Current Threat Environment

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Current Threat Environment Software Engineering Institute Carnegie Mellon University Pittsburgh, PA 15213, PhD Technical Director, CERT mssherman@sei.cmu.edu 29-Aug-2014

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Copyright 2014 Carnegie Mellon University This material is based upon work funded and supported by the Department of Defense under Contract No. FA8721-05-C-0003 with Carnegie Mellon University for the operation of the Software Engineering Institute, a federally funded research and development center. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the United States Department of Defense. NO WARRANTY. THIS CARNEGIE MELLON UNIVERSITY AND SOFTWARE ENGINEERING INSTITUTE MATERIAL IS FURNISHED ON AN AS-IS BASIS. CARNEGIE MELLON UNIVERSITY MAKES NO WARRANTIES OF ANY KIND, EITHER EXPRESSED OR IMPLIED, AS TO ANY MATTER INCLUDING, BUT NOT LIMITED TO, WARRANTY OF FITNESS FOR PURPOSE OR MERCHANTABILITY, EXCLUSIVITY, OR RESULTS OBTAINED FROM USE OF THE MATERIAL. CARNEGIE MELLON UNIVERSITY DOES NOT MAKE ANY WARRANTY OF ANY KIND WITH RESPECT TO FREEDOM FROM PATENT, TRADEMARK, OR COPYRIGHT INFRINGEMENT. This material has been approved for public release and unlimited distribution. This material was prepared for the exclusive use of Participants of C3E Workshop and may not be used for any other purpose without the written consent of permission@sei.cmu.edu. Carnegie Mellon and CERT are registered marks of Carnegie Mellon University. DM-0001785 2

Current Threat Environment Usual view of threat environment Looking backwards from today s threats Looking forwards to future threats The need for prevention is pressing 3

Usual view of threat environment 90% of US busin ss s r port b ing h c d ~--- 59% r port b ing h ck d mort th n one -- ~=l.~~~.~(.:,'*fll TOTIUIAIWAI - ~ IIIII Target Earnings Slide 46% After Data Hreach S12J;r l2\\edu SI..MC:IIa1lo;o.v ~%01~) ~«< A ~ w ~ ~ ~ ~ ~ ~ ~ ~IJ J01J 2014 Sources: Poneman Institute, CNNMoney study, May 28, 2014; McAfee Quarterly Threat Report, June 2014; Wall Street Journal, Feb 26, 2014 retailcustomerexperience.com - 5_lessons_learned_from_recent_retail_data_breaches.pdf - Software Engineering Institute 4

Looking backwards from today s threats 92% of the 100,000 incidents from the last 10 years can be described by 9 basic patterns Insider misuse DOS attacks Cyber-espionage Crimeware Web app attacks Physical theft and loss Payment card skimmers Point-of-sale intrusions Miscellaneous errors 5

Looking forward to future threats Technology Evolving role of people in cyber security Learning from data: measurements, metrics, analysis 6

Cyber threats track evolution of technology Software is the new hardware Covering the next last mile Expanding endpoints 7

Software is the new hardware IT moving from specialized hardware to software, virtualized as Memory Storage Servers Switches Networks Cyber-physical systems (CPS) evolving to a computer with interesting peripherals Airplane function in software moved from 8% to 80% since 1960 Software defined radios drive communication Television evolved to digital signal processors Hardware security needs software analogs New programming models need secure coding guidelines Guard against side channel attacks enabled by virtualization 8

Covering the next last mile securing the border and end points The last mile has expanded to Cellular Main processor Base band processor Secure element (SIM) Industrial and home automation SCADA Bluetooth Zigbee Automotive Intravehicular: more than 50 networked processors Vehicle to infrastructure (V2I): congestion management, emergency services, law enforcement Vehicle to vehicle (V2): safety, efficiency Aviation Fly by wire Next Gen air traffic control Smart grid Embedded medical devices 9

Evolving role of people in cyber security Analysts: Soaring need for cyber analysts Bureau of Labor Statistics projects information security analyst jobs to increase by 20% or more through 2018 Need validated measurement and testing of needed skills, at individual and team level Optimizing analyst effectiveness: Automation assists analysts What can be automated and what left to the analyst Trade off between training and application Developers: Development becoming assembly over creation At least 75% of organizations rely on open source as the foundation of their applications Weak or absent security tracking in the software supply chain Adversaries: Culture role in cyber security Cultural influences on development and attack behavior 10

Learning from data: measurements, metrics, analysis Biggest challenges Determining leading indicators Reducing false positives Need to extract information from data from across the software lifecycle Applying techniques across disciplines including Metric and model definition Social and psychological experimentation Machine learning Statistical modeling Applications to Real-time analysis Retrospective insight 11

An ounce of prevention is worth a pound of cure We wouldn't have to spend so much time, money, and effort on network security if we didn't have such bad software security. Bruce Schneier in Viega and McGraw, Building Secure Software, 2001 13

The need for prevention is pressing 19% fail to carry out security requirement definition 27% do not practice secure design 30% do not use static analysis or manual code review during development 47% do not perform acceptance tests for thirdparty code Mission thread (Business process) More than 81% do not coordinate their security practices in various stages of the development life cycle. Source: Forrester Consulting, State of Application Security, January 2011 14

Security by default - Software Engineering Institute 15

Contact Information (412) 268-9223 mssherman@sei.cmu.edu Web Resources (CERT/SEI) http://www.cert.org/ http://www.sei.cmu.edu/ 16

Software Engineering Institute Carnegie Mellon University - Software Engineering Institute ( :m m :,.dt \lt llunl nh t.. sify 17