5 Questions to Ask When Evaluating a New Cybersecurity Technology.

Source: SIAMRAT.CH via Adobe Stock

Any new cybersecurity technology should be not just a neutral addition to a security stack but a benefit to the other technologies or people managing them. 

The cybersecurity technology field is, shall we politely say, crowded. I recently returned from attending RSA, one of the biggest conferences in the industry. Trying to describe just how many new technologies and solutions I saw there feels a lot like trying to describe how big space is: Our brains can't actually process that kind of scale.

I imagined being a chief information security officer (CISO) at this event, trying to make decisions on what products or technologies would solve their particular organization's security weaknesses. It was, in trying to maintain my earlier commitment to being polite, overwhelming. There must be a better way to quickly figure out if a security technology is worth evaluating.

This ecosystem we have found ourselves in, of slapping new technologies into our security stacks, isn't working. Security staffs everywhere are pulled too thin trying to manage every new technology, and threat actors are continuously breaking through our protection technologies.

So, how do we break this cycle? When looking for security technologies, we start assessing how much value the technology provides — not just whether it can do what it promises to do, but also if it provides a net positive for the entire security stack and management teams.

We are moving into a new era of cybersecurity, and every investment must be prudent. In order to make these decisions, companies must start asking some fundamental questions about these technologies in order to understand the true value — or cost — of a security solution. These questions of proactivity, intelligence, autonomy, scalability, and benefit to the stack as a whole can help you find the most value in every security technology.

Importantly, these questions can also help you evaluate your existing technologies, as you now know in real life how they are (or are not) serving your network and your teams. The answers might surprise you.

Question 1: Is the technology proactive or reactive? 

 While almost any cybersecurity technology will be quick to use the word "proactive," we first should define what the term really means. A truly proactive technology is one sitting "left of boom," or, more simply, before a successful breach. Recently, almost all cybersecurity technology sits "right of boom," responding to and mitigating the effects of breaches that have already happened.

In modern security frameworks and stacks such as MITRE/NIST/zero trust, often the only left-of-boom technology in place is the firewall/next-generation firewall (NGFW). These decades-old technologies have been tasked with more and more, and yet they remain standard. We have to help the rest of the security stack by investing in more proactive technologies.

Question 2: How much cyber intelligence can the technology leverage?

It has become increasingly clear that the word of our time is "intelligence" — be it artificial, human, or, more in my world, cyber. The value of intelligence and data has never been higher, and this has proven especially true in the war against cybercriminals. 

 The future is intelligence driven, and the more intelligence a cybersecurity technology can act on, the better. Any cybersecurity technology must be informed by as much cyber/threat intelligence as possible. Without the data to make informed decisions about enforcement, threat actors automatically have an upper hand.

Question 3: Is the technology (truly) autonomous? 

 I cannot think of a cybersecurity technology that doesn't claim it is "autonomous." This has become so common in our industry that the word itself has almost lost meaning. However, with a cybersecurity staffing shortage that does not look to be going away any time soon, it's critical we evaluate what we mean by "autonomous" when thinking about a technology. How many hours of an employee's day (on average) does this technology require? Does this technology require another full-time employee to manage the alerts or logs? Does this technology automatically update? (And what are the down times like for them?) The answers to these questions should be: zero, no, and yes. Anything else is not an autonomous technology. 

 Question 4: How does the technology scale? 

 Threat actors have shown themselves to be nimble, inventive, and persistent in their attacks. The technologies we implement must be able to grow and adapt to these realities. Can they adapt to higher volumes, deeper obfuscations, and yet-unknown attack vectors? Knowing your technologies can grow with your network and adapt to an ever-changing threat landscape is vital in any security technology investment.

 Question 5: Can the technology work easily with existing technologies? 

 One of the biggest drivers of cybersecurity professionals is what's known as "alert fatigue." This is caused by too many technologies that are extremely sensitive in finding threats or breaches, yet are unable to communicate with each other easily, throwing multiple alerts for the same malicious traffic. The cybersecurity teams are then forced to sift through multiple erroneous/duplicate alerts, and are more prone to errors due to the large volume of traffic networks are receiving day and night. Sadly, this is just one example of how multiple technologies that aren't sharing information can impact a network's cybersecurity posture. 

 Any new cybersecurity technology you consider should be not just a neutral addition to the security stack, but rather a benefit to the other technologies or people managing them. Some questions to ask in this arena might be: Can it feed intelligence easily to other implemented technologies? Does it ease a pain point of another technology? Can it ingest information from other implemented technologies? 

