IEEE JAVA BASED PROJECTS


Resolving Multi-party Privacy Conflicts in Social Media

Abstract

Items shared through Social Media may affect more than one user’s privacy e.g., photos that depict multiple users, comments that mention multiple users, events in which multiple users are invited, etc. The lack of multi-party privacy management support in current mainstream Social Media infrastructures makes users unable to appropriately control to whom these items are actually shared or not. Computational mechanisms that are able to merge the privacy preferences of multiple users into a single policy for an item can help solve this problem. However, merging multiple users’ privacy preferences is not an easy task, because privacy preferences may conflict, so methods to resolve conflicts are needed. Moreover, these methods need to consider how users’ would actually reach an agreement about a solution to the conflict in order to propose solutions that can be acceptable by all of the users affected by the item to be shared. Current approaches are either too demanding or only consider fixed ways of aggregating privacy preferences. In this paper, we propose the first computational mechanism to resolve conflicts for multi-party privacy management in Social Media that is able to adapt to different situations by modeling the concessions that users make to reach a solution to the conflicts. We also present results of a user study in which our proposed mechanism outperformed other existing approaches in terms of how many times each approach matched users’ behavior.

A Web Traffic Analysis Attack Using Only Timing Information

Abstract

We introduce an attack against encrypted web traffic that makes use only of packet timing information on the uplink. This attack is therefore impervious to existing packet padding defenses. In addition, unlike existing approaches, this timing-only attack does not require the knowledge of the start/end of web fetches and so is effective against traffic streams. We demonstrate the effectiveness of the attack against both wired and wireless traffic, achieving mean success rates in excess of 90%. In addition to being of interest in its own right, this timing-only attack serves to highlight deficiencies in existing defenses and so to areas where it would be beneficial for virtual private network (VPN) designers to focus further attention. an attack against encrypted web traffic that makes use only of packet timing information on the uplink. In addition, unlike existing approaches this timing-only attack does not require knowledge of the start/end of web fetches and so is effective against traffic streams. We demonstrate the effectiveness of the attack against both wired and wireless traffic.

Cross-Networks Energy Efficiency Tradeoff: From Wired Networks to Wireless Networks

The tremendously large number of increasing Internet protocol (IP) packets call for quality of service (QoS) vguaranteed packets transmission with low-delay, high throughput and high energy efficiency (defined as the transmitted bits per unit energy consumption) in the fifth-generation (5G) networks. For this motivation, wavelength division multiplexing (WDM) networks and the next generation of wireless technologies are two major methods in the wired and wireless networks, respectively. However, the existing energy efficient switch fabric and wireless technologies have focused on either wired or wireless networks, only separately. The joint cross-networks optimization for energy efficiency in 5G remains unexplored. This does not fully facilitate the QoS guaranteed packets transmission and energy efficient networks planning from the viewpoint of cross-networks. In this paper, we formulate a joint optimization model to enhance the performance of energy efficiency in 5G. Specifically, each base station (BS) is equipped with a set of parallel tunable lasers for simultaneous transmission of multiple packets from the uplink users in the cell as well as the data center networks (DCNs). We propose a novel joint cross-networks scheduling and routing (JCNSR) algorithm according to the wireless channel quality of users, user data rate, and the topology constraint. The IP packets are then delivered to the targeted cells via transport layer in the WDM network and further transmitted to the targeted users via wireless channels under the constraint of delay. Based on the idea of the cross-networks tradeoff between the delay and energy efficiency, JCNSR can achieve high energy efficient transmission with performance guarantee. The effectiveness of the proposed framework is verified by extensive simulations.

A Stable Approach for Routing Queries in Unstructured P2P Networks

Finding a document or resource in an unstructured peer-to-peer network can be an exceedingly difficult problem. In this paper we propose a query routing approach that accounts for arbitrary overlay topologies, nodes with heterogeneous processing capacity, e.g., reflecting their degree of altruism and heterogenous class-based likelihoods of query resolution at nodes which may reflect query loads and the manner in which files/resources are distributed across the network. The approach is shown to be stabilize the query load subject to a grade of service constraint, i.e., a guarantee that queries' routes meet pre-specified class-based bounds on their associated a priori probability of query resolution. An explicit characterization of the capacity region for such systems is given and numerically compared to that associated with random walk based searches. Simulation results further show the performance benefits, in terms of mean delay, of the proposed approach. Additional aspects associated with reducing complexity, estimating parameters, and adaptation to class-based query resolution probabilities and traffic loads are studied. we provided a novel, distributed, and reliable search policy for unstructured peer-to-peer networks with super-peers. Our backpressure based policy can provide capacity gains of as large as 68% over traditional random walk techniques. We also provided modifications to the algorithm that make it amenable to implementation.

