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Title: Signal processing and machine learning approaches to enabling advanced sensing and networking capabilities in everyday infrastructure and electronics
Creator: Ali, Kamran (Scientist)
Date: 2020
Collection: Electronic Theses & Dissertations
Description: Mainstream commercial off-the-shelf (COTS) electronic devices of daily use are usually designed and manufactured to serve a very specific purpose. For example, the WiFi routers and network interface cards (NICs) are designed for high speed wireless communication, RFID readers and tags are designed to identify and track items in supply chain, and smartphone vibrator motors are designed to provide haptic feedback (e.g. notifications in silent mode) to the users. This dissertation focuses on...
Show moreMainstream commercial off-the-shelf (COTS) electronic devices of daily use are usually designed and manufactured to serve a very specific purpose. For example, the WiFi routers and network interface cards (NICs) are designed for high speed wireless communication, RFID readers and tags are designed to identify and track items in supply chain, and smartphone vibrator motors are designed to provide haptic feedback (e.g. notifications in silent mode) to the users. This dissertation focuses on revisiting the physical-layer of various such everyday COTS electronic devices, either to leverage the signals obtained from their physical layers to develop novel sensing applications, or to modify/improve their PHY/MAC layer protocols to enable even more useful deployment scenarios and networking applications - while keeping their original purpose intact - by introducing mere software/firmware level changes and completely avoiding any hardware level changes. Adding such new usefulness and functionalities to existing everyday infrastructure and electronics has advantages both in terms of cost and convenience of use/deployment, as those devices (and their protocols) are already mainstream, easily available, and often already purchased and in use/deployed to serve their mainstream purpose of use.In our works on WiFi signals based sensing, we propose signal processing and machine learning approaches to enable fine-grained gesture recognition and sleep monitoring using COTS WiFi devices. In our work on gesture recognition, we show for the first time thatWiFi signals can be used to recognize small gestures with high accuracy. In our work on sleep monitoring, we propose for the first time aWiFi CSI based sleep quality monitoring scheme which can robustly track breathing and body/limb activity related vital signs during sleep throughout a night in an individual and environment independent manner.In our work on RFID signals based sensing, we propose signal processing and machine learning approaches to effectively image customer activity in front of display items in places such as retail stores using commercial off-the-shelf (COTS) monostatic RFID devices (i.e. which use a single antenna at a time for both transmitting and receiving RFID signals to and from the tags). The key novelty of this work is on achieving multi-person activity tracking in front of display items by constructing coarse grained images via robust, analytical model-driven deep learning based, RFID imaging. We implemented our scheme using a COTS RFID reader and tags.In our work on smartphone's vibration based sensing, we propose a robust and practical vibration based sensing scheme that works with smartphones with different hardware, can extract fine-grained vibration signatures of different surfaces, and is robust to environmental noise and hardware based irregularities. A useful application of this sensing is symbolic localization/tagging, e.g. figuring out whether a user's device is in their hand, pocket, or at their bedroom table, etc. Such symbolic tagging of locations can provide us with indirect information about user activities and intentions without any dedicated infrastructure, based on which we can enable useful services such as context aware notifications/alarms. To make our scheme easily scalable and compatible with COTS smartphones, we design our signal processing and machine learning pipeline such that it relies only on builtin vibration motors and microphone for sensing, and it is robust to hardware irregularities and background environmental noises. We tested our scheme on two different Android smartphones.In our work on powerline communications (PLCs), we propose a distributed spectrum sharing scheme for enterprise level PLC mesh networks. This work is a major step towards using existing COTS PLC devices to connect different types of Internet of Things (IoT) devices for sensing and control related applications in large campuses such as enterprises. Our work is based on identification of a key weakness of the existing HomePlug AV (HPAV) PLC protocol that it does not support spectrum sharing, i.e., currently each link operates over the whole available spectrum, and therefore, only one link can operate at a time. Our proposed spectrum sharing scheme significantly boosts both aggregated and per-link throughputs, by allowing multiple links to communicate concurrently, while requiring a few modifications to the existing HPAV protocol.
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Title: Network reachability : quantification, verification, troubleshooting, and optimization
Creator: Khakpour, Amir Reza
Date: 2012
Collection: Electronic Theses & Dissertations
Description: Quantifying, verifying, troubleshooting, and optimizing the network reachability is essential for network management and network security monitoring as well as various aspects of network auditing, maintenance, and design. Although attempts to model network reachability have been made, feasible solutions for computing, maintaining and optimally designing network reachability have remained unknown. Network reachability control is very critical because, on one hand, reachability errors can cause...
