Security News
Avaya announced an expansion of its artificial intelligence-powered customer experience capabilities for Avaya OneCloud CCaaS customers, through an extended relationship with Amazon Web Services. As an AWS Partner offering AWS Contact Center Intelligence solutions, Avaya can enable customers to leverage AWS AI Services and Machine Learning capabilities to drive more rewarding customer and employee experiences across both voice and digital channels through natural, conversation-driven interactions powered by AI and ML. Avaya's integration with AWS CCI strengthens its portfolio of contact center solutions delivering enhanced customer engagement through better, faster, and more relevant insights and actions, building brand preference while also improving operational efficiency.
In order to defeat these cyber bad guys, security pros and AI should focus on what they do best. AI is markedly better at security-threat detection if clear guidelines can be turned into training data for AI. "For instance, if there are guidelines on certain kinds of IP addresses or websites that are known for being the source of malicious malware activity, the AI can be trained to look for them, take action, learn from this, and become smarter at detecting such activity in the future," writes Sivaraman.
Arista Networks announced an Attack Surface Assessment, an advanced security service delivered through the recent acquisition of Awake Security. "To make matters worse, sponsored groups can steal intellectual property and attack resources that are now in the wild. Big companies and banks are still getting hacked and technologies like IoT are huge threats. We need to reboot security and make it simple to manage. I believe Arista Networks is simplifying security."
That machine-to-machine communication, right? As you speed that up, and you speed up that attacker machine-to-machine communication, you really can start to up-level the ability to conduct these denial of service attacks. While they may be not have been necessarily as in fashion, we're seeing that the ransomware trends, and some of those more, you will probably see a resurgence or DDoS attacks is there, but you crank into, and leverage the increased speed, and the increased dependency on IoT devices in a way that we maybe haven't seen them as monetized in the past, connectivity, ransom against connectivity, rather than ransomware files.
TechRepublic's Karen Roby spoke with Dr. Danda Rawat, professor of electrical engineering and computer science at Howard University, about artificial intelligence, machine learning and how they can help cybersecurity. Danda Rawat: My research projects are focusing on cybersecurity for artificial intelligence systems and the machine learning algorithms.
Howard professor says security must reach all types of networks, including IoT and ad hoc networks.
In his Chamber of Commerce commentary, Beyond the Hype - Artificial Intelligence in Cybersecurity, Housley writes, "While AI systems support cybersecurity by enabling prevention or detection and resolution of threats, they should not be considered the panacea to all cybersecurity problems." Next, the discussion during the webinar looked at how AI will benefit and enhance cybersecurity programs.
Data in an enclave cannot be read or modified by any entity outside the enclave itself, even if the host is physically compromised. AI and ML both leverage and create a number of data sets, each of which have different security requirements.
Blaize fully unveiled the Blaize AI Studio offering, the industry's first open and code-free software platform to span the complete edge AI operational workflow from idea to development, deployment and management. AI Studio dramatically reduces edge AI application deployment complexity, time, and cost by breaking the barriers within existing application development and machine learning operations infrastructure that hinder edge AI deployments.
The AI in cybersecurity market is projected to generate a revenue of $101.8 billion in 2030, increasing from $8.6 billion in 2019, progressing at a 25.7% CAGR during 2020-2030, ResearchAndMarkets reveals. The market is categorized into threat intelligence, fraud detection/anti-fraud, security and vulnerability management, data loss prevention, identity and access management, intrusion detection/prevention system, antivirus/antimalware, unified threat management, and risk & compliance management, on the basis of application.