293 resultados para Computer networks -- Security measures


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Current IEEE 802.11 wireless networks are vulnerable to session hijacking attacks as the existing standards fail to address the lack of authentication of management frames and network card addresses, and rely on loosely coupled state machines. Even the new WLAN security standard - IEEE 802.11i does not address these issues. In our previous work, we proposed two new techniques for improving detection of session hijacking attacks that are passive, computationally inexpensive, reliable, and have minimal impact on network performance. These techniques utilise unspoofable characteristics from the MAC protocol and the physical layer to enhance confidence in the intrusion detection process. This paper extends our earlier work and explores usability, robustness and accuracy of these intrusion detection techniques by applying them to eight distinct test scenarios. A correlation engine has also been introduced to maintain the false positives and false negatives at a manageable level. We also explore the process of selecting optimum thresholds for both detection techniques. For the purposes of our experiments, Snort-Wireless open source wireless intrusion detection system was extended to implement these new techniques and the correlation engine. Absence of any false negatives and low number of false positives in all eight test scenarios successfully demonstrated the effectiveness of the correlation engine and the accuracy of the detection techniques.

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Discrete event-driven simulations of digital communication networks have been used widely. However, it is difficult to use a network simulator to simulate a hybrid system in which some objects are not discrete event-driven but are continuous time-driven. A networked control system (NCS) is such an application, in which physical process dynamics are continuous by nature. We have designed and implemented a hybrid simulation environment which effectively integrates models of continuous-time plant processes and discrete-event communication networks by extending the open source network simulator NS-2. To do this a synchronisation mechanism was developed to connect a continuous plant simulation with a discrete network simulation. Furthermore, for evaluating co-design approaches in an NCS environment, a piggybacking method was adopted to allow the control period to be adjusted during simulations. The effectiveness of the technique is demonstrated through case studies which simulate a networked control scenario in which the communication and control system properties are defined explicitly.

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Performance evaluation of object tracking systems is typically performed after the data has been processed, by comparing tracking results to ground truth. Whilst this approach is fine when performing offline testing, it does not allow for real-time analysis of the systems performance, which may be of use for live systems to either automatically tune the system or report reliability. In this paper, we propose three metrics that can be used to dynamically asses the performance of an object tracking system. Outputs and results from various stages in the tracking system are used to obtain measures that indicate the performance of motion segmentation, object detection and object matching. The proposed dynamic metrics are shown to accurately indicate tracking errors when visually comparing metric results to tracking output, and are shown to display similar trends to the ETISEO metrics when comparing different tracking configurations.

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Alzaid et al. proposed a forward & backward secure key management scheme in wireless sensor networks for Process Control Systems (PCSs) or Supervisory Control and Data Acquisition (SCADA) systems. The scheme, however, is still vulnerable to an attack called the sandwich attack that can be launched when the adversary captures two sensor nodes at times t1 and t2, and then reveals all the group keys used between times t1 and t2. In this paper, a fix to the scheme is proposed in order to limit the vulnerable time duration to an arbitrarily chosen time span while keeping the forward and backward secrecy of the scheme untouched. Then, the performance analysis for our proposal, Alzaid et al.’s scheme, and Nilsson et al.’s scheme is given.

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We describe the design and implementation of a public-key platform, secFleck, based on a commodity Trusted Platform Module (TPM) chip that extends the capability of a standard node. Unlike previous software public-key implementations this approach provides E- Commerce grade security; is computationally fast, energy efficient; and has low financial cost — all essential attributes for secure large-scale sen- sor networks. We describe the secFleck message security services such as confidentiality, authenticity and integrity, and present performance re- sults including computation time, energy consumption and cost. This is followed by examples, built on secFleck, of symmetric key management, secure RPC and secure software update.

