Introduction to Paper Writing and Poster Presentation

1. Introduction to Paper Writing and Poster Presentation Kemal Akkaya Florida International University kakkaya@fiu.edu REU SITE Talks July 9th, 2015

2. Paper • Scientific document to demonstrate a particular theory/outcome/result • It contains original research results or reviews existing results • transparency and repeatability of the research • Peer-reviewed by experts

3. Components of a Paper • Abstract • Summary of the work (technical parts) • Intro • Background and Motivation of the problem • Description of Solution • Related Work • Comparison of your work done by others • Approach • Technical Stuff • Experiments • Validation of your approach • Conclusion

4. Scientific vs actual method of paper writing

5. Types of papers Technical report Conferences Survey papers (literature review) Journal Book chapter Magazines

6. 1: Every paper tells a story • The story is not what you did, but rather • what you show, new ideas, new insights • why interesting, important? • Why is the story of interest to others? • universal truths, hot topic, surprises or unexpected results? • Know your story! • What is the “elevator pitch” of your story? • Elevator pitch = summary that is short enough to give during an elevator ride

7. 1: Every paper tells a story • Do not think that your idea is silly • You may see someone else publishing the same idea in the near future  • Try writing down your ideas on a piece of paper to see if you can convince yourself  • Do not be "perfectionist", you will never be able to start • Every idea, even weak, can be presented as a paper • The point is how to and where to sell it  • Set a target conference, workshop, journal and go ahead

8. 2. Write top down • Most human beings think this way! • State broad themes/ideas first, then go into detail • context, context, context • Even when going into detail … write top down!

9. 3 Introduction: crucial, formulaic • If reader not excited by intro, paper is lost • Recipe: • para. 1: motivation: broadly, what is problem area, why important? • para. 2: narrow down: what is problem you specifically consider • para. 3: “In the paper, we ….”: most crucial paragraph, tell your elevator pitch • para. 4: how different/better/relates to other work • para. 5: “The remainder of this paper is structured as follows”

10. 4. Master the basics of organized writing • Paragraph = ordered set of topically-related sentences • Lead sentence • sets context for paragraph • might tie to previous paragraph • transition is very important not to lose the reader • Sentences in paragraph should have logical narrative flow, relating to theme/topic • Don’t mix tenses in descriptive text • One sentence paragraph: warning! • Smooth logical flow

11. 5. Put yourself in place of the reader • Less is more: • “I would have sent you less if I had had time” • take the time to write less • Page upon page of dense text is no fun to read • avoid cramped feeling of tiny fonts, small margins • create openness with white space: figures, lists • Readers should not have to work • won’t “dig” to get story, understand context, results • need textual signposts to know where ‘story” is going, context to know where they are • good: “e.g., Having seen that let’s next develop a model for.. Let Z be ..” • bad: “Let Z be ..” • What does reader know/not know, want/not want? • write for reader, not for yourself • no one has as much background/content as you • no one can read your mind • all terms/notation defined?

12. 6. No one (not even your mother) is as interested in this topic as you • So you had better be (or appear) interested • Tell readers why they should be interested in your “story” • Don’t overload reader with 40 graphs: • think about main points you want to convey with graphs • can’t explore entire parameter space • Don’t overload reader with pages of equations • put long derivations/proofs in appendix, provide sketch in body of paper

13. 7. State the results carefully • Clearly state assumptions (see overstate/understate your results) • Experiment/simulation description: enough info to nearly recreate experiment/description • Simulation/measurements: • statistical properties of your results (e.g., confidence intervals) • Are results presented representative? • or just a corner case that makes the point you want to make

14. 8. Don’t overstate/understate your results • Overstatement mistake: • “We show that X is prevalent in the Internet” • “We show that X is better than Y” • when only actually shown for one/small/limited cases • Understatement mistake: fail to consider broader implications of your work • if your result is small, interest will be small • “rock the world”

15. 9. Study the art of writing • Writing well gives you an “unfair advantage” • Writing well matters in getting your work published in top venues • Highly recommended: • The Elements of Style, W. Strunk, E.B. White, Macmillan Publishing, 1979 • Writing for Computer Science: The Art of Effective Communication, Justin Sobel, Springer 1997. • Who do you think are the best writers in your area: study their style

16. 10. Good writing takes times • Give yourself time to reflect, write, review, refine • Give others a chance to read/review and provide feedback • get a reader’s point of view • find a good writer/editor to critique your writing • Starting a paper three days before the deadline, while results are still being generated, is a non-starter

17. Posters • Presentation of your Paper in one page • Should be able to explain in a few sentences • The goal of your work • Your approach • Results • Organization • Need to be presented well for people to read • Less text more figures

