Biblio

Wireless Sensor Networks (WSNs) are deployed to monitor the assets (endangered species) and report the locations of these assets to the Base Station (BS) also known as Sink. The hunter (adversary) attacks the network at one or two hops away from the Sink, eavesdrops the wireless communication links and traces back to the location of the asset to capture them. The existing solutions proposed to preserve the privacy of the assets lack in energy efficiency as they rely on random walk routing technique and fake packet injection technique so as to obfuscate the hunter from locating the assets. In this paper we present an energy efficient privacy preserved routing algorithm where the event (i.e., asset) detected nodes called as source nodes report the events' location information to the Base Station using phantom source (also known as phantom node) concept and a-angle anonymity concept. Routing is done using existing greedy routing protocol. Comparison through simulations shows that our solution reduces the energy consumption and delay while maintaining the same level of privacy as that of two existing popular techniques.
 

Demand Response (DR) is a promising technology for meeting the world's ever increasing energy demands without corresponding increase in energy generation, and for providing a sustainable alternative for integrating renewables into the power grid. As a result, interest in automated DR is increasing globally and has led to the development of OpenADR, an internationally recognized standard. In this paper, we propose security-enhancement mechanisms to provide DR participants with verifiable information that they can use to make informed decisions about the validity of received DR event information.

Cloud computing is one of the emerging computing technology where costs are directly proportional to usage and demand. The advantages of this technology are the reasons of security and privacy problems. The data belongs to the users are stored in some cloud servers which is not under their own control. So the cloud services are required to authenticate the user. In general, most of the cloud authentication algorithms do not provide anonymity of the users. The cloud provider can track the users easily. The privacy and authenticity are two critical issues of cloud security. In this paper, we propose a secure anonymous authentication method for cloud services using identity based group signature which allows the cloud users to prove that they have privilege to access the data without revealing their identities.

In bound applications, the locations of events reportable by a device network have to be compelled to stay anonymous. That is, unauthorized observers should be unable to notice the origin of such events by analyzing the network traffic. The authors analyze 2 forms of downsides: Communication overhead and machine load problem. During this paper, the authors give a new framework for modeling, analyzing, and evaluating obscurity in device networks. The novelty of the proposed framework is twofold: initial, it introduces the notion of "interval indistinguishability" and provides a quantitative live to model obscurity in wireless device networks; second, it maps supply obscurity to the applied mathematics downside the authors showed that the present approaches for coming up with statistically anonymous systems introduce correlation in real intervals whereas faux area unit unrelated. The authors show however mapping supply obscurity to consecutive hypothesis testing with nuisance Parameters ends up in changing the matter of exposing non-public supply data into checking out associate degree applicable knowledge transformation that removes or minimize the impact of the nuisance data victimization sturdy cryptography algorithmic rule. By doing therefore, the authors remodeled the matter of analyzing real valued sample points to binary codes, that opens the door for committal to writing theory to be incorporated into the study of anonymous networks. In existing work, unable to notice unauthorized observer in network traffic. However this work in the main supported enhances their supply obscurity against correlation check, the most goal of supply location privacy is to cover the existence of real events.

Vehicle-to-grid (V2G), involving both charging and discharging of battery vehicles (BVs), enhances the smart grid substantially to alleviate peaks in power consumption. In a V2G scenario, the communications between BVs and power grid may confront severe cyber security vulnerabilities. Traditionally, authentication mechanisms are solely designed for the BVs when they charge electricity as energy customers. In this paper, we first show that, when a BV interacts with the power grid, it may act in one of three roles: 1) energy demand (i.e., a customer); 2) energy storage; and 3) energy supply (i.e., a generator). In each role, we further demonstrate that the BV has dissimilar security and privacy concerns. Hence, the traditional approach that only considers BVs as energy customers is not universally applicable for the interactions in the smart grid. To address this new security challenge, we propose a role-dependent privacy preservation scheme (ROPS) to achieve secure interactions between a BV and power grid. In the ROPS, a set of interlinked subprotocols is proposed to incorporate different privacy considerations when a BV acts as a customer, storage, or a generator. We also outline both centralized and distributed discharging operations when a BV feeds energy back into the grid. Finally, security analysis is performed to indicate that the proposed ROPS owns required security and privacy properties and can be a highly potential security solution for V2G networks in the smart grid. The identified security challenge as well as the proposed ROPS scheme indicates that role-awareness is crucial for secure V2G networks.

