Manually classifying the content on a single web page takes but a few seconds to accomplish. Analyzing the keywords – words or phrases – used and the number of instances of each – keyword density – is one way to go about it. When needing to classify the content on billions of web pages at a time, however, the task becomes overwhelmingly daunting for any human eye to handle. In this scenario, only an automated content classification engine can succeed.
Prior to this blog post, zveloLABS published a phishing URL alert about fake Apple account verification websites. Now, zvelo’s team of engineers and researchers has unearthed a new phishing attack campaign using fraudulent Facebook log-in sites.
Instances of large-scale compromises of both private industry and public institutions in 2013 prompted a flurry of activity among security researchers to identify emerging and established threats. Commonly identified as Advance Persistent Threats (APTs), this phenomenon is expected to continue well into the foreseeable future. Fundamental to the spread of these threats is one of their foremost methods of propagation – a water hole attack.
zVelo has received many requests from its technology partners who are in the web filtering and parental control sectors to institute and support a new category that can be used to identify websites that promote self-harm behaviors. As a result of such demand, a new “Self Harm” category has been added to the zveloDB® URL database.
How does zvelo provide the most accurate content categorization service and the best URL database available? The approach is two-fold and while a substantial chunk of the workload is handled by zvelo's line-up of machine learning and artificial intelligence-based categorization processes and systems, the quality assurance and other daily efforts put forth by its human Web Analysts can never be discounted.
This article will be updated periodically, in support of numerous global online safety awareness campaigns occuring every year – Safer Internet Day (promoted in February), Cyber Security Awareness Month (October), IWF Awareness Day (also in October) and others. During these times, web safety advocates, companies, organizations and professionals worldwide raise awareness about safer and more responsible use of online technologies and mobile devices. Following is a living repository of online resources, guides, tips and entities aimed at helping everyone enjoy worry-free Internet experiences. Additional web safety resources will be hand-picked and added as they are discovered. To possibly be included in this list, or if other online safety resources exist that deserve mention, please feel free to comment below. Including a link and a brief description with each comment helps.
Static HTML websites are becoming increasingly rare, and nowadays sites pack quite the punch. We’ve grown accustomed to photo and video slideshows, widgets, feeds, social network integrations, and other dynamic elements. Websites come overloaded with media, are more interactive, and the content can vary dramatically from page-to-page and can differ even more between end-users or browsing sessions. Much of the content is pulled in dynamically from external sources and most of us fuel the Internet’s growth by creating and uploading content of our own daily and at extremely high upload rates. Making sense of it all can be quite the challenge for technology vendors “needing to know” and following are insights into zvelo’s content categorization approach.
Reports are plentiful of non-human bots gaming the online advertising industry by delivering fraudulent impressions and click traffic, and the Internet Advertising Bureau (IAB) took note. The IAB released the “Traffic Fraud: Best Practices for Reducing Risk to Exposure” on December 5, 2013, to help online media buyers, publishers and ad networks mitigate the dilemma.
People don’t seem to worry much about privacy when “checking in” to a favorite local restaurant or coffee shop, or from other social media posts that reveal one’s location. What if you were approached by a complete stranger who knew your name and other personally indefinable information within minutes after making an upload? A few socialites got quite the shock after a social media experiment revealed how much personal information can be extracted from publicly viewable status updates.