PPT-A Privacy Threat Model for

Seattlites Adam Shostack amp many members of Seattle Privacy Coalition amp TA3M Disclaimer Adam is speaking for Adam and no one else This was a group effort Nothing here is intended to represent anyone elses opinion. By Tom Madden, Chief Information Security Officer, Centers for Disease Control and Prevention. BACKGROUND. 34 years with the federal government. 27 years involved in cyber security (was cyber security when cyber security wasn’t cool). . Ahmadi. , Nam Pham, Raghu . Ganti. , . Tarek. . Abdelzaher. , . Suman. . Nath. , . Jiawei. Han. . . Pallavi Arora. Privacy-aware Regression Modeling of Participatory Sensing Data. 2016. . On the road to nowhere…. One billion bank heist:. The gang – dubbed “. Carbanak. ” by Russian security company Kaspersky – has been stealing directly from banks rather than posing as customers to withdraw money in the biggest cyber heist to date.. Threat Correlation. Jamison M. Day, Ph.D.. Distinguished Data Scientist. Overview. Network Activity & Threat Correlation. Creating Value Within Your Organization. Sharing Value Between Organizations. by . Virginia . Mushkatblat. INC MAGAZINE . FASTEST . JOB CREATION CHART. WHY SECURITY?. JP MORGAN CHASE. TARGET. HOME DEPOT. SNAPCHAT. CSU. Healthcare.gov. Memorial . Hermann . Hospital. AltaMed. Health . John William Shinsky. john.w.shinsky2.civ@mail.mil. Problem Statement. Is line-of-sight enough to analyze a vehicles vulnerability to an attack?. Speed?. Continuous line-of-sight?. Kill Chain Sequence Time?. Accomplishments:. Read two chapters from the Deep Learning textbook.. Linear Algebra review from the Deep Learning for Natural Language Processing textbook.. Read an article on Abstractive Text Summarization using Sentiment Infusion.. Florian Tramèr. Intel, Santa Clara, CA. August 30. th. 2018. First they came for images…. The Deep Learning Revolution. The Deep Learning Revolution. And then everything else…. The ML Revolution. . By Marc-Andre Frigon. This disclaimer informs you that the views, thoughts, and opinions expressed in this presentation belong solely to the author, and not necessarily to the author’s employer, organization, committee or other group or individual. . patient care; www.innovativedecisions.com ffffffffx/MCIxD 0 x/MCIxD 0 ally the more fair a model is the higher the privacy risk of the model on the unprivileged subgroups will be Fairness constraints force models to perform equally on all the Eduardo . Cuervo. Amre. . Shakimov. Context of this talk…. Do we sacrifice privacy by using various network services (Internet, online social networks, mobile phones)?. How does the structure/topology of a network affect its privacy properties?. Development and Testing of Navy Torpedoes in A Full Fidelity Simulated Undersea Environment . ITEA July 2021. Carlos Godoy. carlos.godoy@navy.mil . Kenny Sanchez . kenneth.s.sanchez@navy.mil. Acknowledgement.