This paper proposes a novel wireless MAC-layer approach towards achieving channel access anonymity. Nodes autonomously select periodic TDMA-like time-slots for channel access by employing a novel channel sensing strategy, and they do so without explicitly sharing any identity information with other nodes in the network. An add-on hardware module for the proposed channel sensing has been developed and the proposed protocol has been implemented in Tinyos-2.x. Extensive evaluation has been done on a test-bed consisting of Mica2 hardware, where we have studied the protocol's functionality and convergence characteristics. The functionality results collected at a sniffer node using RSSI traces validate the syntax and semantics of the protocol. Experimentally evaluated convergence characteristics from the Tinyos test-bed were also found to be satisfactory.

The video surveillance widely installed in public areas poses a significant threat to the privacy. This paper proposes a new privacy preserving method via the Generalized Random-Grid based Visual Cryptography Scheme (GRG-based VCS). We first separate the foreground from the background for each video frame. These foreground pixels contain the most important information that needs to be protected. Every foreground area is encrypted into two shares based on GRG-based VCS. One share is taken as the foreground, and the other one is embedded into another frame with random selection. The content of foreground can only be recovered when these two shares are got together. The performance evaluation on several surveillance scenarios demonstrates that our proposed method can effectively protect sensitive privacy information in surveillance videos.

The wireless network is become larger than past. So in the recent years the wireless with multiple sinks is more useful. The anonymity and privacy in this network is a challenge now. In this paper, we propose a new method for anonymity in multi sink wireless sensor network. In this method we use layer encryption to provide source and event privacy and we use a label switching routing method to provide sink anonymity in each cluster. A master sink that is a powerful base station is used to connect sinks to each other.

Security threats are irregular, sometimes very sophisticated, and difficult to measure in an economic sense. Much published data about them comes from either anecdotes or surveys and is often either not quantified or not quantified in a way that's comparable across organizations. It's hard even to separate the increase in actual danger from year to year from the increase in the perception of danger from year to year. Staffing to meet these threats is still more a matter of judgment than science, and in particular, optimizing staff allocation will likely leave your organization vulnerable at the worst times.

Aside from massive advantages in safety and convenience on the road, Vehicular Ad Hoc Networks (VANETs) introduce security risks to the users. Proposals of new security concepts to counter these risks are challenging to verify because of missing real world implementations of VANETs. To fill this gap, we introduce VANETsim, an event-driven simulation platform, specifically designed to investigate application-level privacy and security implications in vehicular communications. VANETsim focuses on realistic vehicular movement on real road networks and communication between the moving nodes. A powerful graphical user interface and an experimentation environment supports the user when setting up or carrying out experiments.

In a converging world, where borders between countries are surpassed in the digital environment, it is necessary to develop systems that effectively replace the recognition “vis-a-vis” with digital means of recognizing and identifying entities and people. In this work we summarize the current standardization efforts in the area of digital identity management. We identify a number of open challenges that need to be addressed in the near future to ensure the interoperability and usability of digital identity management services in an efficient and privacy maintaining international framework. These challenges for standardization include: the management of identifiers for digital identities at the global level; attribute management including attribute format, structure, and assurance; procedures and protocols to link attributes to digital identities. Attention is drawn to key elements that should be considered in addressing these issues through standardization.

We propose a distributed continuous-time algorithm to solve a network optimization problem where the global cost function is a strictly convex function composed of the sum of the local cost functions of the agents. We establish that our algorithm, when implemented over strongly connected and weight-balanced directed graph topologies, converges exponentially fast when the local cost functions are strongly convex and their gradients are globally Lipschitz. We also characterize the privacy preservation properties of our algorithm and extend the convergence guarantees to the case of time-varying, strongly connected, weight-balanced digraphs. When the network topology is a connected undirected graph, we show that exponential convergence is still preserved if the gradients of the strongly convex local cost functions are locally Lipschitz, while it is asymptotic if the local cost functions are convex. We also study discrete-time communication implementations. Specifically, we provide an upper bound on the stepsize of a synchronous periodic communication scheme that guarantees convergence over connected undirected graph topologies and, building on this result, design a centralized event-triggered implementation that is free of Zeno behavior. Simulations illustrate our results.

We propose a distributed continuous-time algorithm to solve a network optimization problem where the global cost function is a strictly convex function composed of the sum of the local cost functions of the agents. We establish that our algorithm, when implemented over strongly connected and weight-balanced directed graph topologies, converges exponentially fast when the local cost functions are strongly convex and their gradients are globally Lipschitz. We also characterize the privacy preservation properties of our algorithm and extend the convergence guarantees to the case of time-varying, strongly connected, weight-balanced digraphs. When the network topology is a connected undirected graph, we show that exponential convergence is still preserved if the gradients of the strongly convex local cost functions are locally Lipschitz, while it is asymptotic if the local cost functions are convex. We also study discrete-time communication implementations. Specifically, we provide an upper bound on the stepsize of a synchronous periodic communication scheme that guarantees convergence over connected undirected graph topologies and, building on this result, design a centralized event-triggered implementation that is free of Zeno behavior. Simulations illustrate our results.