I Path: Path Inference in Wireless Sensor Networks


Recent wireless sensor networks (WSNs) are becoming increasingly complex with the growing network scale and the dynamic nature of wireless communications. Many measurement and diagnostic approaches depend on per-packet routing paths for accurate and fine-grained analysis of the complex network behaviors. In this paper, we propose iPath, a novel path inference approach to reconstructing the per-packet routing paths in dynamic and large-scale networks. The basic idea of iPath is to exploit high path similarity to iteratively infer long paths from short ones. iPath starts with an initial known set of paths and performs path inference iteratively. iPath includes a novel design of a lightweight hash function for verification of the inferred paths. In order to further improve the inference capability as well as the execution efficiency, iPath includes a fast bootstrapping algorithm to reconstruct the initial set of paths. We also implement iPath and evaluate its performance using traces from large-scale WSN deployments as well as extensive simulations. Results show that iPath achieves much higher reconstruction ratios under different network settings compared to other state-of-the-art approaches.

Optimal DoS Attack Scheduling in Wireless Networked Control System

Abstract

Recently, many literature works have considered the security issues of wireless networked control system (WNCS). However, few works studied how the attacker should optimize its attack schedule in order to maximize the effect on the system performance due to the insufficiency of energy at the attacker side. This paper fills this gap from the aspect of control system performance. We consider the optimal jamming attack that maximizes the Linear Quadratic Gaussian (LQG) control cost function under energy constraint. After analyzing the properties of the cost function under an arbitrary attack schedule, we derive the optimal jamming attack schedule and the corresponding cost function. System stability under this optimal attack schedule is also considered. We further investigate the optimal attack schedule in a WNCS with multiple subsystems. Different examples are provided to demonstrate the effectiveness of the proposed optimal denial-of-service attack schedule. We first formulated an optimization problem from the perspective of a DoS attacker, in which the attacker can jam the transmission channel with limited actions in any active period. Then, we analyzed the properties of the LQG cost function under any given feasible attack schedule. The optimal attack schedules and corresponding expected cost are obtained, which demonstrate that grouping the limited attacks together in every active period is optimal.We further studied the system stability under optimal attack schedules. We also investigated the optimal attack schedule in WNCS with multiple subsystems

PRIGUARD: A SEMANTIC APPROACH TO DETECT PRIVACY VIOLATIONS IN ONLINE SOCIAL NETWORKS

Abstract

Social network users expect the social networks that they use to preserve their privacy. Traditionally, privacy breaches have been understood as malfunctioning of a given system. However, in online social networks, privacy breaches are not necessarily a malfunctioning of a system but a byproduct of its workings. The users are allowed to create and share content about themselves and others. When multiple entities start distributing content without a control, information can reach unintended individuals and inference can reveal more information about the user. Accordingly, this paper first categorizes the privacy violations that take place in online social networks. Our categorization yields that the privacy violations in online social networks stem from intricate interactions and detecting these violations requires semantic understanding of events. Our proposed approach is based on agent-based representation of a social network, where the agents manage users’ privacy requirements by creating commitments with the system. The privacy context, including the relations among users or content types are captured using description logic. The proposed detection algorithm performs reasoning using the description logic and commitments on a varying depths of social networks. We implement the proposed model and evaluate our approach using real-life social networks.

Cache Bandwidth Allocation for P2P File-Sharing Systems to Minimize Inter-ISP Traffic

Abstract

Many Internet service providers (ISPs) have deployed peer-to-peer (P2P) caches in their networks in order to decrease costly inter-ISP traffic. A P2P cache stores parts of the most popular contents locally, and if possible serves the requests of local mpeers to decrease the inter-ISP traffic. Traditionally, P2P cache resource management focuses on managing the storage resource of the cache so as to maximize the inter-ISP traffic savings. In this paper ,we show that when there are many overlays competing for the upload bandwidth of a P2P cache, then in order to maximize the inter-ISP traffic savings, the cache’s upload bandwidth should be actively allocated among the overlays. We formulate the problem of P2P cache bandwidth allocation as a Markov decision process and propose three approximations to the optimal cache bandwidth allocation policy. We use extensive simulations and experiments to evaluate the performance of the proposed policies, and show that the bandwidth allocation policy that prioritizes swarms with a small ratio of local peers to all peers in the swarm can improve the inter-ISP traffic savings in BitTorrent-like P2P systems by up to 30%–60%.

