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Our current research focuses on three directions: (1) trust establishment foundations; (2) reputation management; and (3) trust-assisted solutions for securing wireless networks. Topic 1: Defense Trust Management Vulnerabilities in Distributed Networks Motivation and Goals: Establishing trust among distributed network entities has been recognized as a powerful tool to secure distributed networks such as mobile ad hoc networks (MANET). Similar to all security schemes, trust establishment methods themselves can be vulnerable to attacks. This motivates us to investigate the vulnerabilities in trust establishment methods and defense mechanisms. Approaches: In this study, we have identified five attacks against trust establishment methods and developed defense mechanisms. Effectiveness of the attacks and the defense is demonstrated in the scenario of securing routing protocols and detecting malicious nodes in MANET. Observations and Outcomes: the advantage of integrating trust in distributed networks is demonstrated through analysis and simulations. Three attacks, including bad-mouthing, on-off attack, and confliction-behavior attack, are investigated in depth. The main results are summarized as follows. For the bad mouthing attack, the most effective defense is to incorporate recommendation trust in the malicious node detection algorithm. To defeat the on-off attack, the adaptive forgetting scheme is better than using fixed forgetting factors. In the conflicting behavior attack, when the attackers do not provide recommendations to anyone, this attack is most effective. Under the conflicting-behavior attack, using recommendation trust in malicious node detection can reduce the detection rate. This research yields a systematic understanding on vulnerability of trust evaluation mechanisms for distributed networks.
Topic 2: Securing Online Rating Systems through Signal Processing and Trust Management Motivation and Goals: The Internet, the revolutionary mass communication media, has enabled individuals to make their personal opinions accessible to the global community at almost no cost. One important type of information sharing is through online opinion forums and rating systems, such as Epinions and Amazon product rating. In such systems, users submit their opinions regarding products, services or other users. Then, the submitted opinions are analyzed, aggregated, and made publicly available. While feedback-based rating systems are having increasing influence on today¡¯s consumers, ensuring reliability and security of such systems is a challenging task, especially when the number of regular ratings is relatively small and unfair ratings can contribute to a significant portion of the overall ratings. The goal of this research is to develop new algorithms and a framework to secure rating aggregation. Approaches: In this project, we designed a comprehensive system for integrating trust management and signal processing techniques into rating aggregation process.
Topic 3: Securing Online Reputation Systems: New Attack and Defense Motivation and Goals: Word-of-mouth, one of the most ancient mechanisms in the history of human society, is gaining new significance in the Internet. The online reputation systems, also known as the on-line feedback mechanisms, are creating large scale, virtual word-of-mouth networks in which individuals share opinions and experiences on a wide range of topics, including products, companies, digital content and even other people. Reputation systems are having increasing influence on purchasing decision of consumers and online digital content distribution. Meanwhile, the manipulation of such systems is rapidly growing. Firms post biased ratings and reviews to praise their own products or bad-mouth the products of their competitors. Political campaigns promote positive video clips and hide negative video clips by inserting unfair ratings at YouTube.com. In the current literature, the research on attacks against reputation systems is still immature. The existing threat models are straightforward. In this research, we investigate sophisticated attacks against reputation systems. Approaches: In this study, we report the discovery of a new attack, named RepTrap, against feedback-based reputation systems, such as those used in P2P file-sharing systems and E-commerce websites (e.g. Amazon.com). We conduct an in-depth investigation on this new attack, including
Topic 4: Modeling Misbehaviors in Online Rating Systems Motivation and Goals: Dealing with unfair ratings in online feedback-based rating systems has been recognized as an important problem. Many unfair rating detection approaches have been developed. Currently, those approaches are evaluated against simple attack behavior models, in which assumptions are made to greatly simplify the behavior of dishonest raters. However, most of the assumptions have not been validated by real user data and the simplification has not been well justified. More important, these simple models cannot reflect the smart attacks from real human users who can always adjust the attack strategies based on their observation of original rating data and gain knowledge about the rating system. The lack of unfair rating data from real human users and realistic attack behavior models has become an obstacle toward developing reliable rating systems. More realistic and complicated models of dishonest raters need to be developed. Approaches: To solve this problem, we first design and launch a rating challenge to collect attack data from real human users. Moreover, we use our research results (see topic 2) in the rating challenge. We are able to collect a broad range of attacks including both straightforward attacks and smart/complicated attacks. Then, we analyze the attack behavior of real human users and evaluate the performance of both the complex and simple defense schemes against real user data. Many important results are obtained. Finally, we build novel attack models as well as a comprehensive attack generator. Observations and Outcomes: Based on the analysis of real attack data, we have discovered important features in unfair ratings. For example, the bias and variance of unfair ratings greatly affect the strength of attacks; there exists an unfair rating arrival rate that maximizes the attack power; correlation between unfair ratings and fair ratings is not presented in current attacks but can improve the attack power, etc. The attack models and attack generator developed in this research can be directly used by the research community and industry to test current rating aggregation systems, as well as to assist the design of future rating systems. The results generated by this research are reported in the following paper.