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RFID has been widely used in today's commercial and supply chain industry, due to the significant advantages it offers and the relatively low production cost. However, this ubiquitous technology has inherent problems in security and privacy. This calls for the development of simple, efficient and cost effective mechanisms against a variety of security threats. This paper proposes a two-step authentication protocol based on the randomized hash-lock scheme proposed by S. Weis in 2003. By introducing additional measures during the authentication process, this new protocol proves to enhance the security of RFID significantly, and protects the passive tags from almost all major attacks, including tag cloning, replay, full-disclosure, tracking, and eavesdropping. Furthermore, no significant changes to the tags is required to implement this protocol, and the low complexity level of the randomized hash-lock algorithm is retained.

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Wireless Multi-media Sensor Networks (WMSNs) have become increasingly popular in recent years, driven in part by the increasing commoditization of small, low-cost CMOS sensors. As such, the challenge of automatically calibrating these types of cameras nodes has become an important research problem, especially for the case when a large quantity of these type of devices are deployed. This paper presents a method for automatically calibrating a wireless camera node with the ability to rotate around one axis. The method involves capturing images as the camera is rotated and computing the homographies between the images. The camera parameters, including focal length, principal point and the angle and axis of rotation can then recovered from two or more homographies. The homography computation algorithm is designed to deal with the limited resources of the wireless sensor and to minimize energy con- sumption. In this paper, a modified RANdom SAmple Consensus (RANSAC) algorithm is proposed to effectively increase the efficiency and reliability of the calibration procedure.

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Before making a security or privacy decision, Internet users should evaluate several security indicators in their browser, such as the use of HTTPS (indicated via the lock icon), the domain name of the site, and information from extended validation certificates. However, studies have shown that human subjects infrequently employ these indicators, relying on other indicators that can be spoofed and convey no cryptographic assurances. We identify four simple security indicators that accurately represent security properties of the connection and then examine 125 popular websites to determine if the sites' designs result in correctly displayed security indicators during login. In the vast majority of cases, at least some security indicators are absent or suboptimal. This suggests users are becoming habituated to ignoring recommended security indicators.

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We consider the problem of object tracking in a wireless multimedia sensor network (we mainly focus on the camera component in this work). The vast majority of current object tracking techniques, either centralised or distributed, assume unlimited energy, meaning these techniques don't translate well when applied within the constraints of low-power distributed systems. In this paper we develop and analyse a highly-scalable, distributed strategy to object tracking in wireless camera networks with limited resources. In the proposed system, cameras transmit descriptions of objects to a subset of neighbours, determined using a predictive forwarding strategy. The received descriptions are then matched at the next camera on the objects path using a probability maximisation process with locally generated descriptions. We show, via simulation, that our predictive forwarding and probabilistic matching strategy can significantly reduce the number of object-misses, ID-switches and ID-losses; it can also reduce the number of required transmissions over a simple broadcast scenario by up to 67%. We show that our system performs well under realistic assumptions about matching objects appearance using colour.

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We describe a novel two stage approach to object localization and tracking using a network of wireless cameras and a mobile robot. In the first stage, a robot travels through the camera network while updating its position in a global coordinate frame which it broadcasts to the cameras. The cameras use this information, along with image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to track the objects. We present results with a nine node indoor camera network to demonstrate that this approach is feasible and offers acceptable level of accuracy in terms of object locations.

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Online social networking has become one of the most popular Internet applications in the modern era. They have given the Internet users, access to information that other Internet based applications are unable to. Although many of the popular online social networking web sites are focused towards entertainment purposes, sharing information can benefit the healthcare industry in terms of both efficiency and effectiveness. But the capability to share personal information; the factor which has made online social networks so popular, is itself a major obstacle when considering information security and privacy aspects. Healthcare can benefit from online social networking if they are implemented such that sensitive patient information can be safeguarded from ill exposure. But in an industry such as healthcare where the availability of information is crucial for better decision making, information must be made available to the appropriate parties when they require it. Hence the traditional mechanisms for information security and privacy protection may not be suitable for healthcare. In this paper we propose a solution to privacy enhancement in online healthcare social networks through the use of an information accountability mechanism.