Distributed and Fair Beaconing Rate Adaptation for Congestion Control In Vehicular Networks

Abstract

Cooperative inter-vehicular applications rely on the exchange of broadcast single-hop status messages among vehicles, called beacons. The aggregated load on the wireless channel due to periodic beacons can prevent the transmission of other types of messages, what is called channel congestion due to beaconing activity. In this paper we approach the problem of controlling the beaconing rate on each vehicle by modeling it as a Network Utility Maximization (NUM) problem. This allows us to formally apply the notion of fairness of a beaconing rate allocation in vehicular networks and to control the trade-off between efficiency and fairness. The NUM methodology provides a rigorous framework to design a broad family of simple and decentralized algorithms, with proved convergence guarantees to a fair allocation solution. In this context, we focus exclusively in beaconing rate control and propose the Fair Adaptive Beaconing Rate for Intervehicular Communications (FABRIC) algorithm, which uses a particular scaled gradient projection algorithm to solve the dual of the NUM problem. The desired fairness notion in the allocation can be established with an algorithm parameter. Simulation results validate our approach and show that FABRIC converges to fair rate allocations in multi-hop and dynamic scenarios.

A Survey of Man in the Middle Attacks

Abstract

The Man-In-The-Middle (MITM) attack is one of the most well known attacks in computer security, representing one of the biggest concerns for security professionals. MITM targets the actual data that flows between endpoints, and the confidentiality and integrity of the data itself. In this paper, we extensively review the literature on MITM to analyse and categorise the scope of MITM attacks, considering both a reference model, such as the Open Systems Interconnection (OSI) model, as well as two specific widely used network technologies, i.e., GSM and UMTS. In particular, we classify MITM attacks based on several parameters, like location of an attacker in the network, nature of a communication channel, and impersonation techniques. Based on an impersonation techniques classification, we then provide execution steps for each MITM class. We survey existing countermeasures and discuss the comparison among them. Finally, based on our analysis, we propose a categorization of MITM prevention mechanisms, and we identify some possible directions for future research. we have analyzed MITM attack and presented a comprehensive classification of such attack based on impersonation techniques. Also, we provided various MITM deface mechanisms along with their descriptions.

STAMP ENABLING PRIVACY-PRESERVING LOCATION PROOFS FOR MOBILE USERS

ABSTRACT:

Location-based services are quickly becoming immensely popular. In addition to services based on users' current location, many potential services rely on users' location history, or their spatial-temporal provenance. Malicious users may lie about their spatial-temporal provenance without a carefully designed security system for users to prove their past locations. In this paper, we present the Spatial-Temporal provenance Assurance with Mutual Proofs (STAMP) scheme. STAMP is designed for ad-hoc mobile users generating location proofs for each other in a distributed setting. However, it can easily accommodate trusted mobile users and wireless access points. STAMP ensures the integrity and non-transferability of the location proofs and protects users' privacy. A semi-trusted Certification Authority is used to distribute cryptographic keys as well as guard users against collusion by a light-weight entropy-based trust evaluation approach. Our prototype implementation on the Android platform shows that STAMP is low-cost in terms of computational and storage resources. Extensive simulation experiments show that our entropy-based trust model is able to achieve high collusion detection accuracy.

A Stable Approach for Routing Queries in Unstructured P2P Networks

ABSTRACT:

Finding a document or resource in an unstructured peer-to-peer network can be an exceedingly difficult problem. In this paper we propose a query routing approach that accounts for arbitrary overlay topologies, nodes with heterogeneous processing capacity, e.g., reflecting their degree of altruism, and heterogenous class-based likelihoods of query resolution at nodes which may reflect query loads and the manner in which files/resources are distributed across the network. The approach is shown to be stabilize the query load subject to a grade of service constraint, i.e., a guarantee that queries' routes meet pre-specified class-based bounds on their associated a priori probability of query resolution. An explicit characterization of the capacity region for such systems is given and numerically compared to that associated with random walk based searches. Simulation results further show the performance benefits, in terms of mean delay, of the proposed approach. Additional aspects associated with reducing complexity, estimating parameters, and adaptation to class-based query resolution probabilities and traffic loads are studied.