Show moreQuantifying, verifying, troubleshooting, and optimizing the network reachability is essential for network management and network security monitoring as well as various aspects of network auditing, maintenance, and design. Although attempts to model network reachability have been made, feasible solutions for computing, maintaining and optimally designing network reachability have remained unknown. Network reachability control is very critical because, on one hand, reachability errors can cause network security breaches or service outages, leading to millions of dollars of revenue loss for an enterprise network. On the other hand, network operators suffer from lack of tools that thoroughly examine network access control configurations and audit them to avoid such errors. Besides, finding reachability errors is by no means easy. The access control rules, by which network reachability is restricted, are often very complex and manually troubleshooting them is extremely difficult. Hence, having a tool that finds the reachability errors and fix them automatically can be very useful. Furthermore, flawed network reachability design and deployment can degrade the network performance significantly. Thus, it is crucial to have a tool that designs the network configurations such that they have the least performance impact on the enterprise network.In this dissertation, we first present a network reachability model that considers connectionless and connection-oriented transport protocols, stateless and stateful routers/firewalls, static and dynamic NAT, PAT, IP tunneling, etc. We then propose a suite of algorithms for quantifying reachability based on network configurations (mainly access control lists (ACLs)) as well as solutions for querying network reachability. We further extend our algorithms and data structures for detecting reachability errors, pinpointing faulty access control lists, and fixing them automatically and efficiently. Finally, we propose algorithms to place rules on network devices optimally so that they satisfy the networks central access policies. To this end, we define correctness and performance criteria for rule placement and in turn propose cost-based algorithms with adjustable parameters (for the network operators) to place rules such that the correctness and performance criteria are satisfied.We implemented the algorithms in our network reachability tool called Quarnet and conducted experiments on a university network. Experimental results show that the offline computation of reachability matrices takes a few hours and the online processing of a reachability query takes 75 milliseconds on average. We also examine our reachability error detection and correction algorithms on a few real-life networks to examine their performance and ensure that Quarnet is efficient enough to be practically useful. The results indicate that we can find reachability errors in order of minutes and fix them in order of seconds depending on the size of network and number of ACLs. Finally, we added the rule placement suite of algorithms to Quarnet, which can design a network ACL in based on the network central policies in order of tens of minutes for an enterprise network. We compare it with Purdue ACL placement, the state-of-the-art access policy design technique, and explain its pros and cons.
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Title: Hardware algorithms for high-speed packet processing
Creator: Norige, Eric
Date: 2017
Collection: Electronic Theses & Dissertations
Description: The networking industry is facing enormous challenges of scaling devices to support theexponential growth of internet traffic as well as increasing number of features being implemented inside the network. Algorithmic hardware improvements to networking componentshave largely been neglected due to the ease of leveraging increased clock frequency and compute power and the risks of implementing complex hardware designs. As clock frequencyslows its growth, algorithmic solutions become important...
Show moreThe networking industry is facing enormous challenges of scaling devices to support theexponential growth of internet traffic as well as increasing number of features being implemented inside the network. Algorithmic hardware improvements to networking componentshave largely been neglected due to the ease of leveraging increased clock frequency and compute power and the risks of implementing complex hardware designs. As clock frequencyslows its growth, algorithmic solutions become important to fill the gap between currentgeneration capability and next generation requirements. This paper presents algorithmicsolutions to networking problems in three domains: Deep Packet Inspection(DPI), firewall(and other) ruleset compression and non-cryptographic hashing. The improvements in DPIare two-pronged: first in the area of application-level protocol field extraction, which allowssecurity devices to precisely identify packet fields for targeted validity checks. By usingcounting automata, we achieve precise parsing of non-regular protocols with small, constantper-flow memory requirements, extracting at rates of up to 30gbps on real traffic in softwarewhile using only 112 bytes of state per flow. The second DPI improvement is on the longstanding regular expression matching problem, where we complete the HFA solution to theDFA state explosion problem with efficient construction algorithms and optimized memorylayout for hardware or software implementation. These methods construct automata toocomplex to be constructed by previous methods in seconds, while being capable of 29gbpsthroughput with an ASIC implementation. Firewall ruleset compression enables more firewall entries to be stored in a fixed capacity pattern matching engine, and can also be usedto reorganize a firewall specification for higher performance software matching. A novelrecursive structure called TUF is given to unify the best known solutions to this problemand suggest future avenues of attack. These algorithms, with little tuning, achieve a 13.7%improvement in compression on large, real-life classifiers, and can achieve the same results asexisting algorithms while running 20 times faster. Finally, non-cryptographic hash functionscan be used for anything from hash tables to track network flows to packet sampling fortraffic characterization. We give a novel approach to generating hardware hash functionsin between the extremes of expensive cryptographic hash functions and low quality linearhash functions. To evaluate these mid-range hash functions properly, we develop new evaluation methods to better distinguish non-cryptographic hash function quality. The hashfunctions described in this paper achieve low-latency, wide hashing with good avalanche anduniversality properties at a much lower cost than existing solutions.