 Rarely will a technology be able to adequately answer for more than one of these questions. For instance, a technology might be able to use lots of intelligence but isn't proactive and needs constant monitoring by employees. These are the challenges security teams face every time they make a decision about a new or existing security technology, but figuring out how much value each technology adds — or doesn't — is the best start.

Source: www.darkreading.com

 

EVOLVING TECHNOLOGY WILL CHANGE WARFARE.

Photo by: AUSA/Jared Lieberher

With the rapid evolution of technology, soldiers fighting on the battlefields of 2050 may not look too different from a science fiction movie or a video game, a senior Army leader said.

“Think about if you’re playing a first-person shooter video game, you’re going on the map, you have visibility on your heads-up display, you know where the enemy is, you have unlimited ammo and you have this amazing ability to never die,” said Young Bang, principal deputy assistant secretary of the Army for acquisition, logistics and technology.

“Now, we’re not quite there yet, but if you think about some of the things we’re working on right now, those are the foundational pieces to get us there," Bang said May 17 at the Association of the U.S. Army’s LANPAC Symposium and Exposition in Honolulu.

Bang said the Army is working hard to transform for the future. Citing as an example the 24 new technologies the Army plans to deliver in fiscal 2023, Bang said those capabilities are “foundational pieces” so that the Army, along with its allies and partners, can “drive this whole thing called integrated deterrence.”

From drone resupply to exoskeletons, the Army is looking at how it can make soldiers more lethal and agile, Bang said. “Take unlimited ammo,” he said. “We’re not quite there but imagine what you could do with drones.”

The Army is experimenting with that at Fort Moore, Georgia, he said. “They were literally dropping off ammo as soldiers were needing it,” Bang said. “It’s an experiment, but those are the possibilities we’re looking at, and the Army needs industry’s help to get us there.”

Soldiers also are testing the use of exoskeletons to carry heavy equipment, and the Army continues to fine-tune its Integrated Visual Augmentation System and develop robotic combat vehicles, among other capabilities, Bang said. “Imagine what the possibilities will be if you tie all that together,” he said. 

 As the Army continues its modernization, it faces an increasingly changing world, Bang said. “Change is constant, and the pace is increasing, and technology is increasing the pace of change,” he said. “With technology that’s driving change, humans have to be able to adapt.”

For the Army, that means “you train, you experiment together with the joint and multinational force,” he said. “The humans have to adapt,” he added. “They have to know how to use that technology and think about it differently.”

The Army also must be light, mobile and flexible, and it must view technology as an enabler instead of the solution to every problem, Bang said. “A lot of people, including me, get enamored by the shiny bauble,” he said. “We’ve got to shift from just the technology to also include the procedural—the teaming, the strategy, the employment. How are we going to use this?” 

 Ultimately, the Army must move from industrial warfare and even information warfare to digital warfare, Bang said. “That’s where we need to be, that’s our future state,” he said. 

 This requires open and modular systems capable of accepting plug-and-play updates, he said. The Army also must flatten and simplify its architecture and improve the way it manages data. 

 “Data is foundational, but we’ve got to simplify that data,” he said. “We have way too much information. Commanders don’t need all that. They need courses of action, they need information to make decisions, but they don’t need it all.”

source: www.ausa.org

 

Google Just Added Generative AI to Search.

Challenged by ChatGPT, the king of search launches a feature that can answer queries with text summarizing information found online.

Google Add Generative AI to Search.

SIX MONTHS AGO, Google didn’t appear remotely worried about its search business. Then OpenAI’s ChatGPT was unleashed, and Microsoft’s Bing spawned a chatbot.

At Google’s annual I/O conference today, the search giant announced that it will infuse results with generative artificial intelligence technology similar to that behind ChatGPT. The company is launching an experimental version of its prized search engine that incorporates text generation like that powering ChatGPT and other advanced chatbots.

Google’s reimagined search still involves typing a query, and it still responds with links to websites, snippets of content, and ads. But in some situations, the top of the page will feature text synthesized by AI that pulls from information found on different sources across the web, and link to those webpages. A user can ask follow up questions to get more specific information.

A query about the coronation of Britain’s new king might be met with a couple of paragraphs summarizing the event. If asked about ebikes, Google’s algorithms can list bullet-point recaps of product reviews published by various websites, and link to online stores where a user can make a purchase. The revamped version of search will be accessible in the US via a new feature called Search Labs, but it will not be activated by default or for all Google users.

