UNITED STATES PATENT AND TRADEMARK OFFICE
`_______________________
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`_______________________
`APPLE INC.,
`Petitioner
`v.
`UNILOC LUXEMBOURG S.A.
`Patent Owner
`_______________________
`Case No. IPR2018-01028
`U.S. Patent No. 7,881,902
`
`DECLARATION OF WILLIAM C. EASTTOM II (CHUCK EASTTOM)
`
`Apple v. Uniloc, IPR2018-01028
`Uniloc's Exhibit No. 2001
`
`

`

`
`
`I.
`
`II.
`
`TABLE OF CONTENTS
`
`INTRODUCTION ........................................................................................................3
`
`BACKGROUND AND QUALIFICATIONS .....................................................................3
`
`III.
`
`THE ‘902 PATENT .....................................................................................................4
`
`IV.
`
`CLAIM CONSTRUCTION ............................................................................................5
`
`V.
`
`ONE OF ORDINARY SKILL IN THE ART ......................................................................5
`
`VI.
`
`GENERAL ISSUES ......................................................................................................5
`
`A. Motivation to Combine ......................................................................................5
`
`B. Cadence Window ...............................................................................................8
`
`VII.
`
`SPECIFIC CLAIM ELEMENTS ......................................................................................9
`
`A. 8.0 The method of claim 5, wherein determining the dynamic step cadence
`window comprises:” ....................................................................................... 10
`
`B. 8.1 computing a rolling average of stepping periods of previously counted
`steps; and ........................................................................................................ 11
`
`C. 8.2 setting the dynamic step cadence window based on the rolling average of
`stepping periods. ............................................................................................ 12
`
`VIII.
`
`CONCLUSIONS ....................................................................................................... 12
`
`IX.
`
`APPENDIX A – EASTTOM CV .................................................................................. 13
`
`A. Education ........................................................................................................ 13
`1. University Degrees ........................................................................ 13
`2.
`Industry Certifications ................................................................... 14
`3. Licenses ......................................................................................... 16
`
`B. Publications ..................................................................................................... 16
`1. Books 16
`2. Papers, presentations, & articles. ................................................. 17
`3. Patents .......................................................................................... 20
`
`C. Standards and Certification Creation.............................................................. 20
`
`
`
`1
`
`

`

`
`
`D. Professional Awards and Memberships ......................................................... 21
`
`E. Speaking Engagements ................................................................................... 22
`
`F. Litigation Support Experience ......................................................................... 25
`
`G. Testifying Experience ...................................................................................... 30
`
`H. Professional Experience .................................................................................. 32
`
`X.
`
`CONTINUING PROFESSIONAL EDUCATION ........................................................... 36
`
`A. References to my work ................................................................................... 37
`1. Media References ......................................................................... 37
`2. References to publications ........................................................... 38
`3. Universities using my books ......................................................... 43
`
`B. Training ........................................................................................................... 45
`
`C. Technical Skills ................................................................................................ 46
`
`
`
`
`
`
`
`
`2
`
`

`

`
`
`I.
`
`INTRODUCTION
`
`1.
`
`I have been retained by Uniloc to provide my expert opinions regarding
`
`validity of U.S. Patent No. U.S. Patent No. 7,653,508 (“508 Patent”). Specifically, I have
`
`been asked to provide expert opinions regarding Claim 5. The ‘508 patent was granted
`
`January 26, 2010 filed December 22, 2006
`
`2.
`
`I am being compensated for my time at my standard consulting rate of
`
`$300 per hour. I am also being reimbursed for expenses that I incur during the course of
`
`this work. My compensation is not contingent upon the results of my study or the
`
`substance of my opinions.
`
`II.
`
`BACKGROUND AND QUALIFICATIONS
`
`3.
`
`I have 25+ years of experience in the computer science industry including
`
`extensive experience with computer security, computer programming, and computer
`
`networking. I have authored 26 computer science books, including textbooks used at
`
`universities around the world. I hold 42 different computer industry certifications,
`
`including many in networking subjects. I am experienced with multiple programming
`
`languages. I also have extensive experience in computer networking. I have extensive
`
`experience with mobile devices, including all aspects of mobile devices (hardware and
`
`software). I am a Distinguished Speaker for the Association of Computing Machinery
`
`(ACM), and a reviewer for the IEEE Security and Privacy journal, as well as a reviewer for
`
`the International Journal of Cyber Warfare and Terrorism (IJCWT). My CV is attached as
`
`appendix A.
`
`
`
`3
`
`