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Title: Statistical approaches for the analysis, measurement, and modeling of RFID systems
Creator: Wang, Liyan (Software engineer)
Date: 2018
Collection: Electronic Theses & Dissertations
Description: The goal of this thesis is to develop statistical and learning algorithms for the analysis, measurement, and modeling of wireless networking( Radio frequency identification systems).Radio frequency identification (RFID) systems are widely used in logistic, supply chain industry and inventory management. RFID is already in use in multiple industries and for various purposes. The device in your car that lets you zoom by in the fast lane at a tollbooth, while deducting a dollar amount from your...
Show moreThe goal of this thesis is to develop statistical and learning algorithms for the analysis, measurement, and modeling of wireless networking( Radio frequency identification systems).Radio frequency identification (RFID) systems are widely used in logistic, supply chain industry and inventory management. RFID is already in use in multiple industries and for various purposes. The device in your car that lets you zoom by in the fast lane at a tollbooth, while deducting a dollar amount from your account, is an example of RFID technology in everyday use. Mostly, existing RFID systems are primarily used to identify the RFID tags present in a tag population(e.g., tracking a specific tag from a tag population) while identifying some specific tags is a critical operation, it is usually very time consuming and is not desired or necessary in some situations. For instance, if the objective is to determine whether any of the tags are missing(e.g., to detect some items according to a consignment), the first thing to do is to identify all tags’ ID and then compare with the original record to determine if there is any tags are missing. Definitely, the whole process will be very slow if we have a very large tag population. In this thesis, I present novel statistical algorithms to enable fast and new applications in RFID systems. For example, detecting the missing tags in a large tag population with high accuracy while using the existing infrastructure of RFID systems which is already deployed in industry. More pacifically, I present my work on designing statistical algorithms for estimation the number of missing tags in a population of RFID tags, for detecting and identifying the missing tags from a population of RFID tags.The key distinction of my work compared to prior art is that my methods are compliant with EPCGlobal Class 1 Generation 2 (C1G2) RFID standard. It is critical for RFID methods to be compliant with the C1G2 standard since the commercially available of-the- shelf RFID equipment follows the C1G2 standard. A method which does not comply with the C1G2 standard cannot be deployed on the existing installations of RFID systems because it requires custom hardware, which will cost a lot. In an RFID-enabled warehouse, there may be thousands of tagged items that belong to different categories, e.g., different places of origin or different brands [72]. Each tag attached to an item has a unique ID that consists of two fields: a category ID that specifies the category of the attached object, and a member ID that identifies this object within its category. As a manager of the warehouse, one may desire to timely monitor the product stock of each category. If the stock of a category is too high, it may indicate that this product category is not popular, and the seller needs to adjust the marketing strategy (e.g., lowering prices to increase sales). On the contrary, if the stock of a category is too low, the seller should perform stock replenishment as soon as possible. Manual checking is laborious and of low time-efficiency. You cannot imagine how difficult it is for a manager to manually count the number of items in each category that may be stacked together or placed on high shelves. Hence, it is desirable to exploit the RFID technique to quickly obtain the number of tagged items in each category. A multi-category RFID estimation protocol should satisfy three additional requirements. First, it should be standard compliant; otherwise, it will be difficult to be deployed. Second, it should preserve the privacy of tags by not reading their member IDs. Third, it should work with both a single-reader and multiple-reader environments. As the communication range between a tag and a reader is limited, a large population of tags is often covered by multiple readers whose regions often overlap.
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Title: Performance analysis and privacy protection of network data
Creator: Ahmed, Faraz (Research engineer)
Date: 2018
Collection: Electronic Theses & Dissertations
Description: "The goal of this thesis is to address network management research challenges faced by operational networks - with specific focus on cellular networks, content delivery networks, and online social networks. Next, I give an overview of my research on network management of these networks. Cellular networks utilize existing service quality management systems for detecting performance degradation issues inside the network, however, under certain conditions degradation in End-to-End (E2E)...
