Affective Computing’s to tackle Security Challenge.docx

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Affective Computing’s to tackle Security Challenge “Physical and Cyber Security – Behavioral Analytics” Final Project Report for “Introduction to Affective Computing” (CMPSCI 590AC) Summer, 2016 Shivangi Pandey
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1. Introduction Physical security challenge has always existed and humans have development tools, houses and security systems with automated mechanism to protect them and their property from loss due to left, forced acquisition etc. Now society faces challenges from Cyber space, where there is no need to be physically present to steal or destroy the valuable information since damage can be done remotely using computer networks in today’s hyper connected world from any where. Cyber war between nations state has become one of the biggest challenges for our society and USA alone will be spending $170B on cyber security by 2020. Another challenge faced by society on security today is individuals or small group of individuals determine to create havoc due to their association with militants/terrorists group or mentally ill individuals as we have seen in last decade in USA. Affective Computing is computing that relates to, arises from or deliberately influences emotion or other affective phenomena. Emotion is fundamental to most aspects of life and everyday tasks. Emotions and behavior of peoples acting suspicious can be detected as long as Machine Leaning is trained over large volume of training, validation and testing data captured from real world example. In today’s world one does not have to be at power generation plant or distribution center to cause grid shutdown or cause damage to nuclear plant if they are able to hack into the computer systems connected to smart grid or nuclear plants, they can issue the commands to create significant damage. Information highway brought a lot of efficiency and convenience in daily life like no need to visit to bank to deposit or transfer the money but same time same convenience can be used by hackers to act as legitimate user and transfer money to unintended accounts. This paper will focus on an enterprise security system but
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same model can be extended for bigger entity like nation as well. Affective computing is currently used by cyber criminals to do coordinated attacks to take an organization down or used as advance persistent threats to steal the intellectual property or spy on organization and peoples without detection. To solve these challenges, industry has discovered that it needs to use Affective computing with Machine Learning. Availability of high performance processors, Graphics Processors, DRAMs, storage and Fast/Big Data platform have played a big role in last decade. 1.1 Background Behavioral Analysis system consists of following elements 1. Data Collection Engine “ Images, Speech, machine logs structured and unstructured” 2. Feature extraction engine to extract the relevant features for analysis 3. Data Enrichment Engine to enrich data with specific environment values 4.
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