`

`
`
`III.
`
`THE ‘902 PATENT
`
`1.
`
`The '902 patent was issued on February 1, 2011. The '902 patent is a
`
`continuation of application No. 11/644,455 ，filed on Dec. 22, 2006. The '902 patent is
`
`about monitoring human activity. The '902 invention uses sensors with a dominant axis.
`
`To quote the patent itself "This invention relates to a method of monitoring human
`
`activity, and more particularly to counting periodic human motions such as steps.".
`
`2.
`
`The inventors of the ’902 patent observed that at the time, step counting
`
`devices that utilize an inertial sensor to measure motion to detect steps generally
`
`required the user to first position the device in a limited set of orientations. In some
`
`devices, the required orientations are dictated to the user by the device. In other devices,
`
`the beginning orientation is not critical, so long as this orientation can be maintained.
`
`EX1001, 1:23-30. Further, the inventors observed that devices at the time were often
`
`confused by motion noise experienced by the device throughout a user's daily routine.
`
`The noise would cause false steps to be measured and actual steps to be missed in
`
`conventional step counting devices. Conventional step counting devices also failed to
`
`accurately measure steps for individuals who walk at a slow pace. Id., 1:31-38.
`
`3.
`
`According to the invention of the ’902 Patent, a device to monitor human
`
`activity using an inertial sensor assigns a dominant axis after determining the orientation
`
`of an inertial sensor. he orientation of the inertial sensor is continuously determined, and
`
`the dominant axis is updated as the orientation of the inertial sensor changes. Id., 2:10-
`
`17.
`
`
`
`4
`
`

`

`
`
`IV.
`
`CLAIM CONSTRUCTION
`
`4.
`
`Fort the purposes of an IPR, claim terms are given their broadest
`
`reasonable meaning. No claim construction is given at this time.
`
`V.
`
`ONE OF ORDINARY SKILL IN THE ART
`
`5.
`
`Patent claims must be viewed from the perspective of one of ordinary skill
`
`in the art. A Person of Ordinary Skill in the Art (POSA) in December 2006 would have been
`
`one with a bachelor’s degree in engineering, computer science, or related technical area
`
`with 2 years of experience related to accelerometers or similar devices. Additional
`
`experience can compensate for a lack of a degree.
`
`6.
`
`I am aware that the petitioner and Dr. Paradiso have a slightly different
`
`view of the level of skill of a person of ordinary skill in the art. However, our differences
`
`are relatively minor. Even if one accepts the petitioners view of one of ordinary skill in the
`
`art, it would not change my opinions.
`
`VI.
`
`GENERAL ISSUES
`
`A.
`
`7.
`
`Motivation to Combine
`
`Throughout the petitioners IPR as well as in specific sections, the petitioner
`
`states that one of ordinary skill in the art would have been motivated to combine Fabio and
`
`Pasolini. They petitioner states the two patents are in the same general field. I agree with
`
`that statement. However, the petitioner does not explicitly identify a deficiency in one that
`
`is overcome by the other.
`
`8.
`
`In one instance the petitioner comes close to identifying a deficiency in
`
`one that is overcome by the other, stating “POSITA would have thus recognized that
`
`
`
`5
`
`

