1. T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering 1 Current Calendar Calendar Index Upcoming Speakers About... Artificial Intelligence Computer Graphics Computer Networking Software Engineering Systems Technical Reports About... Admissions BSCSE BSCIS BACIS CIS Minor Courses Undergrad Advising Honors Program Student Organizations About... Admissions Masters Program PhD Program Joint Programs Fellowships/Financial Aid Courses Graduate Life Student Organizations Faculty Grad Students Undergraduates Administrative Staff Computing Staff Administrative Contacts Directory of Personnel About... CSE Class Schedule CSE Course Description CSE Syllabi OSU Course Description OSU Registrar About... Policies Users Guide Help Desk (SOC) CSE Labs Staff Listing Faculty Positions Diversity Program Current Calendar Calendar Index Upcoming Speakers About... Artificial Intelligence Computer Graphics Computer Networking Software Engineering Systems Technical Reports About... Admissions BSCSE BSCIS BACIS CIS Minor Courses Undergrad Advising Honors Program Student Organizations About... Admissions Masters Program PhD Program Joint Programs Fellowships/Financial Aid Courses Graduate Life Student Organizations Faculty Grad Students Undergraduates Administrative Staff Computing Staff Administrative Contacts Directory of Personnel About... CSE Class Schedule CSE Course Description CSE Syllabi OSU Course Description OSU Registrar About... Policies Users Guide Help Desk (SOC) CSE Labs Staff Listing Faculty Positions Diversity Program Current Calendar Calendar Index Upcoming Speakers About... Artificial Intelligence Computer Graphics Computer Networking Software Engineering Systems Technical Reports About... Admissions BSCSE BSCIS BACIS CIS Minor Courses Undergrad Advising Honors Program Student Organizations About... Admissions Masters Program PhD Program Joint Programs Fellowships/Financial Aid Courses Graduate Life Student Organizations Faculty Grad Students Undergraduates Administrative Staff Computing Staff Administrative Contacts Directory of Personnel About... CSE Class Schedule CSE Course Description CSE Syllabi OSU Course Description OSU Registrar About... Policies Users Guide Help Desk (SOC) CSE Labs Staff Listing Faculty Positions Diversity Program Lifetime Optimization of Sensor Networks under Physical Attacks Xun Wang, Wenjun Gu, Sriram Chellappan, Kurt Schosek, and Dong Xuan Department of Computer Science and Engineering The Ohio State University Xun Wang, Wenjun Gu, Sriram Chellappan, Kurt Schosek, and Dong Xuan Department of Computer Science and Engineering The Ohio State University

2. T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering 2 Outline Physical attacks in sensor networks –Blind physical attacks –Search-based physical attacks Countermeasures to physical attacks –Lifetime optimization of sensor networks under blind physical attacks –Sacrificial node-assisted defense against search-based physical attacks Final remarks & Future work

3. T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering 3 Physical Attacks are Salient Threats Sensor network applications that operate in hostile environments –Volcanic monitoring –Battlefield applications –Anti sensor network forces Physical attacks are inevitable in sensor networks –Simple to launch Small form factor of sensors Unattended and distributed nature of deployment –Can be fatal to sensor networks

4. T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering 4 Physical Attacks (Cont’d) Differ from electronic attacks –Physical vulnerability is exploited by attacker Two phases: –Targeting phase –Destruction phase Two broad types of physical attacks –Blind physical attacks –Search-based physical attacks

5. T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering 5 Blind Physical Attacks Targeting phase –Identifying the sensor network deployment area Destruction phase –Randomly/ blindly selecting attack area –Brute-force physical destruction with bombs/ grenades or tanks/ vehicles –Sensors in the attack area are destroyed Features –Fast –Non-accurate due to blind destruction –Larger causalities to deployment field

6. T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering 6 Search-Based Attacks Targeting phase –Searching for sensors by detecting signals emitted by sensors (passive and active signals) –Isolating an area for each detected sensor Destruction phase –Reaching the isolation area of each detected sensor –Destroying small size sensors through physical destruction methods (like physical force, radiation, hardware/ circuit tampering) Features –Slow –Accurate destruction of only isolated area –Better preserves the deployment field (airports, oil fields, or battlefield). It can be an important agenda for the attacker

7. T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering 7 Countermeasures to Physical Attacks For Blind physical attacks –Optimal sensor deployment to prolong lifetime of sensor networks under blind physical attacks For Search-based physical attacks –Trading short term local coverage for long term global coverage –Adopting Sacrificial Node-Assisted Attack Notification and States Switching to reduce the number of detected/ destroyed sensors

8. T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering 8 Lifetime Optimization of Sensor Networks under Blind Physical Attacks Given a two tier sensor network, a certain number of forwarder nodes (higher tier sensors), 1)Calculate the maximum network effective lifetime and 2)Develop forwarder nodes deployment plan to achieve the maximum network effective lifetime, when the network is subjected to Blind Physical Attacks.

9. T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering 9 Sensor Network Model Tier 1 Tier 2 Radio Transmissions Sensor Nodes Forwarder Nodes Base Station

10. T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering 10 Lifetime Optimization Given a sensor network consisting of n s uniformly distributed sensor nodes that continuously send data to a BS, n f forwarder nodes, initial sensor node energy, e s, initial forwarder node energy, e f, and a data rate from each sensor node, r, determine 1) the maximum lifetime that can be attained by the network; 2) how to geographically deploy the forwarder nodes in the network to forward all alive sensor nodes’ data to the BS while maintaining a minimum throughput C* with a confidence, cf, in the presence of physical attacks.

11. T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering 11 Sensor Nodes Deployment Closer to BS, more dense forwarder nodes Must determine –Total traffic that needs to be forwarded at distance d at time t: –Total number of forwarder nodes at distance d at time t: –Power consumption to forward a bit by a forwarder node at distance d at time t:

12. T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering 12 Sensor Nodes Deployment The power consumption rate for each forwarder node at distance d away from BS under attacks at time t:. Optimal lifetime is the maximum T est Variables,, are based on initial forwarder node density at distance d away from BS,. Obtain the optimal to maximize T est which also meets

13. T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering 13 General Network Extension Extend to general case using polar coordinates

14. T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering 14 Defending Sensor Networks against Search-based Physical Attacks Trade short term local coverage for long term global coverage. Attack Notifications from victim sensors. States Switching of receiver sensors of Attack Notifications to reduce the number of detected sensors. Adopting Sacrificial Nodes (sensors) to improve monitoring of the attacker and to increase the protection areas provided by Attack Notifications.

15. T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering 15 Final Remarks Physical attacks are patent and potent threats to sensor networks. We studied a deployment problem to maximize lifetime objectives under blind physical attacks Viability of future sensor networks is contingent on their ability to resist physical attacks. Our research is an important first step in this regard.

16. T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering 16 Future Work Hybrid Physical Attacks –Two objectives of the attacker: Destroy sensors as fast as possible Preserve the sensor field which is important to the attacker –Search process + flexible destruction method –Brute-force destruction/bombing: faster but larger casualties –Elaborate destruction/sweeping: slower but smaller casualties –Choose destruction method based on the priorities of the two objectives Multiple Attackers –Co-operation between them –Minimizes movement distance of attackers More Intelligent Attackers –Aware of the underlying defense mechanisms Corresponding defenses

17. T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering T H E O H I O S T A T E U N I V E R S I T Y Computer Science and Engineering 17 Q&A Thank You !!!