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Table of Contents

Overview

  • Title: Special Topics on Computer Security
  • Provided by: Dept. of Computer Engineering, Myongji University
  • Lead by: Minho Shin (mhshin@mju.ac.kr, Rm5736)
  • Period: Fall semester, 2022
  • Location: 5441/5701 at 5th Engineering Building
  • Time: Mondays, 12pm to 3pm
  • Type: Graduate Seminar
  • Goal of the class
    • This class aims to familiarize students with current research topics in Computer Security & Privacy area
    • This class also aims to train students with their communication skills including oral presentation, discussion, writing, and collaboration
  • Resources for researchers from Publishing Campus of Elsevier

Participants

# Name Dept Advisor Mobile Phone Email Address
1 Eunseong Kim CE Minkyoung Cho
2 Jimin Son CE Minho Shin
3 Somon CE Sangwon Hyun
4 Suwon Park CE Minho Shin
5 Hoguk Lee CE Minho Shin
6 Soyoung Ji CE Minho Shin

Agenda

Date Name Topic Slides Minutes
9/14 Minho Ice-breaking
9/21 Sam debreach_mitigating_compression_side_channels_via.pdf debreach.pptx
Eun ai_스피커의_보안성_평가_및_대응방안_연구.pdf
slide 		ai_스피커의_보안성_평가_및_대응방안_연구.pptx
9/28 No Class
10/5 No Class
10/12 Jimin 블록체인_기반의_scada.pdf 블록체인_기반의_scada_시스템_보안.pptx
Suwon arp_공격_시그니처_정보에_기반한_스푸핑_공격_탐지_및_차단_모델.pdf spoofing_attack_detection_and_blocking_model.pptx
10/17 3pm Soyoung 웹_기밀성_및_무결성의_보안성_검증_방법.pdf 1.웹기밀성및무결성의보안성검증방법.pptx
Hoguk securing_medical_records_of_covid-19_patients_using_elliptic_curve_digital_-_signature_algorithm_ecdsa_in_blockchain.pdf securing_medical_records.pptx
10/19 Sam htb_a_very_effective_method_to_protect_web_servers.pdf heal_the_breach_abdusamatov_somon_.pptx
Eun ai_사이버보안_체계를_위한_블록체인_기반의.pdf ai_사이버보안_체계를_위한_블록체인_기반의_data-preserviing.pptx
10/26 Jimin 클라이언트_환경에서_보안_소켓_레이어의_트래픽_복호화.pdf 클라이언트_환경에서_보안_소켓_레이어의_트래픽_복호화.pptx
Suwon applsci-12-07655-v2.pdf sgxdump.pptx
10/31 3pm Soyoung 웹모니터링기반암호화웹트래픽공격탐지시스템.pdf 2.웹모니터링기반암호화웹트래픽공격탐지시스템.pptx
Hoguk on_the_security_of_networked_control_systems_in.pdf on_the_security_of_networked_control_systems-in_smart_vehicle_and_its_adaptive_cruise_control.pptx
11/2 Sam privacy-preserving_computing_in_the_blockchain_era.pdf privacy-preserving_in_the_blockchain_era_abdusamatov_somon_.pptx
Eun 자율_운항_선박의_인공지능_잠재적_사이버_위협과_보안.pdf 자율_운항_선박의_인공지능.pptx
11/9 Jimin 자율_주행_자동차_보안_위협_및_기술_동향.pdf 자율_주행_자동차_보안_위협_및_기술_동향.pptx
Suwon 1-s2.0-s0167404821004053-main.pdf automated-analysis-of-malicious-microsoft-office-documents.pptx
11/16 No Class
11/21 3pm Soyoung 3._블록체인_기반의_신뢰적_거래_플랫폼_개발.pdf
Hoguk
11/23 Sam
Eun
11/30 Jimin sdn에서의_보안_시스템_부하_감소_기법.pdf
Suwon
12/7 Soyoung 4._apt_공격_사례_기반_보안_요구사항_추천_프레임워크.pdf
Hoguk
9/21 Zhong Perfectly Privacy-Preserving AI,
A Survey on Collaborative Deep Learning
and Privacy-Preserving 		Privacy-Preserving AI