`

`
`
`Pasolini offers more specific teachings about improved step detection that would be
`
`beneficially implemented into Fabio’s device.” It should be noted that Pasolini was filed
`
`Oct. 2, 2006 and granted Dec. 9, 2008. Fabio was filed Oct. 2, 2006 and granted Apr.13,
`
`2010. Pasolini was filed the same day as Fabio. This is relevant because both Fabio and
`
`Pasolini are from the same inventors (despite the labels the petitioner has assigned). The
`
`petitioner filed both on the same day yet did not feel one needed to be combined with
`
`the other to overcome any deficiency. Clearly the inventors of Fabio and Pasolini did not
`
`feel that Fabio required the ‘improved step detection’ of Pasolini. This specific instance
`
`applies throughout the Petition.
`
`9.
`
`The petitioner also claims “A POSITA would have also combined Tsuji with
`
`Fabio and Pasolini because using Tsuji’s known technique of detecting a user’s step based
`
`on a moving average of the most recent walk cycles (i.e., stepping periods)”. However,
`
`the petitioner does not state what deficiency in Fabio or Pasolini is being corrected by this
`
`‘moving average of the most recent walk cycles’.
`
`10.
`
`The petitioner also claims “A POSITA would have found it obvious to
`
`combine Fabio, Pasolini, and Tsuji because, as described below, the combination is merely
`
`a simple substitution of one known element for another to obtain predictable results.”
`
`But then in the next paragraphs the petitioner describes first taking Pasolini's axis with
`
`Fabio’s pedometer and then further combining Tsuji's step process.
`
`11.
`
`The first problem with this claim is that the petitioner provides no
`
`explanation of why a POSITA would combine Fabio’s pedometer with Pasolini. This
`
`particularly important because Pasolini already is a pedometer. In fact, Pasolini is entitled
`
`
`
`6
`
`

`

`
`
`“Pedometer device and step detection method using an algorithm for self-adaptive
`
`computation of acceleration thresholds.” The petitioner fails to explain why POSITA
`
`would need to combine Fabio’s pedometer with Pasolini, since Pasolini already is itself a
`
`pedometer. In fact, a POSITA would not be motivated to combine Pasolini and Fabio's
`
`pedometer since both already have a pedometer.
`
`12.
`
`The second problem with the petitioner’s claim is the combining of Tsuji’s
`
`step counting process. Fabio and Pasolini both already have a step counter. For example,
`
`Pasolini, in the abstract describes “In a pedometer device for detecting and counting steps
`
`of a user on foot...”. Fabio states “A method for controlling a pedometer includes the
`
`steps of: generating a signal correlated to movements of a user of the pedometer.” The
`
`petitioner fails to explain why a POSITA would want to add a step counter to Pasolini or
`
`Fabio when both already have step counters. In fact, a POSITA would not be motivated to
`
`combine Fabio, Pasolini, and or Tsuji’s step counting process, since all three already have
`
`step counting processes.
`
`13.
`
`Aside from the fact that a POSITA would not have seen a need to combine
`
`Fabio, Pasolini, and/or Tjsuji, this would not have been a ‘simple substitution.’ The first
`
`issue is combining Pasolini and Fabio’s pedometer. Both devices are in fact pedometers.
`
`To combine the two different pedometers, would require extensive re-working of both
`
`inventions. Then to add in Tsuji’s step counting, when Fabio and Pasolini each already
`
`have their own step-counting would have required significant re-work. The petitioner
`
`points to core functionality for each of the three prior art references, then claims it would
`
`be ‘simple substitution’ to fundamentally change how each prior art reference
`
`
`
`7
`
`

`

`
`
`accomplishes this core functionality. A POSITA would readily see that this is a very difficult
`
`task requiring undue experimentation.
`
`B.
`
`Cadence Window
`
`14.
`
`Claim 5 recites “when the step count is at or above the step count
`
`threshold, determining a dynamic step cadence window and using the dynamic step
`
`cadence window to identify the time frame within which to monitor for the next step.”
`
`Claim 7 recites “examining previous acceleration data to determine whether any
`
`additional steps would have been counted if the dynamic step cadence window had been
`
`used when the previous acceleration data was received; and.” Claim 8 recites “The
`
`method of claim 5, wherein determining the dynamic step cadence window comprises,”
`
`15.
`
`In the body of the ‘902 patent is further discussion of the cadence Window
`
`including “Referring to FIG. 1, the cadence logic 132 may determine one or more sample
`
`periods to be used by the rolling average logic 135, and may determine a cadence window
`
`150 to be used by the step counting logic 130”
`
`16.
`
`The petitioner states “Thus, for the purposes of this proceeding, the term
`
`“cadence window” as used in the claims includes “a window of time since a last step was
`
`counted that is looked at to detect a new step.” Ex.1003, p.15.”
`
`17.
`
`The petitioner claims Fabio discloses this limitation. However, what Fabio
`
`actually states is shown here (note that portion underlined in red is the portion the
`
`petitioner cited):
`
`
`
`8
`
`