Show more"The goal of this thesis is to address network management research challenges faced by operational networks - with specific focus on cellular networks, content delivery networks, and online social networks. Next, I give an overview of my research on network management of these networks. Cellular networks utilize existing service quality management systems for detecting performance degradation issues inside the network, however, under certain conditions degradation in End-to-End (E2E) performance may go undetected. These conditions may arise due to problems in the mobile device hardware, smartphone applications, and content providers. In this thesis, I present a system for detecting and localizing E2E performance degradation at cellular service providers across four administrative domains: cellular network, content providers, device manufacturers, and smartphone applications. Cellular networks also need systems that can prioritize performance degradation issues according to the number of customers impacted. Cell tower outages are performance degradation issues that directly impact connectivity of cellular network users. In this thesis, we design and evaluate a cell tower outage monitoring system that analyzes and estimates device level impact during cell tower outages. Content delivery networks (CDNs) maintain multiple transit routes from content distribution servers to eyeball ISP networks which provide Internet connectivity to end users. Two major considerations for CDNs are transit prices and performance dynamics of delivering content to end users. The dynamic nature of transit pricing and performance makes it challenging to optimize the cost and performance tradeoff. There are thousands of eyeball ISPs which are reachable via different transit routes and different geographical locations. Each choice of transit route for a particular eyeball ISP and geographical location has distinct cost and performance characteristics, which makes the problem of developing a transit routing strategy challenging. In this thesis, I present a measurement approach to actively collect client perceived network performance and then use these measurements towards optimal transit route selection for CDNs. Online Social Networks (OSNs) often refuse to publish their social network graphs due to privacy concerns. Differential privacy has been the widely accepted criteria for privacy preserving data publishing. In this thesis, I present a random matrix approach to OSN graph publishing, which achieves storage and computational efficiency by reducing dimensions of adjacency matrices and achieves differential privacy by adding a small amount of noise."--Pages ii-iii.
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Title: On design and implementation of fast & secure network protocols for datacenters
Creator: Munir, Ali (Graduate of Michigan State University)
Date: 2019
Collection: Electronic Theses & Dissertations
Description: My PhD work focuses on improving the performance and security of networked systems. For network performance, my research focuses on scheduling and transport in datacenter networks. For network security, my research focuses on multipath TCP security.To improve the performance of datacenter transport, I proposed PASE, a near-optimal and deployment friendly transport protocol. To this end, I first identified the underlying strategies used by existing datacenter transports. Next, I showed that...
Show moreMy PhD work focuses on improving the performance and security of networked systems. For network performance, my research focuses on scheduling and transport in datacenter networks. For network security, my research focuses on multipath TCP security.To improve the performance of datacenter transport, I proposed PASE, a near-optimal and deployment friendly transport protocol. To this end, I first identified the underlying strategies used by existing datacenter transports. Next, I showed that these strategies are complimentary to each other, rather than substitutes, as they have different strengths and can address each other's limitations. Unfortunately, prior datacenter transports use only one of these strategies and as a result they either achieve near-optimal performance or deployment friendliness but not both. Based on this insight, I designed a datacenter transport protocol called PASE, which carefully synthesizes these strategies by assigning different transport responsibility to each strategy. To further improve the performance of datacenter transport in multi-tenant networks, I proposed Stacked Congestion Control (SCC), to achieve performance isolation and objective scheduling simultaneously. SCC is a distributed host-based bandwidth allocation framework, where an underlay congestion control layer handles contention among tenants, and a private congestion control layer for each tenant optimizes its performance objective. To my best knowledge, no prior work supported performance isolation and objective scheduling simultaneously.To improve task scheduling performance in datacenters, I proposed NEAT, a task scheduling framework that leverages information from the underlying network scheduler to make task placement decisions. Existing datacenter schedulers optimize either the placement of tasks or the scheduling of network flows. Inconsistent assumptions of the two schedulers can compromise the overall application performance. The core of NEAT is a task completion time predictor that estimates the completion time of a task under given network condition and a given network scheduling policy. Next, a distributed task placement framework leverages the predicted task completion times to make task placement decisions and minimize the average completion time of active tasks.To improve multipath TCP (MPTCP) security, I reported vulnerabilities in MPTCP that arise because of cross-path interactions between MPTCP subflows. MPTCP allows two endpoints to simultaneously use multiple paths between them. An attacker eavesdropping one MPTCP subflow can infer throughput of other subflows and also can inject forged MPTCP packets to change priorities of any MPTCP subflow. Attacker can exploit these vulnerabilities to launch the connection hijack attack on the paths he has no access to, or to divert traffic from one path to other paths. My proposed vulnerabilities fixes, changes to MPTCP specification, provide the guarantees that MPTCP is at least as secure as TCP and the original MPTCP. And has been adopted by IETF.
