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Ariel Weintraub on Putting Data to Work in the SOC and IAM Ariel Weintraub joined MassMutual last fall to focus on putting datascience to work to help improve the insurance company's security operations and identity and access management programs. What are the early use cases and lessons learned?
22, 2024, CyberNewswire — INE Security offers essential advice to protect digital assets and enhance security. Warn “Small businesses face a unique set of cybersecurity challenges and threats and must be especially proactive with cybersecurity training,” said Dara Warn, CEO of INE Security. “At Cary, NC, Oct.
WestCap-Led Funding to Drive Click-Fraud Protection, Ad Integrity Expansion Human Security's recent $50 million growth funding, led by WestCap, will drive the development of click-fraud defense and enhance advertising integrity solutions.
Cisco’s $28 billion acquisition of Splunk comes at an inflection point of security teams beginning to adopt to working with modern, cloud-native data lakes. Related: Dasera launches new Snowflake platform For years, Splunk has been the workhorse SIEM for many enterprise Security Operation Centers (SOCs).
Social news aggregation platform Reddit suffered a security breach, attackers gained unauthorized access to internal documents, code, and some business systems. “Based on several days of initial investigation by security, engineering, and datascience (and friends!), ” continues the notice.
“The NITEC innovation challenge,” said Mike Street, Head of innovation and datascience at the NCI Agency, “is a great way for a wide range of companies and organizations to share their innovative products and services with the NCI Agency. Copyright (C) 2014 Media.net Advertising FZ-LLC All Rights Reserved -->.
New Head of Enterprise Cybersecurity Succeeds CISO Jim Routh Less than a year ago, Ariel Weintraub was dabbling in datascience as head of security operations and engineering at MassMutual, working under CISO Jim Routh. Now she’s replaced Routh as the new head of enterprise cybersecurity - and she welcomes the challenge.
The top drivers of the continued growth of cybersecurity are: the growing need to protect the API supply chain, the inadequacy of existing identity management systems, and the unfulfilled promise of data-driven AI-powered cybersecurity systems. Securing APIs. Every week, we see a new pitch for an API supply chain security startup.
Researchers at security firm Duo Security have created a set of open source tools and disclosed techniques that could be used to identify large Twitter botnet. Security experts from Duo Security have developed a collection of open source tools and disclosed techniques that can be useful in identifying large Twitter botnet.
“Investigations of this kind are primarily conducted by Binance’s internal risk intelligence unit known as Binance Sentry as well as an analytics arm, the SecurityDataScience division.” The post Ukraine police and Binance dismantled a cyber gang behind $42M money laundering appeared first on Security Affairs.
Microservices 1 is a powerful technology that is the kernel for modern cloud architecture, and it’s going to drive how people build, manage and deploy secure apps. And the ecosystem that’s going to drive all this will need to address old challenges, such as security, identity, and logging, with new tools. My key takeaways from KubeCon.
Yet, in bringing us here, APIs have also spawned a vast new tier of security holes. Yet, API security risks haven’t gotten the attention they deserve. It has become clear that API security needs to be prioritized as companies strive to mitigate modern-day cyber exposures. Thus security-proofing APIs has become a huge challenge.
When CyberTown, USA is fully built out, it’s backers envision it emerging as the world’s premier technology hub for cybersecurity and datascience. It’s mission has been to seek out and assist government cyber specialists in a position to enter the private sector and build commercial cyber and datascience companies.
While datascience and machine learning are related, they are very different fields. In a nutshell, datascience brings structure to big data while machine learning focuses on learning from the data itself. What is datascience? This post will dive deeper into the nuances of each field.
The BlackCat/ALPHV ransomware gang claims to have stolen 80GB of data from the Reddit in February cyberattack. In February, the social news aggregation platform Reddit suffered a security breach , attackers gained unauthorized access to internal documents, code, and some business systems. continues the notice.
Cary, NC, May 28, 2024, CyberNewsWire — If there is a single theme circulating among Chief Information Security Officers (CISOs) right now, it is the question of how to get stakeholders on board with more robust cybersecurity training protocols. Human error remains one of the leading causes of security breaches.
Researchers from security firm Aqua observed threat actors exploiting misconfigured JupyterLab and Jupyter Notebook servers to hijack environments, deploy streaming tools, and duplicate live sports broadcasts on illegal platforms. JupyterLab and Jupyter Notebook are widely used interactive tools for datascience.
They took advantage of the weaknesses inherent in an increasingly connected world and highlighted the need for companies to not only ensure their own security but also look at the security of their vendors and put into place necessary protections. Multi-party cyberattack data (source: Cyentia). Collateral Damage.