`

`
`
`
`
`18. What is being described is a test of the regularity of the individual step.
`
`This is the first validation test. Even if one supposes that “regularity of the individual step”
`
`to be synonymous with “cadence”, this excerpt is not describing updating the “regularity
`
`of the individual step”. This in no way describes updating anything even analogous to the
`
`cadence window. It must also be noted that Fabio only discusses updating with respect
`
`to updating the number of steps, not anything even analogous to the cadence window.
`
`VII.
`
`SPECIFIC CLAIM ELEMENTS
`
`19.
`
`The petitioner claims that “Claim 8 is obvious under 35 U.S.C. § 103(a)
`
`over Pasolini in view of Fabio, further in view of Tsuji.” I address claim 8 in detail in this
`
`section of my declaration.
`
`
`
`9
`
`

`

`
`
`8.0 The method of claim 5, wherein determining the dynamic step
`A.
`cadence window comprises:”
`
`20.
`
`Nothing in Fabio teaches or even suggests recording a user cadence,
`
`comparing to a user cadence, or similar functionality. Rather Fabio simply determines if
`
`there is too much time between two steps, to zero out the count. This actually teaches
`
`away from the ‘902 cadence window. The petitioner does not actually offer any
`
`arguments in this section of the petition, but rather states” See section [5.0] – [5.4]. As
`
`discussed in [5.4], Fabio discloses determining a dynamic step cadence window.
`
`Ex.1003, p.52.” In that section of the petition, the petitioner claims:
`
`
`
`21.
`
`Then Petitioner adds “Based on this, a POSITA would have understood that
`
`defining the validation interval in this way compensates for changes in each step”.
`
`However, this is not what Fabio is teaching. What Fabio is teaching is looking only at
`
`homogenous durations of steps, with no respect to a ‘dynamic cadence window’. In fact, a
`
`homogeneous duration is the antithesis of a ‘dynamic’ cadence window. In this respect,
`
`Fabio teaches away from the ‘902 patent.
`
`
`
`10
`
`

`

`
`
`8.1 computing a rolling average of stepping periods of previously
`B.
`counted steps; and
`
`22.
`
`The petitioner claims that “Tsuji discloses this limitation because it teaches
`
`that its pedometer computes a moving (i.e., rolling) average of the walk cycle (i.e.,
`
`stepping period) using a predetermined number of previous walk cycles recognized to be
`
`steps. Ex.1003, p.52.”
`
`23. What Tsuji actually discloses is “In addition, the reference cycle calculating
`
`means may include second cycle storing means for successively storing therein data on
`
`cycles of a predetermined number of newest signals each judged to be within the first
`
`reference cycle range by the first cycle judging means, and obtain a moving average of
`
`the cycles of the predetermined number of signals the data on which is stored in the
`
`second cycle storing means.”
`
`24.
`
`Even if one adopts the petitioners claim that a moving average in Tsuji is
`
`the same as the rolling average in the ‘902 patent, what Tsuji is averaging is “cycles of the
`
`predetermined number of signals”, not counted steps.
`
`25.
`
`Furthermore, Tsuji states “In this embodiment mode, Ta±10% (Ta is a
`
`moving average value of the cycles of a newest predetermined number of signals during
`
`a walk outputted from the filter portion 105) is set as the above first reference cycle
`
`range. Then, when the signal from the filter portion 105 is within the first reference cycle
`
`range, the walk cycle comparing portion 106 judges that the cycle of the signal from the
`
`filter portion 105 is similar to the reference walk cycle”
`
`
`
`11
`
`