This paper has conducted analyzing the accident case of data spill to study policy issues for ICT security from a social science perspective focusing on risk. The results from case analysis are as follows. First, ICT risk can be categorized 'severe, strong, intensive and individual' from the level of both probability and impact. Second, strategy of risk management can be designated 'avoid, transfer, mitigate, accept' by understanding their own culture type of relative group such as 'hierarchy, egalitarianism, fatalism and individualism'. Third, personal data has contained characteristics of big data such like 'volume, velocity, variety' for each risk situation. Therefore, government needs to establish a standing organization responsible for ICT risk policy and management in a new big data era. And the policy for ICT risk management needs to balance in considering 'technology, norms, laws, and market' in big data era.
 

Big data's explosive growth has prompted the US government to release new reports that address the issues--particularly related to privacy--resulting from this growth. The Web extra at http://youtu.be/j49eoe5g8-c is an audio recording from the Computing and the Law column, in which authors Brian M. Gaff, Heather Egan Sussman, and Jennifer Geetter discuss how big data's explosive growth has prompted the US government to release new reports that address the issues--particularly related to privacy--resulting from this growth.
 

The trend towards Cloud computing infrastructure has increased the need for new methods that allow data owners to share their data with others securely taking into account the needs of multiple stakeholders. The data owner should be able to share confidential data while delegating much of the burden of access control management to the Cloud and trusted enterprises. The lack of such methods to enhance privacy and security may hinder the growth of cloud computing. In particular, there is a growing need to better manage security keys of data shared in the Cloud. BYOD provides a first step to enabling secure and efficient key management, however, the data owner cannot guarantee that the data consumers device itself is secure. Furthermore, in current methods the data owner cannot revoke a particular data consumer or group efficiently. In this paper, we address these issues by incorporating a hardware-based Trusted Platform Module (TPM) mechanism called the Trusted Extension Device (TED) together with our security model and protocol to allow stronger privacy of data compared to software-based security protocols. We demonstrate the concept of using TED for stronger protection and management of cryptographic keys and how our secure data sharing protocol will allow a data owner (e.g, author) to securely store data via untrusted Cloud services. Our work prevents keys to be stolen by outsiders and/or dishonest authorised consumers, thus making it particularly attractive to be implemented in a real-world scenario.

With the rapid advancement in technology and the growing complexities in the interaction of these technologies and networks, it is even more important for countries and organizations to gain sustainable security advantage. Security advantage refers to the ability to manage and respond to threats and vulnerabilities with a proactive security posture. This is accomplished through effectively planning, managing, responding to and recovering from threats and vulnerabilities. However not many organizations and even countries, especially in the developing world, have been able to equip themselves with the necessary and sufficient know-how or ability to integrate knowledge and capabilities to achieve security advantage within their environment. Having a structured set of requirements or indicators to aid in progressively attaining different levels of maturity and capabilities is one important method to determine the state of cybersecurity readiness. The research introduces the Cybersecurity Capability Maturity Model (CM2), a 6-step process of progressive development of cybersecurity maturity and knowledge integration that ranges from a state of limited awareness and application of security controls to pervasive optimization of the protection of critical assets.

With the rapid advancement in technology and the growing complexities in the interaction of these technologies and networks, it is even more important for countries and organizations to gain sustainable security advantage. Security advantage refers to the ability to manage and respond to threats and vulnerabilities with a proactive security posture. This is accomplished through effectively planning, managing, responding to and recovering from threats and vulnerabilities. However not many organizations and even countries, especially in the developing world, have been able to equip themselves with the necessary and sufficient know-how or ability to integrate knowledge and capabilities to achieve security advantage within their environment. Having a structured set of requirements or indicators to aid in progressively attaining different levels of maturity and capabilities is one important method to determine the state of cybersecurity readiness. The research introduces the Cybersecurity Capability Maturity Model (CM2), a 6-step process of progressive development of cybersecurity maturity and knowledge integration that ranges from a state of limited awareness and application of security controls to pervasive optimization of the protection of critical assets.
 

The Internet of Things (IoT) becomes reality. But its restrictions become obvious as we try to connect solutions of different vendors and communities. Apart from communication protocols appropriate identity management mechanisms are crucial for a growing IoT. The recently founded Identities of Things Discussion Group within Kantara Initiative will work on open issues and solutions to manage “Identities of Things” as an enabler for a fast-growing ecosystem.