iPath: Path Inference in Wireless Sensor Networks

ABSTRACT:

Recent wireless sensor networks (WSNs) are becoming increasingly complex with the growing network scale and the dynamic nature of wireless communications. Many measurement and diagnostic approaches depend on per-packet routing paths for accurate and fine-grained analysis of the complex network behaviors. In this paper, we propose iPath, a novel path inference approach to reconstructing the per-packet routing paths in dynamic and large-scale networks. The basic idea of iPath is to exploit high path similarity to iteratively infer long paths from short ones. iPath starts with an initial known set of paths and performs path inference iteratively. iPath includes a novel design of a lightweight hash function for verification of the inferred paths. In order to further improve the inference capability as well as the execution efficiency, iPath includes a fast bootstrapping algorithm to reconstruct the initial set of paths. We also implement iPath and evaluate its performance using traces from large-scale WSN deployments as well as extensive simulations. Results show that iPath achieves much higher reconstruction ratios under different network settings compared to other state-of-the-art approaches.

Opportunistic Routing With Congestion Diversity in Wireless Ad Hoc Networks

We consider the problem of routing packets across a multi-hop network consisting of multiple sources of traffic and wireless links while ensuring bounded expected delay. Each packet transmission can be overheard by a random subset of receiver nodes among which the next relay is selected opportunistically. The main challenge in the design of minimum-delay routing policies is balancing the trade-off between routing the packets along the shortest paths to the destination and distributing the traffic according to the maximum backpressure. Combining important aspects of shortest path and backpressure routing, this paper provides a systematic development of a distributed opportunistic routing policy with congestion diversity (D-ORCD). D-ORCD uses a measure of draining time to opportunistically identify and route packets along the paths with an expected low overall congestion. D-ORCD with single destination is proved to ensure a bounded expected delay for all networks and under any admissible traffic, so long as the rate of computations is sufficiently fast relative to traffic statistics. Furthermore, this paper proposes a practical implementation of D-ORCD which empirically optimizes critical algorithm parameters and their effects on delay as well as protocol overhead. Realistic QualNet simulations for 802.11-based networks demonstrate a significant improvement in the average delay over comparable solutions in the literatur.

Spatial Reusability-Aware Routing in Multi-Hop Wireless Networks

In the problem of routing in multi-hop wireless networks, to achieve high end-to-end throughput, it is crucial to find the “best” path from the source node to the destination node. Although a large number of routing protocols have been proposed to find the path with minimum total transmission count/time for delivering a single packet, such transmission count/time minimizing protocols cannot be guaranteed to achieve maximum end-to-end throughput. In this paper, we argue that by carefully considering spatial reusability of the wireless communication media, we can tremendously improve the end-to-end throughput in multi-hop wireless networks. To support our argument, we propose spatial reusability-aware single-path routing (SASR) and anypath routing (SAAR) protocols, and compare them with existing single-path routing and anypath routing protocols, respectively. Our evaluation results show that our protocols significantly improve the end-to-end throughput compared with existing protocols. Specifically, for single-path routing, the median throughput gain is up to 60 percent, and for each source-destination pair, the throughput gain is as high as 5:3_; for anypath routing, the maximum per-flow throughput gain is 71.6 percent, while the median gain is up to 13.2 percent.

STAMP: Enabling Privacy-Preserving Location Proofs for Mobile Users

ABSTRACT:

Location-based services are quickly becoming immensely popular. In addition to services based on users' current location, many potential services rely on users' location history, or their spatial-temporal provenance. Malicious users may lie about their spatial-temporal provenance without a carefully designed security system for users to prove their past locations. In this paper, we present the Spatial-Temporal provenance Assurance with Mutual Proofs (STAMP) scheme. STAMP is designed for ad-hoc mobile users generating location proofs for each other in a distributed setting. However, it can easily accommodate trusted mobile users and wireless access points. STAMP ensures the integrity and non-transferability of the location proofs and protects users' privacy. A semi-trusted Certification Authority is used to distribute cryptographic keys as well as guard users against collusion by a light-weight entropy-based trust evaluation approach. Our prototype implementation on the Android platform shows that STAMP is low-cost in terms of computational and storage resources. Extensive simulation experiments show that our entropy-based trust model is able to achieve high collusion detection accuracy.

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Thursday, November 20, 2014


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