`

`
`
`26.
`
`These are ‘cycles of the predetermined number of signals’ which are quite
`
`different from the ‘a rolling average of stepping periods of previously counted steps’ of
`
`claim 8 of the ‘902 patent.
`
`8.2 setting the dynamic step cadence window based on the rolling
`C.
`average of stepping periods.
`
`27.
`
`The petitioner states “The combination of Fabio, Pasolini, and Tsuji renders
`
`this limitation obvious. First, as discussed above in [5.4], Fabio teaches determining a
`
`dynamic step cadence window by determining a “validation interval TV” at each step. “As
`
`has already been discussed in this declaration a POSA would not have been motivated to
`
`combine Fabio, Pasolini, nor Tsuji.
`
`28.
`
`Also, as was discussed earlier in this declaration, Fabio does not disclose a
`
`dynamic step cadence window. Rather Fabio simply determines if there is too much time
`
`between two steps, to zero out the count. This actually teaches away from the ‘902
`
`cadence window.
`
`VIII.
`
`CONCLUSIONS
`
`29.
`
`Based on my analysis as well as my extensive experience and training, it is
`
`my opinion that neither Fabio, Pasolini, nor Tsuji alone or in any combination thereof
`
`anticipate or render obvious claim 8 of the ‘902 patent.
`
`30.
`
`Furthermore, it is my opinion that a POSA would not have been motivated
`
`to combine Fabio with Pasolini. Nor would a POSA be motivated to combine Fabio and/or
`
`Pasolini with Tsuji.
`
`
`
`
`
`
`
`12
`
`

`

`
`
`
`
`_______________________
`William C. Easttom II (Chuck Easttom) 15 August 2018
`
`
`
`
`
`
`
`
`IX.
`
`APPENDIX A – EASTTOM CV
`
`A.
`
`Education
`
`1.
`
`University Degrees
`
`• B.A. Southeastern Oklahoma State University. Major Communications with
`Minors in Chemistry and Psychology. Extensive coursework in science (chemistry,
`physics, and biology) as well as neuroscience (neurobiology of memory, cognitive
`science, etc.). Also, additional coursework in computer science including
`programming and database courses.
`• M.Ed. Southeastern Oklahoma State University. Coursework included technology
`related courses such as digital video editing, multimedia presentations, and
`computer graphics. A statistics course was also part of the coursework.
`• M.B.A. Northcentral University major in Applied Computer Science. Extensive
`course work in graduate computer science including graduate courses in: C++
`programming, C# programming, Computer Graphics, Web Programming,
`Network communication, Complex Database Management Systems, and
`Artificial Intelligence. Approximately 30 graduate hours of graduate computer
`science courses. Additionally, a doctoral level statistics course was included. A
`semester research project in medical software was also part of the curriculum. I
`also took several research courses beyond the requirements for the degree.
`• Doctor of Science (In progress) Capitol Technology University. Majoring in
`cybersecurity, dissertation topic is a study of lattice-based cryptography for post-
`quantum computing. Currently all but dissertation (ABD) which is 3/5ths
`complete and due to graduate in April.
`• MSSE Master of Science in Systems Engineering (In progress). University of Texas
`at El Paso. The coursework includes studies in software & system requirements;
`system integration, verification, and validation; system architecture and design;
`and systems modeling & simulation.
`
`
`
`
`
`
`13
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`

`

`
`
`2.
`
`Industry Certifications
`
`The following is a list of computer industry certifications I have earned.
`
`
`
`a.
`
`Hardware and Networking Related Certifications
`
`1. CompTIA (Computer Technology Industry Associations) A+ Certified
`
`2. CompTIA Network + Certified
`
`3. CompTIA Server+ Certified
`
`4. CompTIA I-Net+ Certified
`
`
`
`b.
`
`Operating System Related Certifications
`
`5. CompTIA Linux + Certified
`
`6. Microsoft Certified Professional (MCP) – Windows Server 2000 Professional
`Certification Number: A527-9546
`
`7. Microsoft Certified Systems Administrator (MCSA) Windows Server 2000
`Certification Number: A527-9556
`
`8. Microsoft Certified Systems Engineer (MCSE) Windows Server 2000 Certification
`Number: A527-9552
`
`9. Microsoft Certified Technology Specialist (MCTS) Windows Server 2008 Active
`Directory Microsoft Certification ID: 1483483
`
`10. Microsoft Certified Technology Specialist (MCTS) Windows 7 Microsoft Certification
`ID: 1483483
`
`11. Microsoft Certified IT Professional (MCITP) Windows 7 Microsoft Certification ID:
`1483483
`
`12. Microsoft Certified Solutions Associate Windows 7 Microsoft Certification ID:
`1483483
`
`13. National Computer Science Academy Windows 8 Certification Certificate #: 4787829
`
`
`
`Programming and Web Development Related
`c.
`Certifications
`
`14. Microsoft Certified Professional (MCP) – Visual Basic 6.0 Desktop Applications
`Microsoft Certification ID: 1483483
`
`15. Microsoft Certified Professional (MCP) – Visual Basic 6.0 Distributed Applications
`Microsoft Certification ID: 1483483
`
`16. Microsoft Certified Application Developer (MCAD) - C# Microsoft Certification ID:
`1483483
`
`
`
`14
`
`