Google’s AI-infused search is considerably tamer than ChatGPT, eschewing an anthropomorphized persona and avoiding topics that might be deemed controversial, such as politics and medical or financial advice. When asked if Joe Biden is a good president or for information about different US states’ abortion laws, for example, Google’s generative AI product declined to answer. 

“The technology is very early on, it has its challenges, and we will make mistakes certainly,” says Liz Reid, vice president of search at Google, who gave WIRED a preview of the new features ahead of I/O.

Google is moving quickly to add ChatGPT-like features to search, but whether users will find them useful remains to be seen. Product searches, for instance, synthesized material from different reviews, but it was not immediately obvious how the brief summaries might improve the search experience.

The unpolished feel of these new features may reflect the fact that their launch is a defensive move. Google has invested huge sums and major resources in AI over recent years, with CEO Sundar Pichai often calling the company “AI first.” Yet Google still found itself wrong-footed with the arrival of ChatGPT, a surprisingly clever and garrulous—though also fundamentally flawed—chatbot from OpenAI.

ChatGPT is powered by a machine learning model trained to predict the words likely to follow a string of text by digesting huge amounts of text, including vast numbers of web pages. Additional training, provided by humans rating the quality of the bot’s responses, made ChatGPT more adept at answering questions and holding a conversation. 

Because ChatGPT was trained on much of the web, users quickly found it a promising new way to search, even if the bot is prone to fabricating information. Microsoft seized on this potential by investing $10 billion in OpenAI in January and then incorporating ChatGPT into Bing a month later.

The hype and strong interest from users, who fed queries to ChatGPT and Bing chat by the millions, left Google scrambling to catch up. Researchers at the company had developed some of the core technology at work in the new chatbots, but Google had been cautious about publicly launching its precursor to ChatGPT, called LaMDA.

In March, Google changed strategy, announcing a ChatGPT competitor called Bard. In April, Google said it would combine its AI research group with another Alphabet company focused on AI, DeepMind. Now Google is infusing text-generation technology into its core product, search.

Google’s dominance and reputation could make this latest move the biggest test yet of the power and usefulness of ChatGPT-style technology. It’s also risky.

Because language models can fabricate, companies have to develop ways to check that the information served to users is accurate. And some online publishers are concerned about search companies scraping and regurgitating their content in ways that mean fewer referrals. Google also needs to avoid cannibalizing its search advertising business, which provides a significant chunk of the company’s revenue.

Source: www.wired.com

Google AI search different from Bard chatbot

 

How is the new Google AI search different from Bard chatbot?

Google already has a Bard chatbot that competes with ChatGPT, the chatbot from OpenAI that has generated huge excitement among users with its humanlike responses.

Google AI search different from Bard chatbot

 SO WHEN DO YOU GOOGLE AND WHEN DO YOU BARD?

The company says that traditional Google search should still be used for finding and seeking information, such as locating something to purchase. Bard is a chatbot with a persona that can hold humanlike conversations, and is intended to be used for creative collaboration, for instance, to generate software code or write a caption for a photo. 

WHAT ARE THE UPDATES TO GOOGLE SEARCH?

With the enhanced search termed the Search Generative Experience, Google's home page still looks and acts like its familiar search bar. The difference is in the answers: if the new Google detects that generative AI can be used to answer a query, the top of the results page will show the AI-generated response. The traditional links to the Web will remain below. For example, a search for "weather San Francisco" will as usual point a user to an eight-day forecast, while a query asking what outfit to wear in the California city prompts a lengthy response generated by AI, according to a demonstration for Reuters earlier this week. "You should bring layers, including a short-sleeved shirt and a light sweater or jacket for the day," the result stated, including links to websites where it gleaned such advice. Users will also be able to enter a brand-new "conversational mode," which similar to Bard and ChatGPT remembers the user's prior questions so users can ask follow-ups more easily. However, the company points out that conversational mode is not designed to be a chatbot with a personality; it is intended only to help hone search results. For example, its responses will never contain the "I" phrase, unlike Bard and ChatGPT. 

CAN I TRY THE NEW GOOGLE SEARCH NOW?

Not yet. U.S. consumers will gain access to the Search Generative Experience in the coming weeks via a wait list, a trial phase during which Google will monitor the quality, speed and cost of search results, the company said. 

CAN I TRY BARD NOW?

The company said on Wednesday that Bard is now available with no wait list in 180 countries and territories, and plans to expand its support to 40 languages.

Source: Reuters.com