1. Trusted P2P and Grid Computing: Security Binding, Worm Control, and Reputation Aggregation
Kai Hwang University of Southern California
Technical Presentation at :
Tsinghua University, Beijing, China, Dec. 5, 2005,
November 27, 2018
Kai Hwang at USC

2. Evolution of HPC, Clusters, Distributed P2P/Grid Computing, and Web Services
Distributed Computing
High –Perf. Computing
Disparate Systems
Sharing
Homogeneous
Results in High Performance
P2P
Clusters
Mainly for file sharing
Geographically Sparse
Resource Sharing
Close to each other
Web Services
GRID
Heterogeneous Application Interaction
Within a Framework
No existing framework
November 27, 2018
Kai Hwang at USC

3. Integration of Grid and Web Services
OGSI
GT2
GT1
HTTP
WSDL,
WS-*
WSDL 2,
WSDM
Have been
converging
Started far apart in apps & tech ?
Web
However, despite enthusiasm for OGSI, adoption within Web community turned out to be problematic
November 27, 2018
Kai Hwang at USC

4. P2P Systems, Computational Grids, and P2P Grids
Features
P2P Systems
Grids
P2P Grids
Architecture, Connectivity
Flexible topology, highly scalable, autonomous users
Static configuration with limited scalability
P2P flexibility with Grid resource sharing initiatives
Control and Resource Discovery
Distributed control, client-oriented, free in and out, and self-organizing peers
Centralized control, server or supercomputer-oriented with registered participants
Policy-based control, operating with both P2P and Grid resource management
Security, Privacy, Reliability
Distrusted peers, insecure P2P interactions, and anonymity
Guaranteed trust, more secure with federated users and accountability
Peer-layer reputation system and Grid-layer security infrastructure
Applications and Job Management
General, content delivery, file sharing, download services
Scientific computing, global problem solving, and hierarchical job management
Support desktop, distributed Grid computing, and community services
Represen-tative Systems
Gnutella, Chord (DHT), CAN, Tapestry, etc.
TeraGrid , GriPhyN Grid, LHC Grid , e-Science in UK , Vaga Grid in China
Entropia, P2P Grid, PC Grid , P Grid, Linger Longer
November 27, 2018
Kai Hwang at USC

5. GridSec: A Grid Security Research Project supported National Science Foundation at USC
Steps for automated self-defense at resource site :
Step 1: Intrusion detected by host-based firewall /IDS
Step 2: All VPN gateways are alerted with the intrusions
Step 3: Gateways broadcast response commands to all hosts
VPN Gateway 3
Site S1
Host 1 2
Internet
Site S2
Site S3
From Computer Magazine
November 27, 2018
Kai Hwang at USC

6. Five Related Publications to This Seminar : ( http://GridSec.usc.edu )
K. Hwang, et al, “DHT-based Security Infrastructure for Trusted Internet and Grid Computing” Int’l Journal of Critical Infrastructure, Vol.2, No.4, 2005
S. Song, K. Hwang, and Y.K. Kwok, “ Trusted Grid Computing with Security Binding and Trust Integration”, Journal of Grid Computing, Sept. 2005
M. Cai, K. Hwang, et al, “Fast Internet Worm Containment”, IEEE Security and Privacy, May/June,
R. Zhou and K. Hwang, “Trust-Preserving Overlays for Fast Reputation Aggregation in Scalable P2P Grid Systems “, IEEE Trans. Parallel and Distributed Computing (TPDS), submitted Nov
Y. K. Kwok, S. Song, and K. Hwang, “Selfish Grid Computing: Game Theoretic Modeling and NAS Performance Results”, ACM/IEEE Int’l Conf. on Cluster Computing and The Grids (CCGrid 2005), Cardiff, U.K., May 9-12, 2005
November 27, 2018
Kai Hwang at USC

7. The NetShield Architecture with Distributed Security Enforcement over a DHT Overlay [1]
Serious hackers
November 27, 2018
Kai Hwang at USC