`

`
`
`17. Microsoft Certified Trainer (MCT 2005-2012) Microsoft Certification ID: 1483483
`
`18. Microsoft Certified Technology Specialist (MCTS) Visual Studio 2010 Windows
`Application Microsoft Certification ID: 1483483
`
`19. Microsoft Certified Technology Specialist (MCTS) Visual Studio 2010 Data Access
`Microsoft Certification ID: 1483483
`
`20. National Computer Science Academy HTML 5.0 Certification Certificate #: 4788000.
`
`21. National Computer Science Academy ASP.Net Certification Certificate #: 4788342
`
`22. Certified Internet Webmaster (CIW) Associate CIW0163791
`
`
`
`d.
`
`Database Related Certifications
`
`23. Microsoft Certified Database Administrator (MCDBA) SQL Server 2000 Microsoft
`Certification ID: 1483483
`
`24. Microsoft Certified Technology Specialist (MCTS) Implementing SQL Server 2008
`Microsoft Certification ID: 1483483
`
`25. Microsoft Certified IT Professional (MCITP) SQL Server Administration Microsoft
`Certification ID: 1483483
`
`
`
`e.
`
`Security and Forensics Related Certifications
`
`26. CIW Certified Security Analyst CIW0163791
`
`27. EC Council Certified Ethical Hacker v5 (CEH) ECC942445
`
`28. EC Council Certified Hacking Forensics Investigator v4 (CHFI) ECC945708
`
`29. EC Council Certified Security Administrator (ECSA) ECC947248
`
`30. EC Council Certified Encryption Specialist (ECES)
`
`31. EC Council Certified Instructor
`
`32. CISSP – Certified Information Systems Professional #387731
`
`33. ISSAP – Certified Information Systems Architect #387731
`
`34. CCFP – Certified Cyber Forensics Professional #387731
`
`35. Certified Criminal Investigator (CCI) 2015-2017
`
`36. Forensic Examination of CCTV Digital VTR Surveillance Recording Equipment
`
`37. Oxygen Phone Forensics Certified
`
`38. Access Data Certified Examiner (ACE) 2014-2017
`
`39. OSForensics Certified Examiner (OSFCE)
`
`40. Certified Forensic Consultant (CFC) 2015-2017
`
`
`
`15
`
`

`

`
`
`f.
`
`Software Certifications
`
`41. National Computer Science Academy Microsoft Word 2013 Certification Certificate
`#: 5078016
`
`42. National Computer Science Academy Microsoft Word 2000 Certification Certificate
`#: 5078187
`
`
`
`3.
`
`Licenses
`
`Texas State Licensed Private Investigator. Registration Number 827827. Associated with
`Allegiant Investigations & Security License Number: A18596
`
`
`
`
`
`
`
`B.
`
`Publications
`
`1.
`
`Books
`
`Easttom, C. (2003). Moving from Windows to Linux. Newton Center, MA:
`1.
`Charles River Learning. 1st Edition, Charles River Media.
`Easttom, C., Hoff, B. (2006). Moving from Windows to Linux, 2nd Ed.
`2.
`Newton Center, MA: Charles River Learning. 1st Edition, Charles River Media.
`
`Easttom, C. (2003). Programming Fundamentals in C++. Newton Center,
`3.
`MA: Charles River Learning. 1st Edition, Charles River Media.
`
` Easttom C. (2002). JFC and Swing with JBuilder 8.0. Plano, Texas:
`4.
`WordWare Publishing.
`
`Easttom, C. (2002). JBuilder 7.0 EJB Programming. Plano, Texas:
`5.
`WordWare Publishing.
`
`Easttom, C. (2001). Beginning JavaScript, 1st Edition. Plano, Texas:
`6.
`WordWare Publishing.
`
`Easttom, C. (2002). Beginning VB.Net. Plano, Texas: WordWare
`7.
`Publishing.
`Easttom, C. (2001). Advanced JavaScript, 2nd Edition. Plano, Texas:
`8.
`WordWare Publishing.
`
`Easttom, C. (2005). Introduction to Computer Security. New York City,
`9.
`New York: Pearson Press.
`
`Easttom, C. (2006). Network Defense and Countermeasures. New York
`10.
`City, New York: Pearson Press.
`Easttom, C. (2005). Advanced JavaScript, 3rd Edition. Plano, Texas:
`11.
`WordWare Publishing.
`
`16
`
`