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Secure communications in wireless sensor networks operating under adversarial conditions require providing pairwise (symmetric) keys to sensor nodes. In large scale deployment scenarios, there is no prior knowledge of post deployment network configuration since nodes may be randomly scattered over a hostile territory. Thus, shared keys must be distributed before deployment to provide each node a key-chain. For large sensor networks it is infeasible to store a unique key for all other nodes in the key-chain of a sensor node. Consequently, for secure communication either two nodes have a key in common in their key-chains and they have a wireless link between them, or there is a path, called key-path, among these two nodes where each pair of neighboring nodes on this path have a key in common. Length of the key-path is the key factor for efficiency of the design. This paper presents novel deterministic and hybrid approaches based on Combinatorial Design for deciding how many and which keys to assign to each key-chain before the sensor network deployment. In particular, Balanced Incomplete Block Designs (BIBD) and Generalized Quadrangles (GQ) are mapped to obtain efficient key distribution schemes. Performance and security properties of the proposed schemes are studied both analytically and computationally. Comparison to related work shows that the combinatorial approach produces better connectivity with smaller key-chain sizes.

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A Delay Tolerant Network (DTN) is one where nodes can be highly mobile, with long message delay times forming dynamic and fragmented networks. Traditional centralised network security is difficult to implement in such a network, therefore distributed security solutions are more desirable in DTN implementations. Establishing effective trust in distributed systems with no centralised Public Key Infrastructure (PKI) such as the Pretty Good Privacy (PGP) scheme usually requires human intervention. Our aim is to build and compare different de- centralised trust systems for implementation in autonomous DTN systems. In this paper, we utilise a key distribution model based on the Web of Trust principle, and employ a simple leverage of common friends trust system to establish initial trust in autonomous DTN’s. We compare this system with two other methods of autonomously establishing initial trust by introducing a malicious node and measuring the distribution of malicious and fake keys. Our results show that the new trust system not only mitigates the distribution of fake malicious keys by 40% at the end of the simulation, but it also improved key distribution between nodes. This paper contributes a comparison of three de-centralised trust systems that can be employed in autonomous DTN systems.

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Grouping users in social networks is an important process that improves matching and recommendation activities in social networks. The data mining methods of clustering can be used in grouping the users in social networks. However, the existing general purpose clustering algorithms perform poorly on the social network data due to the special nature of users' data in social networks. One main reason is the constraints that need to be considered in grouping users in social networks. Another reason is the need of capturing large amount of information about users which imposes computational complexity to an algorithm. In this paper, we propose a scalable and effective constraint-based clustering algorithm based on a global similarity measure that takes into consideration the users' constraints and their importance in social networks. Each constraint's importance is calculated based on the occurrence of this constraint in the dataset. Performance of the algorithm is demonstrated on a dataset obtained from an online dating website using internal and external evaluation measures. Results show that the proposed algorithm is able to increases the accuracy of matching users in social networks by 10% in comparison to other algorithms.

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The IEEE Wireless LAN standard has been a true success story by enabling convenient, efficient and low-cost access to broadband networks for both private and professional use. However, the increasing density and uncoordinated operation of wireless access points, combined with constantly growing traffic demands have started hurting the users' quality of experience. On the other hand, the emerging ubiquity of wireless access has placed it at the center of attention for network attacks, which not only raises users' concerns on security but also indirectly affects connection quality due to proactive measures against security attacks. In this work, we introduce an integrated solution to congestion avoidance and attack mitigation problems through cooperation among wireless access points. The proposed solution implements a Partially Observable Markov Decision Process (POMDP) as an intelligent distributed control system. By successfully differentiating resource hampering attacks from overload cases, the control system takes an appropriate action in each detected anomaly case without disturbing the quality of service for end users. The proposed solution is fully implemented on a small-scale testbed, on which we present our observations and demonstrate the effectiveness of the system to detect and alleviate both attack and congestion situations.