Browsing by Author "Channakeshava, Karthik"
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- High performance, scalable, and expressive modeling environment to study mobile malware in large dynamic networksChannakeshava, Karthik (Virginia Tech, 2010-10-14)Advances in computing and communication technologies are blurring the distinction between today's PCs and mobile phones. With expected smart phones sales to skyrocket, lack of awareness regarding securing them, and access to personal and proprietary information, has resulted in the recent surge of mobile malware. In addition to using traditional social-engineering techniques such as email and file-sharing, malware unique to Bluetooth, Short Messaging Service (SMS) and Multimedia Messaging Service (MMS) messages are being used. Large scale simulations of malware on wireless networks have becomes important and studying them under realistic device deployments is important to obtain deep insights into their dynamics and devise ways to control them. In this dissertation, we present EpiNet: an individual-based scalable high-performance oriented modeling environment for simulating the spread of mobile malware over large, dynamic networks. EpiNet can be used to undertake comprehensive studies during both planning and response phase of a malware epidemic in present and future generation wireless networks. Scalability is an important design consideration and the current EpiNet implementation can scale to 3-5 million device networks and case studies show that large factorial designs on million device networks can be executed within a day on 100 node clusters. Beyond compute time, EpiNet has been designed for analysts to easily represent a range of interventions and evaluating their efficacy. The results indicate that Bluetooth malware with very low initial infection size will not result in a major wireless epidemic. The dynamics are dependent on the network structure and, activity-based mobility models or their variations can yield realistic spread dynamics. Early detection of the malware is extremely important in controlling the spread. Non-adaptive response strategies using static graph measures such as degree and betweenness are not effective. Device-based detection mechanisms provide a much better means to control the spread and only effective when detection occurs early on. Automatic signature generation can help in detecting newer strains of the malware and signature distributions through a central server results in better control of the spread. Centralized dissemination of patches are required to reach a large proportion of devices to be effective in slowing the spread. Non-adaptive dynamic graph measures such as vulnerability are found to be more effective. Our studies of SMS and hybrid malware show that SMS-only malware spread slightly faster than Bluetooth-only malware and do not spread to all devices. Hybrid malware spread orders of magnitude faster than either SMS-only or Bluetooth-only malware and can cause significant damage. Bluetooth-only malware spread faster than SMS-only malware in cases where density of devices in the proximity of an infected device is higher. Hybrid malware can be much more damaging than Bluetooth-only or SMS-only malware and we need mechanisms that can prevent such an outbreak. EpiNet provide a means to propose, implement and evaluate the response mechanisms in realistic and safe settings.
- Human Initiated Cascading Failures in Societal InfrastructuresBarrett, Christopher L.; Channakeshava, Karthik; Huang, Fei; Marathe, Achla; Marathe, Madhav V.; Pei, Guanhong; Saha, Sudip; Vullikanti, Anil Kumar S.; Kim, Junwhan; Subbiah, Balaaji S. P. (Public Library of Science, 2012-10-31)In this paper, we conduct a systematic study of human-initiated cascading failures in three critical inter-dependent societal infrastructures due to behavioral adaptations in response to a crisis. We focus on three closely coupled socio-technical networks here: (i) cellular and mesh networks, (ii) transportation networks and (iii) mobile call networks. In crises, changes in individual behaviors lead to altered travel, activity and calling patterns, which influence the transport network and the loads on wireless networks. The interaction between these systems and their co-evolution poses significant technical challenges for representing and reasoning about these systems. In contrast to system dynamics models for studying these interacting infrastructures, we develop interaction-based models in which individuals and infrastructure elements are represented in detail and are placed in a common geographic coordinate system. Using the detailed representation, we study the impact of a chemical plume that has been released in a densely populated urban region. Authorities order evacuation of the affected area, and this leads to individual behavioral adaptation wherein individuals drop their scheduled activities and drive to home or pre-specified evacuation shelters as appropriate. They also revise their calling behavior to communicate and coordinate among family members. These two behavioral adaptations cause flash-congestion in the urban transport network and the wireless network. The problem is exacerbated with a few, already occurring, road closures. We analyze how extended periods of unanticipated road congestion can result in failure of infrastructures, starting with the servicing base stations in the congested area. A sensitivity analysis on the compliance rate of evacuees shows non-intuitive effect on the spatial distribution of people and on the loading of the base stations. For example, an evacuation compliance rate of 70% results in higher number of overloaded base stations than the evacuation compliance rate of 90%.
- Utility Accrual Real-time Channel Establishment in Multi-hop NetworksChannakeshava, Karthik (Virginia Tech, 2004-03-04)Real-time channels are established between a source and a destination to guarantee in-time delivery of real-time messages in multi-hop networks. In this thesis, we propose two schemes to establish real-time channels for soft real-time applications whose timeliness properties are characterized using Jensen's Time Utility Functions (TUFs) that are non-increasing. The two algorithms are (1) Localized Decision for Utility accrual Channel Establishment (LocDUCE) and (2) Global Decision for Utility accrual Channel Establishment (GloDUCE). Since finding a feasible path optimizing multiple constraints is an NP-Complete problem, these schemes heuristically attempt to maximize the system-wide accrued utility. The channel establishment algorithms assume the existence of a utility-aware packet scheduling algorithm at the interfaces. The route selection is based on delay estimation performed at the source, destination, and all routers in the path, from source to destination. We simulate the algorithms, measure and compare their performance with open shortest path first (OSPF). Our simulation experiments show that for most of the cases considered LocDUCE and GloDUCE perform better than OSPF. We also implement the schemes in a proof-of-concept style routing module and measure the performance of the schemes and compare them to OSPF. Our experiments on the implementation follow the same trend as the simulation study and show that LocDUCE and GloDUCE have a distinct advantage over OSPF and accrue higher system-wide utility. These schemes also react better to variation in the loading of the links. Among the two proposed approaches, we observe that GloDUCE performs better than LocDUCE under conditions of increased downstream link loads.