Class Information

  • Rules for the class
    • We have 15 presentations in total by three students
    • Each present 5 presentations throughout the semester
    • One presentation per day
    • The presenter announces the paper to present at least one week ahead
    • The presenter prepares a powerpoint slides for 30-60min talk
    • The other students submit a review article (1-2 pages) before class
    • The presentation should contain:
      • (Motivation) What are the motivations for this particular problem? What is the backgrounds for understanding the problem? Why is this important?
      • (Problem) What is, on earth, the exact problem the authors aim to address, and why on earth, is the problem important?
      • (Related work) What has been done by other researchers to address the same or similar problem on the table? Why the existing work is not enough to call done?
      • (Method) What is their main methodology to address the problem? How did they actually solve the problem in detail?
      • (Evaluation) What are the evidences for their success found in the paper? What is missing in their evaluation?
      • (Contribution) What is the contribution of the paper and what is not their contributions? Are there any limitations in their result? How would you evaluate the value of the paper?
      • (Future work) What is the remaining problems that were only partially addressed or never covered by the paper? What will be a possible approach to the problem?
    • A review article contains
      • The same content as described for the presenter
      • But in a succinctly written words form
      • Not exceeding two pages
      • Submit in Word/PDF by email
    • Evaluation
      • As a Presenter (10 points each)
        • Slide Quality
        • Talk Quality
        • Knowledge Level
      • As a reviewer (5 points each)
        • Clarity of the review
        • Understanding level

Reading List on Privacy

List: privacy-preserving_ai-2020.4.1.pdf

SAMPLE:

Privacy-preserving for AI applications:

  1. Privacy Preserving in Blockchain based on Partial Homomorphic Encryption System for AI Applications
  2. (Taken by) A Survey on Collaborative Deep Learning and Privacy-Preserving
  3. Membership inference attacks against machine learning models
  4. (Taken by)Privacy-Preserving Deep Learning
  5. Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning
  6. SecureML: A System for Scalable Privacy-Preserving Machine Learning
  7. (Taken by)Privacy-Preserving Scoring of Tree Ensembles: A Novel Framework for AI in Healthcare

Privacy-preserving approach using machine learning:

  1. (Taken by)A hybrid deep learning architecture for privacy-preserving mobile analytics
  2. A machine-learning based approach to privacy-aware information-sharing in mobile social networks
  3. The feasibility of dynamically granted permissions: Aligning mobile privacy with user preferences
  4. Turtle Guard: Helping Android Users Apply Contextual Privacy Preferences
  5. SmarPer: Context-Aware and Automatic Runtime-Permissions for Mobile Devices
  6. ConXsense – Automated Context Classification for Context-Aware Access Control
  7. (Taken by zz)FlowIntent: Detecting Privacy Leakage from User Intention to Network Traffic Mapping
  8. (Taken by)AutoPer: Automatic Recommender for Runtime-Permission in Android Applications
  9. Contextualizing Privacy Decisionsfor Better Prediction (and Protection)
  10. Keeping Context In Mind: Automating Mobile App Access Control with User Interface Inspection
  11. iprivacy: Image privacy protection by identifying sensitive objects via deep multi-task learning

Others:

  1. Crowd-ml: A privacy-preserving learning framework for a crowd of smart devices
  2. Blind Data Classification Using Hyper-Dimensional Convex Polytopes
  3. Deep learning with differential privacy

Reading List Security

Reading List on Blockchain

General

Survey

Blockchain Technology

Blockchain Security & Privacy

Hyperledger (Permissioned Blockchain)

Applications: Security & Privacy

Applications: Medical

Applications: IoT

Applications: Business

Applications: Government

Blockchain Technology and Decentralized Governance: Is the State Still Necessary?

Applications: Smart City

Applications: Energy

Applications: Others

 
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