`

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`Easttom, C., Taylor, J. (2010). Computer Crime, Investigation, and the
`12.
`Law. Boston, Massachusetts: Cengage Learning.
`
`Easttom, C. (2013). Essential Linux Administration: A Comprehensive
`13.
`Guide for Beginners. Boston, Massachusetts: Cengage Learning.
`Easttom, C. (2011). Introduction to Computer Security, 2nd Edition. New
`14.
`York City, New York: Pearson Press.
`Easttom, C. (2012). Network Defense and Countermeasures, 2nd Edition.
`15.
`New York City, New York: Pearson Press.
`Easttom, C. (2013). System Forensics, Investigation, and Response, 2nd
`16.
`Edition. Burlington Massachusetts: Jones & Bartlett.
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`Easttom, C. (2014). CCFP Certified Cyber Forensics Professional All-in-One
`17.
`Exam Guide. New York City, New York: McGraw-Hill Publishing.
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`Easttom, C., Dulaney, E. (2015). CompTIA Security+ Study Guide: SY0-401.
`18.
`Hoboken, New Jersey: Sybex Press.
`
`Easttom, C. (2015). Modern Cryptography: Applied Mathematics for
`19.
`Encryption and Information Security. New York City, New York: McGraw-Hill
`Publishing.
`Easttom, C. (2016). Computer Security Fundamentals, 3rd Edition. New
`20.
`York City, New York: Pearson Press.
`Easttom, C. (2017). System Forensics, Investigation, and Response, 3rd
`21.
`Edition. Burlington Massachusetts: Jones & Bartlett.
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`Easttom, C., Dulaney, E. (2017). CompTIA Security+ Study Guide: SY0-501.
`22.
`Hoboken, New Jersey: Sybex Press.
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`Easttom, C. (2018). Penetration Testing Fundamentals: A Hands-on Guide
`23.
`to Reliable Security Audits. New York City, New York: Pearson Press.
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`Easttom, C., Christy, R. (2017). CompTIA Security+ Review Guide: SY0-
`24.
`501. Hoboken, New Jersey: Sybex Press.
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`Easttom, C., Roberts, R. (2018). Networking Fundamentals, 3rd Edition.
`25.
`Goodheart-Wilcox Publishing.
`Easttom, C. (2018). Network Defense and Countermeasures, 3rd Edition.
`26.
`New York City, New York: Pearson Press.
`
`2.
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`Papers, presentations, & articles.
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`1. Easttom, C. (2010). RSA and its Challenges. EC Council White Paper.
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`2. Easttom, C. (2010). Finding Large Prime Numbers. EC Council White Paper
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`3. Easttom, C. (2010). A Method for Finding Large Prime Numbers. Haking
`Magazine. Hands-On Cryptography Issue.
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`4. Easttom, C. (2014). A method for finding large prime numbers. Open Source
`Article published by Academia.edu 2014.
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`5. Easttom, C. (2011). The RSA Algorithm - The ups and Downs. CryptoMagazine.
`
`6. Easttom, C. (2011). Feistel Ciphers - An Overview. Presentation at Cast Security
`Conference. Washington, D.C.
`
`7. Easttom, C. (2011). Steganography- History and Modern Applications.
`Presentation at Takedown Security Conference.
`
`8. Easttom, C. (2012). Problems with RSA. Presentation at Takedown Security
`Conference – Dallas, TX.
`
`9. Easttom, C. (2013). Cryptanalysis. Presentation at Takedown Security
`Conference. Huntsville, Alabama.
`
`10. Easttom, C. (2014). An Overview of Cryptographic S-Boxes used in Block Ciphers.
`Research Gate. DOI RG.2.2.14084.94088.
`
`11. Easttom, C. (2014). Cryptographic Backdoors. Presentation at ISC2 Security