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Title: Measurement and modeling of large scale networks
Creator: Shafiq, Muhammad Zubair
Date: 2014
Collection: Electronic Theses & Dissertations
Description: The goal of this thesis is to identify measurement, modeling, and optimization opportunities for large scale networks -- with specific focus on cellular networks and online social networks. These networks are facing unprecedented operational challenges due to their very large scale.Cellular networks are experiencing an explosive increase in the volume of traffic for the last few years. This unprecedented increase in the volume of mobile traffic is attributed to the increase in the subscriber...
Show moreThe goal of this thesis is to identify measurement, modeling, and optimization opportunities for large scale networks -- with specific focus on cellular networks and online social networks. These networks are facing unprecedented operational challenges due to their very large scale.Cellular networks are experiencing an explosive increase in the volume of traffic for the last few years. This unprecedented increase in the volume of mobile traffic is attributed to the increase in the subscriber base, improving network connection speeds, and improving hardware and software capabilities of modern smartphones. In contrast to the traditional fixed IP networks, mobile network operators are faced with the constraint of limited radio frequency spectrum at their disposal. As the communication technologies evolve beyond 3G to Long Term Evolution (LTE), the competition for the limited radio frequency spectrum is becoming even more intense. Therefore, mobile network operators increasingly focus on optimizing different aspects of the network by customized design and management to improve key performance indicators (KPIs).Online social networks are increasing at a very rapid pace, while trying to provide more content-rich and interactive services to their users. For instance, Facebook currently has more than 1.2 billion monthly active users and offers news feed, graph search, groups, photo sharing, and messaging services. The information for such a large user base cannot be efficiently and securely managed by traditional database systems. Social network service providers are deploying novel large scale infrastructure to cope with these scaling challenges.In this thesis, I present novel approaches to tackle these challenges by revisiting the current practices for the design, deployment, and management of large scale network systems using a combination of theoretical and empirical methods. I take a data-driven approach in which the theoretical and empirical analyses are intertwined. First, I measure and analyze the trends in data and then model the identified trends using suitable parametric models. Finally, I rigorously evaluate the developed models and the resulting system design prototypes using extensive simulations, realistic testbed environments, or real-world deployment. This methodology is to used to address several problems related to cellular networks and online social networks.
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Title: A graph theoretic approach to malware detection
Creator: Tabish, Syeda Momina
Date: 2012
Collection: Electronic Theses & Dissertations
Description: Current malware detection approaches (i.e. anti-virus software) deployed at end hosts utilize features of a specic malware instance. These approaches suer from poor accuracy because such features are easily evaded by trivial obfuscation such as garbage insertion and re-ordering of instruction or call sequences. In this paper,we introduce a novel graph theoretic approach to detect malware from instruction or call sequences. In our approach, we map the instruction or call sequence of an...
Show moreCurrent malware detection approaches (i.e. anti-virus software) deployed at end hosts utilize features of a specic malware instance. These approaches suer from poor accuracy because such features are easily evaded by trivial obfuscation such as garbage insertion and re-ordering of instruction or call sequences. In this paper,we introduce a novel graph theoretic approach to detect malware from instruction or call sequences. In our approach, we map the instruction or call sequence of an executable program to a graph. We then extract features from the constructed graphs at three levels: (1) vertex level, (2) sub-graph level, and (3) graph level. These features act as footprints of the behavior of an executable program and are leveraged to dierentiate between benign and malware programs. The results of our experiments show that our graph-theoretic approach differentiate between benign and malware programs with 100% accuracy.
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Title: Intention based authorization dialog boxes
Creator: Santa, Marc
Date: 2012
Collection: Electronic Theses & Dissertations
Description: "Throughout the computing experience, users frequently encounter security authorization dialog boxes in the form of Yes/No questions, which we call Decision Based Authorization systems. These systems are confusing to users who may not be technologically adept enough to make a correct \Allow" or \Deny" decision. In this paper, we propose an Intention Based Authorization system in which the user is presented with a list of intentions and he/she selects the intention that is closest to his/her...