Using one password for all web services is not secure because the leakage of the password compromises all the web services accounts, while using independent passwords for different web services is inconvenient for the identity claimant to memorize. A password manager is used to address this security-convenience dilemma by storing and retrieving multiple existing passwords using one master password. On the other hand, a password manager liberates human brain by enabling people to generate strong passwords without worry about memorizing them. While a password manager provides a convenient and secure way to managing multiple passwords, it centralizes the passwords storage and shifts the risk of passwords leakage from distributed service providers to a software or token authenticated by a single master password. Concerned about this one master password based security, biometrics could be used as a second factor for authentication by verifying the ownership of the master password. However, biometrics based authentication is more privacy concerned than a non-biometric password manager. In this paper we propose a cloud password manager scheme exploiting privacy enhanced biometrics, which achieves both security and convenience in a privacy-enhanced way. The proposed password manager scheme relies on a cloud service to synchronize all local password manager clients in an encrypted form, which is efficient to deploy the updates and secure against untrusted cloud service providers.

The strong development of the Internet of Things (IoT) is dramatically changing traditional perceptions of the current Internet towards an integrated vision of smart objects interacting with each other. While in recent years many technological challenges have already been solved through the extension and adaptation of wireless technologies, security and privacy still remain as the main barriers for the IoT deployment on a broad scale. In this emerging paradigm, typical scenarios manage particularly sensitive data, and any leakage of information could severely damage the privacy of users. This paper provides a concise description of some of the major challenges related to these areas that still need to be overcome in the coming years for a full acceptance of all IoT stakeholders involved. In addition, we propose a distributed capability-based access control mechanism which is built on public key cryptography in order to cope with some of these challenges. Specifically, our solution is based on the design of a lightweight token used for access to CoAP Resources, and an optimized implementation of the Elliptic Curve Digital Signature Algorithm (ECDSA) inside the smart object. The results obtained from our experiments demonstrate the feasibility of the proposal and show promising in order to cover more complex scenarios in the future, as well as its application in specific IoT use cases.

Vehicular ad-hoc networks (VANETs) provides infrastructure less, rapidly deployable, self-configurable network connectivity. The network is the collection vehicles interlinked by wireless links and willing to store and forward data for their peers. As vehicles move freely and organize themselves arbitrarily, message routing is done dynamically based on network connectivity. Compared with other ad-hoc networks, VANETs are particularly challenging due to the part of the vehicles' high rate of mobility and the numerous signal-weakening barrier, such as buildings, in their environments. Due to their enormous potential, VANET have gained an increasing attention in both industry and academia. Research activities range from lower layer protocol design to applications and implementation issues. A secure VANET system, while exchanging information should protect the system against unauthorized message injection, message alteration, eavesdropping. The security of VANET is one of the most critical issues because their information transmission is propagated in open access (wireless) environments. A few years back VANET has received increased attention as the potential technology to enhance active and preventive safety on the road, as well as travel comfort Safekeeping and privacy are mandatory in vehicular communications for a grateful acceptance and use of such technology. This paper is an attempt to highlight the problems occurred in Vehicular Ad hoc Networks and security issues.

Privacy preservation is very essential in various real life applications such as medical science and financial analysis. This paper focuses on implementation of an asymmetric secure multi-party computation protocol using anonymization and public-key encryption where all parties have access to trusted third party (TTP) who (1) doesn't add any contribution to computation (2) doesn't know who is the owner of the input received (3) has large number of resources (4) decryption key is known to trusted third party (TTP) to get the actual input for computation of final result. In this environment, concern is to design a protocol which deploys TTP for computation. It is proposed that the protocol is very proficient (in terms of secure computation and individual privacy) for the parties than the other available protocols. The solution incorporates protocol using asymmetric encryption scheme where any party can encrypt a message with the public key but decryption can be done by only the possessor of the decryption key (private key). As the protocol works on asymmetric encryption and packetization it ensures following: (1) Confidentiality (Anonymity) (2) Security (3) Privacy (Data).

With the rapid increase in cloud services collecting and using user data to offer personalized experiences, ensuring that these services comply with their privacy policies has become a business imperative for building user trust. However, most compliance efforts in industry today rely on manual review processes and audits designed to safeguard user data, and therefore are resource intensive and lack coverage. In this paper, we present our experience building and operating a system to automate privacy policy compliance checking in Bing. Central to the design of the system are (a) Legal ease-a language that allows specification of privacy policies that impose restrictions on how user data is handled, and (b) Grok-a data inventory for Map-Reduce-like big data systems that tracks how user data flows among programs. Grok maps code-level schema elements to data types in Legal ease, in essence, annotating existing programs with information flow types with minimal human input. Compliance checking is thus reduced to information flow analysis of Big Data systems. The system, bootstrapped by a small team, checks compliance daily of millions of lines of ever-changing source code written by several thousand developers.

Identity verification plays an important role in creating trust in the economic system. It can, and should, be done in a way that doesn't decrease individual privacy.