`Congress. Atlanta, Georgia.
`
`12. Easttom, C. (2014). Cryptographic Backdoors. Presentation at University of Texas
`Dallas ACM Chapter Conference.
`
`13. Easttom, C. (2014). Windows Registry Forensics. Research Gate. DOI
`RG.2.2.29603.86561
`
`14. Easttom, C. (2014). Artificial Intelligence, Fuzzy Logic, Neural Networks and Fuzzy
`Neural Networks and their impact on Electronic Medical Records. Academia.edu.
`
`15. Easttom, C. (2014). A Basic Overview of Electro-Magnetic Interference.
`Academia.edu.
`
`16. Easttom, C. (2014). An Overview of Targeted Malware. Academia.edu.
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`17. Easttom C. (2014). An Introduction to Mobile Forensics. Academia.edu.
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`18. Easttom, C. (2015). Cryptographic Backdoors. Academia.edu.
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`19. Easttom, C. (2015). The History of Computer Crime in America. Academia.edu.
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`20. Easttom, C. (2015). Spyware Techniques. Academia.edu.
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`21. Easttom, C. (2015). Recovering Deleted Files from NTFS. Academia.edu.
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`22. Easttom, C. (2015). Multi-dimensional analysis of cyber-forensic evidence.
`Academia.edu.
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`23. Easttom, C. (2016). Spyware coding techniques. Journal of Information Security
`Science & Digital Forensics (HJISSDF), 1 (1)
`
`24. Easttom, C. (2016). Cryptographic Backdoors – an introduction. Journal of
`Information Security Science & Digital Forensics (HJISSDF), 1 (1)
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`25. Easttom, C. (2016). A Look at Spyware Techniques. 2600 Magazine, 33(3).
`Autumn issue 2016.
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`26. Easttom, C. (2016). Multi-Dimensional Analysis of Digital Forensic Evidence.
`Forensic Examiner Journal, 25 (4).
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`27. Easttom, C. (2016). Applying Graph Theory to Evidence Evaluation. Research
`Gate DOI: RG.2.2.23391.0528
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`28. Easttom, C. (2017). An Overview of Pseudo Random Number Generators.
`Research Gate. DOI: RG.2.2.13941.58087
`
`29. Easttom, C. (2017). A Model for Penetration Testing. Research Gate. DOI:
`RG.2.2.36221.15844
`
`30. Easttom, C. (2017). The RSA Algorithm Explored. International Journal of
`Innovative Research in Information Security. (IJIRIS). 4(1).
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`31. Easttom, C. (2017). Utilizing Graph Theory to Model Forensic Examination.
`International Journal of Innovative Research in Information Security (IJIRIS), 4(2).
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`32. Easttom, C. (2017). Applying Graph Theory to Modeling Investigations. IOSR
`Journal of Mathematics (IOSR-JM) 13,2 PP 47-51. doi:10.9790/5728-130205475
`
`33. Easttom, C. (2017). Enhancing SQL Injection with Stored Procedures. 2600
`Magazine. 34(3).
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`34. Easttom, C. (2017). An Overview of Key Exchange Protocols. IOSR Journal of
`Mathematics (IOSR-JM). 13(4). DOI: 10.9790/5728-1304021618.
`
`35. Easttom, C. (2017). An Overview of Quantum Cryptography with Lattice Based
`Cryptography. IOSR Journal of Mathematics, 13(6).
`
`36. Easttom, C. (2018). A Generalized Methodology for Designing Non-Linear
`Elements in Symmetric Cryptographic Primitives. In Computing and
`Communication Workshop and Conference (CCWC), 2018 IEEE 8th Annual. IEEE.
`
`37. Easttom, C. (2018). The role of weapon