Show more"Throughout the computing experience, users frequently encounter security authorization dialog boxes in the form of Yes/No questions, which we call Decision Based Authorization systems. These systems are confusing to users who may not be technologically adept enough to make a correct \Allow" or \Deny" decision. In this paper, we propose an Intention Based Authorization system in which the user is presented with a list of intentions and he/she selects the intention that is closest to his/her actual intention. Only if the users intention matches that of the application, then the application is authorized to perform the action that it requested."--From abstract.
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Title: Statistical and learning algorithms for the design, analysis, measurement, and modeling of networking and security systems
Creator: Shahzad, Muhammad (College teacher)
Date: 2015
Collection: Electronic Theses & Dissertations
Description: "The goal of this thesis is to develop statistical and learning algorithms for the design, analysis, measurement, and modeling of networking and security systems with specific focus on RFID systems, network performance metrics, user security, and software security. Next, I give a brief overview of these four areas of focus." -- Abstract.

Title: Denial of firewalling : attack and defense
Creator: Hulst, Joshua
Date: 2011
Collection: Electronic Theses & Dissertations
Description: Firewalls are critical security devices handling all traffic in and out of a network. When under heavy load of both malicious and legitimate traffic, firewalls may be overloaded and start discarding or permitting packets without checking firewall rules, which can cause huge revenue losses or security breaches. In this paper, we study Denial of Firewalling attacks, where attackers use well-crafted traffic to effectively overwhelm a firewall. We first investigate firewall implementation...
Show moreFirewalls are critical security devices handling all traffic in and out of a network. When under heavy load of both malicious and legitimate traffic, firewalls may be overloaded and start discarding or permitting packets without checking firewall rules, which can cause huge revenue losses or security breaches. In this paper, we study Denial of Firewalling attacks, where attackers use well-crafted traffic to effectively overwhelm a firewall. We first investigate firewall implementation characteristics that can be exploited for such attacks while treating the firewall as a black box. We conducted our studies on a testbed with three popular firewall devices. Second, given a remote firewall, we propose methods for attackers to infer the implementation of the firewall. We develop firewall fingerprinting techniques based on firewall decisions on a sequence of TCP packets with unusual flags and machine learning techniques for inferring firewall implementation. Next, we present methods that attackers can use to generate the traffic that can effectively overload an identified remote firewall. We show that some firewalls can be easily overloaded by a small volume of carefully crafted traffic. Finally, we discuss methods for defending against such attacks.
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Title: Privacy and integrity preserving computation in distributed systems
Creator: Chen, Fei
Date: 2011
Collection: Electronic Theses & Dissertations
Description: Preserving privacy and integrity of private data has become core requirements for many distributed systems across different parties. In these systems, one party may try to compute or aggregate useful information from the private data of other parties. However, this party is not be fully trusted by other parties. Therefore, it is important to design security protocols for preserving such private data. Furthermore, one party may want to query the useful information computed from such private...
Show morePreserving privacy and integrity of private data has become core requirements for many distributed systems across different parties. In these systems, one party may try to compute or aggregate useful information from the private data of other parties. However, this party is not be fully trusted by other parties. Therefore, it is important to design security protocols for preserving such private data. Furthermore, one party may want to query the useful information computed from such private data. However, query results may be modified by a malicious party. Thus, it is important to design query protocols such that query result integrity can be verified.In this dissertation, we study four important privacy and integrity preserving problems for different distributed systems. For two-tiered sensor networks, where storage nodes serve as an intermediate tier between sensors and a sink for storing data and processing queries, we proposed SafeQ, a protocol that prevents compromised storage nodes from gaining information from both sensor collected data and sink issued queries, while it still allows storage nodes to process queries over encrypted data and the sink to detect compromised storage nodes when they misbehave. For cloud computing, where a cloud provider hosts the data of an organization and replies query results to the customers of the organization, we propose novel privacy and integrity preserving schemes for multi-dimensional range queries such that the cloud provider can process encoded queries over encoded data without knowing the actual values, and customers can verify the integrity of query results with high probability. For distributed firewall policies, we proposed the first privacy-preserving protocol for cross-domain firewall policy optimization. For any two adjacent firewalls belonging to two different administrative domains, our protocol can identify in each firewall the rules that can be removed because of the other firewall. For network reachability, one of the key factors for capturing end-to-end network behavior and detecting the violation of security policies, we proposed the first cross-domain privacy-preserving protocol for quantifying network reachability.
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