{"id":614,"date":"2018-08-10T00:00:29","date_gmt":"2018-08-10T00:00:29","guid":{"rendered":"http:\/\/bocchinfuso.net\/?p=614"},"modified":"2026-03-20T07:32:10","modified_gmt":"2026-03-20T07:32:10","slug":"fit-mgt5157-week-6","status":"publish","type":"post","link":"http:\/\/bocchinfuso.net\/index.php\/2018\/08\/10\/fit-mgt5157-week-6\/","title":{"rendered":"FIT – MGT5157 – Week 6"},"content":{"rendered":"

The submissions for this assignment are posts in the assignment’s discussion. Below are the discussion posts for Richard Bocchinfuso, or you can\u00a0view the full discussion<\/b><\/a>.<\/p>\n

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from\u00a06.3 Discussion<\/a><\/div>\n
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Aug 10, 2018 1:02pm<\/div>\n
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Richard Bocchinfuso<\/span><\/a><\/div>\n
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Discussion: Describe the basis for effective collaboration of security defenses within and between organizations.<\/em><\/p>\n

This is an interesting question. I think ten years ago effective collaboration of security defenses within and between organizations would be highly dependent on effective open communication between these organizations. Today I think the effective collaboration of security defenses is being aided by two core technology shifts:<\/p>\n

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  1. Cloud<\/li>\n
  2. Machine Learning, Deep Learning, AI<\/li>\n<\/ol>\n

    Let’s start with the cloud. Today’s security providers are increasingly becoming cloud-enabled, they are relying on the aggregation of massive data sets (big data) for heuristics on massive compute farms that far surpass what is possible in a heuristics engine on a laptop, desktop or mobile device. Just about every security technology provider is leveraging the cloud and vast resources it provides. When organizations buy into the cloud-based security paradigms it is the equivalent of sharing and communicating information, but this information is now being aggregated, anonymized, analyzed and cross-referenced in real-time.\u00a0 (Quora Contributor, 2018)<\/p>\n

    Machine learning, deep learning, and AI are not just buzzwords, they are technologies that harness data and continuously train models that can begin to see things which are not visible to the naked eye. These technologies are greatly altering how we think about security. Security providers like\u00a0AlertLogic\u00a0(Links to an external site.)<\/span>Links to an external site.<\/span><\/span><\/a>,\u00a0Secureworks\u00a0(Links to an external site.)<\/span>Links to an external site.<\/span><\/span><\/a>\u00a0and many others that focus on IPS\/IDS and incident responses models that leverage data which is anonymized, but aggregated and analyzed across their entire customer base, this has tremendous value. Security providers like\u00a0Tanium\u00a0(Links to an external site.)<\/span>Links to an external site.<\/span><\/span><\/a>\u00a0and\u00a0Panda Security\u00a0(Links to an external site.)<\/span>Links to an external site.<\/span><\/span><\/a>\u00a0and others who focus on end-point security also use cloud technologies, big data and machine learning to provide superior heuristics. For example, the embedded anti-malware in Windows 10 makes use of “cloud-based protection” to better protect users, users are opted-in to collaborating and opting-out requires the user intervention that is buried in the bowels of the operating system and anti-malware (Windows Defender) configuration settings.<\/p>\n

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    Collaboration and engagement require a focus on Human-Computer Interaction (HCI) to drive system usability and adoption, this is especially true in the field of security. Users vary and they have different expectations of the systems they interact with, a simple blacklist of whitelist approach no longer gets the job done, these approaches slow productivity and encourage working around the system. (Coursera, 2018)<\/p>\n

    Intelligent security systems which leverage AI may be able to adapt security protocols based on user usage profiles. For example, what users took the lollipop and what users didn’t and should how security is enforced for these two user types differ? (DreamHost, 2018)<\/p>\n