8. Grid Security Issues and Known Solutions
Level
Issues
Solutions
Comments
Host Level
Data Protection
Application Sandboxing
(+) Strong security (-) Application modification
User Space Sandboxing
(+) Easy to implement (-) Security limitations
Kernel Sandboxing
(+) Very strong security (-) Huge complexity
Policy Level Solutions
(+) Easy to implement (-) Static policies
Job Starvation
Advance Reservations
(+) Flexible Mechanism (-) Prior information
Priority Reduction
(+) Simple mechanisms (-) QoS violation
Infra-struc-ture Level
Resource Hacking
Auditing based Solution
(+) Guidelines for a good accounting system (-) Requirements need to be clarified
Policy Mapping
(+) Flexible policies/rights at VO level. (-) Plug-ins at resource end for authorization
Resource Level
(+) Authorization needed (-) Not for a VO
Denial-of-Service
Preventive
(+) Simple implementation (-) Static and cannot detect new attacks
Reactive
(+) Can detect attackers (-) Can be used as a DoS attack tool
Informa-tion Security
Secure Communication
(+) Digital signatures and SSL/TLS used.
Authentication
(+) Uses PKI services (-) No provisions for enhancement.
Single Sign On
(+) No need for repetitive authentication (-) CA’s known to all hosts.
Domain Level
Policy
Policy Management
Still in research
Security
Credential Management
November 27, 2018
Kai Hwang at USC

9. Trusted Grid Job Scheduling [2]
Secure mapping of user jobs onto the Grid sites — the job security demand (SD) and the site trust index (TI) are attributed to many security measures and trust parameters
A practical Grid job scheduler should be risk-resilient by considering SD and TI when mapping jobs to sites
Trust Index of resource sites:
Site reputation, prior job success rate, firewalls, intrusion detection, attack history, false alarms, system vulnerability, crypto library, security update frequency, etc.
Security Demand of user jobs:
Job sensitivity, peer authentication, encrypted messaging, access control, data integrity, user requirements, job application environment, etc.
User jobs demanding security assurance
Grid resource sites with trust levels assessed by peers
Job
Scheduler
This slides shows that user jobs can demand various kinds of security assurances. For example, they may need encrypted massage …. Similarly, the trust index of Grid sites are also determined by many parameters.
Our fuzzy inference approach can aggregate these many parameters to a single scalar quantity that can be used by the job scheduler. In the next, I will show you that the a practical job scheduler should be risk resilient by considering the job security demand and site trust indices.
November 27, 2018
Kai Hwang at USC

10. Security Binding in Grids [2]
Evaluating site trust index using a fuzzy-logic based trust model
Fuzzy trust aggregation at the intra-site and inter-site levels
Feedback loop for dynamic security upgrading
Matching with Job Security demand and Optimized Job Mapping
Site Trust Index
Intersite
aggregation
Defense Capability
Site
Reputation
Intrasite
aggregation
IDS related
Capabilities
Anti-Virus Capabilities
Firewall
Secure Job Execution
Prior Job Execution Success Rate
Cumulative Site Utilization
Job Turnaround Time
Job Slowdown Ratio
November 27, 2018
Kai Hwang at USC

11. Trust Integration over a DHT Overlay
Cooperating gateways working together
to establish VPN tunnels for trust integration
Physical backbone
DHT Overlay Ring
Trust Vector
Trust vector propagation
User application and SeGO server negotiation V
SeGO Server
Hosts
VPN
Gateway
Site S3
Site S2
Site S1
Site S4
From Computer Magazine
November 27, 2018
Kai Hwang at USC

12. Risk-Resilient Scheduling Algorithms
Policy
Heuristic Algorithms
Genetic Algorithms
Risky
Risky-Heuristic: Jobs are scheduled based on a heuristic algorithm without considering any risk factors.
Risky-STGA: Jobs are scheduled based on space-time genetic algorithm without considering any risk factors.
Preemptive
P-Heuristic: The job is scheduled to a site that can be preempted due to insecure conditions. Resubmit the failed jobs to other available sites.
P-STGA: Job is scheduled based on STGA that allows preemption under insecure conditions. Resubmit the failed jobs to other available sites.
Replication
R-Heuristic: Replicated jobs may be dispatched to multiple sites to prevent from possible job failures.
R-STGA: STGA that allows replicated jobs may be dispatched to multiple sites to prevent from possible job failures.
Delay-tolerant
DT-Heuristic: When a failure is observed, the scheduler allows job to be delayed for a preset period of time before rescheduling the job.
DT-STGA: STGA that allows job be delayed for a preset period of time before rescheduling the job.
November 27, 2018
Kai Hwang at USC

13. Performance Metrics for Trusted Grid Computing [2]
Serious hackers
Effects of Trust Integration
November 27, 2018
Kai Hwang at USC

14. Trusted Grid Job Scheduling : Simulated NAS Benchmark Results [2]
Makespan, NAS workload
November 27, 2018
Kai Hwang at USC

15. Grid Utilization and Job Failure Rate
NAS workload with 16,000 jobs over 12 Grid sites [2]
Job Failure rate
Grid Utilization
November 27, 2018
Kai Hwang at USC