18. Privacy-preserving Data Collection on IEEE 802.11s-based Smart Grid AMI Networks PI: Kemal Akkaya Advanced Wireless and Sensor Networking Lab (ADWISE), kemal@cs.siu.edu IEEE 802.11s-based SG AMI Networks Privacy Preserving via Obfuscation • Data Masking - Goal: • To preserve the privacy of the consumer • Give the utility the opportunity to do billing and distribution state estimation • Compared to : • Baseline: no privacy and security • Baseline Sign: authentication only • Baseline Sec: authentication and confidentiality • Multihop network of smart meters • Routing done at MAC layer (Hybrid Wireless Mesh Protocol) • Suitable for AMI applications • Lead Gateway (LG) picks random weights for the basis set at each data collection (e.g., t1) for the obfuscation vector • However, the sum of all weights for a billing period (e.g. t1, t2, t3, ….tn) should sum to 0. • LG encrypts and signs obfuscation value for each smart meter (SM) using Elliptic Curve Cryptography (ECC) Results : The delay in Obfuscation is lower since the SMs send at different time schedule depend on the arrival of obfuscation value while the baselines send at the same time (contention) The PDR of Obfuscation is lower since some SMs do not receive some obfuscation values from the gateway (i.e. the PDR from the gateway to SMs is not 100%), This lead to small goodput. • In each SM, reading + obfuscation value is time-stamped and signed (using ECC), and then send to LG. • LG sends to the utility in clear Challenges Data explosion in Smart Grid (SG) Security, and privacy requirements in SG Summary Data aggregation via homomorphic encryption • Homomorphic Systems - Goal : • Feasibility assessment of Fully Homomorphic Encryption in a real network • Obfuscation method provides end-to-end privacy with no significant overhead and enable the utility company to do billing and state estimation at the same time by using the same reported data. • The network needs to be clustered accordingly based on the needs of the applications. • FHE is feasible for 802.11s-based AMI Networks despite its large message size and processing delay. • Again the network size should be adjusted based on the data collection frequency to ensure collection of all the data on time. • Household activities can be inferred from fined-grained power usage data • Arithmetic operation on encrypted message = addition operation on plaintext • Fully (additionandmultiplication) – Smart-Vercauteren’s FHE (SV-FHE) • Produces relatively small key and ciphertext size • Key generation, bit wise encryption/decryption, bitwise addition/multiplication, recryption operation • Partially (additionormultiplication) – Paillier (PHE) • lower message expansion size. No Aggregation Quinn E. Privacy and the new energy infrastructure. Social Science Research Network (SSRN), February 2009. Possible Solutions • Power data masking : obfuscation of readings • Data aggregation via homomorphic encryption • Partially Homomorphic Encryption • Fully Homomorphic Encryption • Anonymization : disassociation of customer ID and data • Power data reshaping : hiding the actual use Aggregation • References: • Nico Saputro and Kemal Akkaya, "On Preserving User Privacy in Smart Grid Advanced Metering Infrastructure Applications“, Security and Communication Networks Vol 7, Issue 1, January 2014. John Wiley & Sons. • Andrew Beussink et.al, "Preserving consumer privacy on ieee 802.11 s-based smart grid ami networks using data obfuscation“, In Computer Communications Workshops (INFOCOM WKSHPS), 2014 IEEE Conference on, pp. 658-663. IEEE, 2014. *NE-NA = No Encryption – No aggregation approach • Results : • The overhead of FHE is significantly higher then PHE, but the 802.11s-based SG AMI can handle the overhead even when the network scales. • Data aggregation reduces the traffic overhead significantly

19. A Mobile Sensor Network Testbed using iRobots Shadi Janansefat, Izzet F. Senturk, Kemal Akkaya, Micheal Gloff Department of Computer Science Southern Illinois University Carbondale, IL 62901Email: shadi.janan@siu.edu, isenturk@cs.siu.edu, kemal@cs.siu.edu, mgloff@siu.edu, Abstract • The movement command is sent to the iRobot from the IRIS mote: • Turn until calculated angle ω is reached • Drive until calculated distance d is reached Need: Low-cost mobile sensing platform for Wireless Sensor Networks (WSNs) and using it in a real testbed. Our Approach: Designing a mobile sensing device (iRobotSense) by integrating IRIS mote with an iRobot Create, both commercially available and economically efficient. Testing it in a real testbed created at SIU. 3. Mobile WSN Testbed For Connectivity Restoration • Using iRobotSense, a connectivity restoration algorithm named PArtition Detection and Recovery Algorithm (PADRA) [1] is implemented in a 7 node testbed. • Upon partitioning of the network due to failure of a node, the connectivity is restored through cascaded movement of nodes that are dominatee nodes • The moving nodes autonomously made the decision to move to the right locations. 1. Designing The Hardware • Components: • IRIS Mote: A wireless sensor module used in WSNs widely • iRobot Create: An educational development kit that can perform the common drive tasks of a robot • IRIS Interface Board: An interface board with breakout region • HMC6352 Compass Module: A fully integrated compass module, capable of I2C communication • New node is called iRobotSense and costs only $130. 4. Conclusion 2. Robot-Mote Interaction A new mobile sensor called iRobotSense which uses iRobot Create as the mobile platform and an IRIS mote for sensing and communication capabilities is introduced. An MSN testbed which implements and tests PADRA is created to practice the effects of cascaded movement on connectivity issues. • Using nesC, programming the iRobot through serial port of the mote, interfaced by the iRobot • When an iRobotSense needs to move: • It reads the current deviation angle it is facing from the compass via I2C interface • Based on (x, y) of the current location and the destination, the direction it needs to face and distance to the destination (i.e., d) are computed • Given the deviation angle and the moving direction toward the destination, the degrees the iRobotSense should turn before travel is calculated (i.e. ω) Acknowledgment This work is supported by US National Science Foundation under the grant number CNS 1018404. References [1] K. Akkaya et al. “Distributed recovery from network partitioning in movable sensoractor networks via controlled,” in IEEE Transactions on Computers, vol. 59, no. 2, Feb. 2010, pp. 258–271. The 37th IEEE Local Computer Networks (LCN) 2012 Clearwater, Florida, USA

20. Credits J. Kurose, UMass S. Keshav, Waterloo