Topic 5: Secure Collaborative Spectrum Sensing in Cognitive Radio Networks Motivation and Goals: Collaborative sensing in cognitive radio networks can significantly improve the probability of detecting the transmission of primary users. In current collaborative sensing schemes, all collaborative secondary users are assumed to be honest. However, it is well known that wireless devices can be compromised and under the control of malicious parities. The malicious secondary user can send false information and mislead the spectrum sensing results to cause collision or inefficient spectrum usage. In this study, we investigate how to improve the security of collaborative sensing. Approaches: We develop a malicious user detection algorithm that calculates the suspicious level of secondary users based on their past reports. Then, we calculate trust values as well as consistency values that are used to eliminate the malicious users' influence on the primary user detection results. Observations and Outcomes: We just started this research and only preliminary results are obtained. The preliminary results are summarized in the following manuscript.
Topic 6: Securing Time-synchronization Protocols in Sensor Networks Motivation and Goals: Time synchronization is critical to sensor networks. Precise time is required by many applications and protocols, such as measuring time-of-flight for positioning, forming TDMA radio scheduling, coordinating sensors¡¯ sleep wakeup schedules, preventing replay attacks, and collaborative signal processing. If malicious entities can manipulate the time synchronization protocol, catastrophic failure of many applications and protocols in sensor networks would occur. Recently, several schemes are proposed to secure time synchronization in sensor networks. These schemes focus either on securing pair wise clock synchronization between two or several nodes, or on external attacks. When there are sophisticated attacks from insiders (i.e., compromised sensors) targeting network-wide time synchronization, the existing defense methods are not sufficient. In this study, we identify various attacks against time synchronization and then develop a detection and self-healing scheme to defeat those attacks. Approaches:This work contributes to securing time synchronization protocols in sensor networks from two perspectives. First, we identify various attacks that can be launched by compromised sensors. Second, we design a trust-enhanced detection and self-healing scheme to defeat major attacks against time synchronization protocols. The defense scheme has three phases: (1) abnormality detection performed by individual sensors, (2) trust-based malicious node detection performed by the base station, and (3) self-healing through changing the topology of the synchronization tree. Observations and Outcomes: Simulations have shown that the proposed scheme can successfully detect several attacks and enable fast recovery from those attacks. For example, when the attackers launch a smart attack that cannot be detected by the existing schemes, the proposed scheme can detect 85% of malicious nodes just after 12 rounds of operation. The results generated by this research are reported in the following paper.
Cooperative Transmission in Wireless Networks Cooperative transmission is an emerging communication technique that takes advantage of spatial diversity and broadcast natures of wireless channel to improve wireless channel capacity. However, cooperative transmission can be vulnerable to malicious attacks, especially in its current design. In this project, we examine whether the cooperative transmission still has performance advantage when we consider security issues. In particular, we identify various attacks against cooperative transmission, analyze vulnerabilities of current schemes, design a trust-assisted cooperative transmission scheme, and evaluate the proposed scheme through simulations. The proposed scheme strengthens security and maintains the performance advantage. It performs much better than the traditional scheme when there are malicious/selfish relays or severe channel estimation errors. In addition, we investigate the advantage of cooperative transmission in terms of defending jamming attacks. A reduction in link outage probability is obtained and the recovery from attacks is observed. Reference:
Trust Establishment in Distributed System Trust establishment is recognized as an important approach to defend distributed networks, such as mobile ad hoc networks and sensor networks, against malicious attacks. Trust establishment mechanisms can stimulate collaboration among distributed computing and communication entities, facilitate the detection of untrustworthy entities, and assist decision-making in various protocols. In the current literature, the methods proposed for trust establishment are always evaluated through simulation, but theoretical analysis is extremely rare. In this project, we present a suite of approaches to analyze trust establishment process. These analysis approaches are used to provide in-depth understanding of trust establishment process and quantitative comparison among trust establishment methods. The proposed analysis methods are validated through simulations. Reference:
Energy Efficiency in Wireless Sensor Networks Energy has been identified as a crucial resource in wireless sensor networks (WSNs). Since it is usually difficult to recharge the sensors deployed in a remote or hostile environment, reducing the energy consumption is the key to prolong the lifetime of the network. In this project, we investigate an energy-saving strategy, called outsourcing, which allows a sensor to outsource tasks to others in order to reduce the overall energy consumption as well as the energy consumption of the sensors with low remaining energy. Based on this strategy, we designed an energy efficient reliable transport protocol that intelligently distributes the task of data recovery. Both analysis and simulations show the significant reduction in energy consumption. In addition, the implementation of the proposed scheme requires minor modification to the existing protocols. References:
Key Management for Secure Group Communications References:
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Network Security and Trust Group |
| Dept. of Electrical, Computer and Biomedical Engineering at the University of Rhode Island You are the |