{"id":66787,"date":"2017-11-14T21:08:40","date_gmt":"2017-11-14T13:08:40","guid":{"rendered":"https:\/\/wp-productionenv-bjg9h2g2bgg5b8aa.southeastasia-01.azurewebsites.net\/news\/leveraging-deep-learning-to-keep-cyber-assets-safe\/"},"modified":"2017-11-14T21:08:40","modified_gmt":"2017-11-14T13:08:40","slug":"leveraging-deep-learning-to-keep-cyber-assets-safe","status":"publish","type":"post","link":"https:\/\/starpath.global\/news\/leveraging-deep-learning-to-keep-cyber-assets-safe\/","title":{"rendered":"Leveraging Deep Learning to Keep Cyber Assets Safe"},"content":{"rendered":"<\/p>\n

Deep learning could prove to be one of the most critical tools for those engaged in ongoing cyber warfare, said a group of experts at the 2017 CyberSat Summit. During a Nov. 8 panel discussing the new paradigm of military satcom, Jon Korecki, who develops ViaSat\u2019s<\/strong> cybersecurity and information assurance strategy, said that deep learning holds \u201csome of the most promise\u201d in terms of its ability to catch malicious actors in cyberspace.<\/p>\n

Korecki described deep learning as \u201ca dynamic automated form of Artificial Intelligence (AI),\u201d able to more quickly and efficiently monitor swaths of code as analysts continually inject new threat intelligence.<\/p>\n

According to Korecki, the biggest problem in cybersecurity is its asymmetric nature. \u201cWe can spend billions of dollars plugging every hole, but we\u2019re always going to leave one open and we\u2019ll never know where it\u2019s going to be. And the enemy only has to find one to get in,\u201d he said. \u201cWe have to spend a higher magnitude of money to protect ourselves from their penetration.\u201d<\/p>\n

Essentially, he said, cyber warfare boils down to a matter of economics. Because it\u2019s unfeasible to pay countless analysts to manually pinpoint anomalies, Korecki suggested turning to more automated forms of detection \u2014 i.e. deep machine learning \u2014 to alleviate the cost difference between defense and offense.<\/p>\n

During the discussion, the panelists emphasized repeatedly that cost is central to the trajectory of cyber capabilities. While machine learning can be a powerful defensive tool, it can also be used as a means to malicious ends, and whoever develops such technology first has the upper hand. Consequently, Randy Blaisdell, owner\/operator at RL Blaisdell Consulting<\/strong> said his concern is that the enemy can evolve at a faster pace due to the resources they may have at their disposal. \u201cMost of us working on it from the good side are getting paid a reasonable amount of money,\u201d he said. \u201cOne of the challenges we\u2019re looking at [is] trying to figure out how we can invest in these technologies fast enough to either keep pace with or outpace the enemy. It relates very much back to this issue of being able to pay the talent pool to do it.\u201d<\/p>\n

As Korecki pointed out, one of the government\u2019s biggest challenges is that it cannot always afford to keep the talent it needs. \u201cThe unfortunate truth is the government doesn\u2019t pay as well as the commercial industry,\u201d he said. This holds true for criminal cyber hackers as well, Blaisdell echoed, who can make exorbitant sums of money in places such as China and Russia.<\/p>\n

So, how can government agencies keep pace when handicapped by limited resources? One solution the panelists suggested is changing the way they acquire systems from the private industry. ViaSat in particular is taking a new approach to how it works alongside the government, Korecki said, by leasing whole systems on an annual contract basis rather than disparately selling spectrum or hardware. A more integrated solution allows service providers \u201cfull visibility\u201d across the entirety of the system, meaning they are able to more competently provide end-to-end cyber protection, Korecki said, \u201cfrom the terminal in the plane to the connectivity in their network.\u201d<\/p>\n

Blaisdell pointed out that the culture of acquisition in the government is resistant to the idea of leveraging existing commercial assets. He agreed that owning systems outright isn\u2019t necessary in all situations, particularly for the space business where hardware quickly becomes outdated. \u201cIn the space business, your focus needs to be on producing the capability for a warfighter or whoever your customer is. You may well be able to do that entire mission and never own a physical option other than the display you\u2019re putting in front of somebody,\u201d Blaisdell said. \u201cWhat we\u2019re recommending is to look at how they integrate the space systems they currently have or the ones they\u2019re currently developing with commercial systems.\u201d<\/p>\n

To address some of these concerns, Rob Lynn, a telecommunications engineer at the Defense Information Systems Agency<\/strong> (DISA), said the government is undergoing a comprehensive Analysis of Alternatives (AOA) to update its acquisition models. \u201cThere\u2019s a whole gamut of areas this AOA is looking at to try and come up with a picture of what\u2019s going to be required for the next generation,\u201d he said, including the space segment, related policies, the international cyber environment and geopolitical concerns.<\/p>\n

The key factor distinguishing this AOA, Lynn added, is the inclusion of commercial expertise throughout the process. Although he was unable to provide an estimated timeline of when it will be released, he said once completed the AOA could serve military requirements for at least 10 years.<\/p>\n","protected":false},"excerpt":{"rendered":"

Deep learning could prove to be one of the most critical tools for those engaged in ongoing cyber warfare, said a group of experts at the 2017 CyberSat Summit. During a Nov. 8 panel discussing the new paradigm of military satcom, Jon Korecki, who develops ViaSat\u2019s cybersecurity and information assurance strategy, said that deep learning […]<\/p>\n","protected":false},"author":1,"featured_media":66788,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[2],"tags":[],"class_list":["post-66787","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"acf":[],"_links":{"self":[{"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/posts\/66787"}],"collection":[{"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/comments?post=66787"}],"version-history":[{"count":0,"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/posts\/66787\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/media\/66788"}],"wp:attachment":[{"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/media?parent=66787"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/categories?post=66787"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/starpath.global\/blog\/wp-json\/wp\/v2\/tags?post=66787"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}