16. Major Worm Outbreaks in Recent Years
Name
Vulnerability
Infected Hosts
Protocol
Aug. 2001
CodeRed
MS IIS
≈ 360K
TCP
Jan. 2003
Slammer
MS-SQL
≈ 75K, 90% of Internet scanned in 10 mins
404-byte UDP
Mar. 2004
Witty
ISS firewalls
≈ 12K
UDP
November 27, 2018
Kai Hwang at USC

17. Nimda, CodeRed, Slammer, Blaster, etc.
CodeRed affected 360, web servers in 16 hours
Slammer was the fastest worm at large - it scanned % of the Internet in less than 10 minutes.
November 27, 2018
Kai Hwang at USC

18. WormShield Built with a DHT-based Overlay with Six Worm Monitors [3]
Serious hackers
November 27, 2018
Kai Hwang at USC

19. Effects of Global Prevalence Threshold [3]
Collaborative monitors detect signatures about 10 times faster than using independent monitors [2]
November 27, 2018
Kai Hwang at USC

20. Collaborative Worm Detection Results [3]
About 27 times reduction of infected hosts as 1% of vulnerable edge networks monitored
November 27, 2018
Kai Hwang at USC

21. Further Research on Worm and Epidemic Control :
Combine both network-based and host-based signature generation
Benchmark the performance of different signature generation systems using the same metrics and worm spreading experiments
Distributed signature generation for polymorphic worms
Sequential pattern mining for generating polymorphic worm signatures
November 27, 2018
Kai Hwang at USC

22. DETER Testbed for Internet Simulation
DETER Testbed built at USC/ISI and UC Berkeley, funded by the US NSF and DHS
November 27, 2018
Kai Hwang at USC

23. Research Frontiers of Structured P2P Systems and P2P Grids:
Fast routing algorithms for DHT systems, support data locality, load balancing for non-uniform data distribution, and optimal scheme
Scalable reputation systems for supporting P2P and Grid applications : Fuzzy trust inference and PowerTrust for global reputation aggregation
P2P Grid technology becomes one of the the most promising technology to be integrated with scalable web services for Internet commerce, distance educations, distributed supercomputing, and digital government applications
November 27, 2018
Kai Hwang at USC

24. PowerTrust for Scalable P2P Grid Computing [4]
Nodes represent the peers and directed edges are labeled with local trust scores. The global reputation is aggregated from scores on incoming edges.
Key attribute as the feedback distribution in the TON plays a key role in P2P reputation system design.
November 27, 2018
Kai Hwang at USC

25. Power-Law Distribution of Peer Feedbacks [4]
Driven by two fundamental factors:
Dynamic growth: network expands with newly added nodes
Preferential attachment: new node interacts selectively with existing reputable nodes
Backed up by e-Bay transaction trace data and proven applicable to any dynamic P2P systems
A scalable P2P reputation system: PowerTrust
Leverages on the power-law properties
A new lookahead random walk for system construction
Distributed ranking mechanism for fast aggregation
November 27, 2018
Kai Hwang at USC

26. Success Rate in Distributed P2P File Sharing
After ten rounds of global reputation aggregation [4]
November 27, 2018
Kai Hwang at USC

27. PSA Benchmark Results of 4 Reputation Systems for P2P Grid Computing [4]
November 27, 2018
Kai Hwang at USC

28. Game-Theoretic Solution to the Selfish Grid Computing Problem [5]
Game theory is intended to provide a theory of strategic behavior when all parties in the game interact directly, rather than through the third party, and with the goal to maximize all the individual benefits.
UCLA
What is benefit if I accept jobs from UCLA?
Accept jobs from UCLA or USC?
USC, benefit more, then USC
A Sequence of Rounds: Define how players mutate strategies across round, assuming all players try to maximize their payoffs by tending towards those strategies with highest observed return in previous rounds
USC
UCSD
November 27, 2018
Kai Hwang at USC

29. Game-Theoretical Modeling of Grids
Inter-domain Game
— combine reputation based and game theoretical approaches
Internet and Grid
Computing Lab.
USC ISD
Grids
Grid
Computing Lab
HPC CS
SDSC
ISI
Intra-domain Game
Resource
Registry
Tr. 1
Tr. 2 …
Tr. M
USC
UCLA
UCSD
Utility = f (trust)
November 27, 2018
Kai Hwang at USC

30. Final Remarks :
The NetShield built with DHT-based security overlay networks support distributed intrusion and anomaly detection, alert correlation, collaborative worm and DDoS defense
Extensive benchmark experiments on the DETER testbed will prove the effectiveness, still a long way to achieve assurance.
Fuzzy trust model is effective to support distributed security enforcement in both computational Grids and P2P systems.
Game-theoretic approach provides a viable solution to the selfish and non-cooperative problems in real-life Grids
November 27, 2018
Kai Hwang at USC