Datascience is playing a fundamental role in a more dynamic approach to cybersecurity, says Jim Routh, CISO of Aetna, who stresses the importance of applying machine learning to front-line datasecurity controls. Routh will be a featured speaker at the ISMG Security Summit in New York Aug.
GCIS was a Davos-level conference with no vendors and no selling, where scores of chief security information officers (CISOs), top CEO’s, industry and government thought leaders and leading innovators discussed the myriad challenges in and around cybersecurity and possible solutions in today’s environment.
The importance of identifying data sources, collecting those sources, and applying them wisely is key to prevention, the reduction of threat actor dwell time, and threat mitigation.
Every security team craves clear visibility into the endpoints, networks, containers, applications, and other resources of the organization. To address that limitation, a new tool is emerging: Securitydata lakes (SDLs), which might provide a solution that enables unfiltered visibility for security teams. What is SIEM?
So when DataScience teams think about AI governance, they think model management. Model management, an element of MLOps, ensures that datascience best practices are followed when building and maintaining an AI model throughout its lifecycle. Notice that “AI use case” is the subject, not the AI model.
His resume also says he is a datascience intern at Mondi Group , an Austrian manufacturer of sustainable packaging and paper. ” “He’s not even an information security specialist,” Quotpw said of Sergey. Mr. Proshutinskiy did not respond to requests for comment.
The combination of datascience expertise, cloud resources, and Cato's vast data lake enables real-time, ML-powered protection against evasive cyberattacks, reducing risk and improving security.
Despite public reckoning over mass surveillance, NSA famously faces the challenge of collecting such extreme quantities of data that, on top of legal and ethical problems, it can be nearly impossible to sift through all of it to find everything of value. The field of datascience aims to solve them.
This in turn has made security tools less intuitive and self-explanatory. This is not because they don’t want to learn the tool but rather most threat hunters don’t have the time to specialize on an individual tool in their security stack. Pairing data scientists and threat hunters in a cyber defence team might just solve this issue.
Wage growth is starting to accelerate, and CIOs could find themselves paying premiums for certain roles in high demand such as datascience, AI, security and cloud technology.
Despite all the cybersecurity defenses in enterprises, the human element matters the most, as phishing attacks remain the top avenue of incursion, accounting for more than 85% of all breaches, according to the annual Verizon Data Breach Investigations Report. That’s where incident response software and services come in.
By consistently updating and expanding our training modules, we ensure that every course reflects the latest in technology and security practices. This fall, the prestigious SC Awards recognized INE Security, INE’s cybersecurity-specific training, as the Best IT Security-Related Training Program. another small business user. .”
On a business level, decisions based on bad external data may have the potential to cause business failures. In business, data is the food that feeds the body or enterprise. Better data makes the body stronger and provides a foundation for the use of analytics and datascience tools to reduce errors in decision-making.
Several women in data engineering, datascience, datasecurity and IT management share their views on how other women can make the best of a career in technology.
Unlike most other AI research projects, ChatGPT has captivated the interest of ordinary people who do not have PhDs in datascience. ChatGPT Security Threats. Phishing accounts for nearly 90% of malware attacks, according to HP Wolf Security research. In a week, the app gained more than one million users.
This pipeline should include hiring and training new staff who may not have a STEM (science, technology, engineering and maths) background and developing existing employees’ skills. Not sure where to start? Our commitment to building your Microsoft skills.
Artificial intelligence (AI) is becoming increasingly integral to information security. In fact, in its Reinventing Cybersecurity with Artificial Intelligence report , Capgemini found that 61% of respondents said they can no longer detect data breach attempts without the help of AI. That goes for information security, as well.
As social impact organizations accelerate digitization, they are increasingly aware of the untapped potential lying within their data, and how AI solutions leveraging this data can amplify impact. The organizations then began incubation projects alongside the DSE team, building models and data capacity alike.
Related: Why datascience is the key to securing networks. Kovetz: Some multi-factor authentication methods are not really secure. Now that we’ve created this platform that can add authentication, very dynamically, anywhere in the network, we’ve started to integrate with other security vendors. Kovetz: Exactly.
As The 2018 Thales Global Data Threat Report notes, “The top Big Datasecurity issue is that sensitive data can be anywhere – and therefore everywhere – a concern expressed by 34% of global and U.S. Moreover, encryption keys must be protected and managed in a trusted manner for security and compliance with regulations.
If you want to implement AI governance, you may face several challenges, including: AI models are complex and require a cross-functional team for development and deployment that includes expertise in various areas such as datascience, software engineering and compliance.
Source: “Smarter, Cleaner, Faster: How the Public Sector Can Leverage Machine Learning to Achieve Reliable and Trusted Data” Combine ML-driven data quality rule management with secure cloud computing. Leveraging datascience and automation to ensure reliable and trusted data is the new frontier.
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