respondents said CM was improving their security posture.
Enforcing user security often can result in complex, costly and disruptive processes.
This report represents the results of a survey undertaken in the United States, Canada, Germany, and the United Kingdom on ransomware and related issues. The survey was conducted during June, 2016 with 165 organizations in the United States and 125 each in the other nations for a total of 540 surveys completed. In order to qualify for participation in the survey, respondents had to be a CIO, IT manager, IT directory, CISO or in a related role; and knowledgeable about security issues within their organization. A total of 21 questions were included in the online survey. Results from the other surveys are available in separate survey reports to be published by Osterman Research and Malwarebytes.
Reliable. Secure. Constant. These qualities should define the energy and utilities industry, and usually they do. Electric, gas, and water utilities are built on a highly regulated framework, run by professionals, and backed by decades of operating experience and billions of dollars of infrastructure investment. Even so—and even with strong regulatory compliance—a successful cyber attack is still in the cards. The industry views that prospect with grave concern, for the consequences of such an attack on the companies supplying a city or a nation’s fuel, electricity and drinking water could reach far beyond any purely economic impact. The health and welfare of a whole region or even an entire nation could be at risk.
Data breaches are on the rise. The number of breach notifcations issued by the New York State Attorney General’s ofce, for example, has risen 40% during 2016 compared with the same period a year earlier.
Cyber defense automation is an imperative. Defensive costs are increasing and automation is necessary to manage the staggering number of devices and endpoints and to better defend our digital systems, resources and assets. Analytics must be integrated with direct policy feedback without requiring human intervention or approval for all responses. Cyber-attacks are automated but still under human direction and control, and therefore cyber defenses must also be automated to have any chance of protecting cyber and digital assets from both the automated attacks and the human element behind those attacks.
Veracode’s research team performed a set of uniform tests across six home automation devices and organized the findings into four different domains: user–facing cloud services, back–end cloud services, mobile application interfaces and device debugging interfaces.
Implementing and measuring Critical Security Controls (CSC) requires analyzing all data types (structured, semi-structured and unstructured). This implementation can be a daunting task. One of the goals of effective implementation of Critical Security Controls is to automate as much as possible. Machine learning techniques can help automate many of the measurements in Critical Security Controls. This paper proposes a method to integrate all types of data into a single data repository, extract relationships between different entities and perform machine learning to automate the analysis. This solution provides the security team the ability to analyze the information, and make data-driven security decisions.
Did you know that privileged users often are your riskiest employees? What are they doing to put your data at risk?
2015 Energy Industry Cybersecurity Report
Strategic Cybersecurity: A Toolkit for Prioritizing, Coordinating, and Transforming Your Cybersecurity Program