Why Software is Our Greatest Crime-Fighting Superhero

Why Software is Our Greatest Crime-Fighting Superhero

The Federal Bureau of Investigation recently released its annual report, “Crime in the United States,” which stated that in 2014 there were 1.2 million violent crimes committed in America, 63.6% of which were aggravated assaults. In addition, 8.2 million property crimes were reported by law enforcement agencies; victims suffered financial losses of approximately $14.3 billion.

However, not all larceny occurs in “the real world,” per say. In a separate FBI report on Internet crime, cybercrimes accounted for nearly 270,000 documented incidents last year. These illicit activities, which include auto and real estate fraud, government impersonation scams and extortion, resulted in total losses of $800 million.

With the sheer volume of crimes being committed on a daily basis and the severity of the resulting financial damages, clearly more could be done to deter future incidents. Unfortunately, as technology advances, criminals become more sophisticated in their methods, and it becomes even more paramount to remain multiple steps ahead.

Information Fusion in Action: A Demo of Objectivity’s ThingSpan

Information Fusion in Action: A Demo of Objectivity’s ThingSpan

Information fusion has its foundation in data fusion as used by military and intelligence agencies, generally defined as the use of techniques that combine data from multiples sources and gather that information in order to achieve inferences. This process would be more efficient that if the fusion was achieved by means of a single source.

Depending on the model used, there are several levels of assessment or refinement. As the fusion process goes through these different levels, the information is refined as more value is added. Information fusion can be defined as the process of merging information from disparate sources despite differences in conceptual, contextual and typographical representations, typically combining data from structured, unstructured and semi-structured resources.

The world is full of real world objects (people, places, things) and relationships (knows, likes). Information fusion works with these real world objects and relationships, and in the fusion process discovers new objects and relationships. The best way to represent these is in an object model representation.

Deciphering the Buzzwords: An Infographic on Information Fusion

Deciphering the Buzzwords: An Infographic on Information Fusion

As a writer and marketer, I’m no stranger to using catchy buzzwords to succinctly explain an important concept that many people are facing. Despite the fact that buzzwords are used so ubiquitously that they are often added to the Oxford English Dictionary (including emoji, twerk, and cakepop, to name a few), they are not as beloved in the enterprise technology industry as they are among consumers.

The irony behind our love/hate relationship with buzzwords, such as Big Data and IoT, is that everyone throws these labels around, but no one can agree on what they mean.

To dispel some of this confusion, I’m here to discuss a term that Objectivity has been at the forefront for years: Information Fusion.

Announcing ThingSpan, Objectivity’s Information Fusion Platform for Big and Fast Data

Announcing ThingSpan, Objectivity’s Information Fusion Platform for Big and Fast Data

Objectivity has been a pioneer in the world of Big Data, enabling leading businesses and government organizations to rapidly store, analyze, and find all the relationships and connections within their data from multiple sources, even at enormous scale.

Since our company’s founding more than 20 years ago, our solutions have continually expanded to address the most complex and demanding Big Data challenges—and today, we’re thrilled to announce the newest addition to our product line: ThingSpan, a purpose-built information Fusion platform that simplifies and accelerates an organization’s ability to deploy Industrial Internet of Things (IoT) applications.

Information Fusion and Data Integration: Fast vs. Batch

Information Fusion and Data Integration: Fast vs. Batch

Almost any popular, fast-growing market experiences at least a bit of confusion around terminology. Multiple firms are frantically competing to insert their own “marketectures,” branding, and colloquialisms into the conversation with the hope their verbiage will come out on top.

Add in the inherent complexity at the intersection of Business Intelligence and Big Data, and it’s easy to understand how difficult it is to discern one competitive claim from another. Everyone and their strategic partner is focused on “leveraging data to glean actionable insights that will improve your business.” Unfortunately, the process involved in achieving this goal is complex, multi-layered, and very different from application to application depending on the type of data involved.

Turning Data into Intelligence for Improved Security

Most people today are aware that businesses and infrastructure are increasingly at risk of a broad spectrum of security events, including terrorism, Advanced Persistent Threats (APT), fraud, insider attacks, and other criminal activities. While many are focused on creating technologies to counter such threats, others are developing methods that can proactively track suspicious behavior patterns and activities in order to reveal hidden threats and dangers in enough time to take immediate action to prevent them from occurring in the first place. One approach, known as Information Fusion, is seeing significant inroads as a means to stop threats before they can be executed. For example, governments and large organizations currently have custom-built, complex solutions to capture, store, and search large amounts of real-time, streaming data from different sensors and sources such as satellites, monitoring systems, communication networks, mobile devices, and digital media. Built on extremely scalable and distributed technologies, these solutions enable analysts to build on top of the data and add human inferences to help create a realistic view of the situation being monitored. This incorporation of human reasoning as part of the data being collected is the differentiation between basic Data Integration and complex Information Fusion. The value of Information Fusion systems is to provide in-time access to all relevant components of Big Data for analytic applications. This enables the discovery of hidden connections and relationships within disparate data, allowing analysts to “connect-the-dots” and develop a common view of multiple data streams to support advanced analytic applications. Objectivity’s products, Objectivity/DB and InfiniteGraph, are based on object and graph oriented technologies, making them well-suited to support this type of...