Biblio

Unmanned Aerial Systems (UAS) have raised a great concern on privacy recently. A practical method to protect privacy is needed for adopting UAS in civilian airspace. This paper examines the privacy policies, filtering strategies, existing techniques, then proposes a novel method based on the encrypted video stream and the cloud-based privacy servers. In this scheme, all video surveillance images are initially encrypted, then delivered to a privacy server. The privacy server decrypts the video using the shared key with the camera, and filters the image according to the privacy policy specified for the surveyed region. The sanitized video is delivered to the surveillance operator or anyone on the Internet who is authorized. In a larger system composed of multiple cameras and multiple privacy servers, the keys can be distributed using Kerberos protocol. With this method the privacy policy can be changed on demand in real-time and there is no need for a costly on-board processing unit. By utilizing the cloud-based servers, advanced image processing algorithms and new filtering algorithms can be applied immediately without upgrading the camera software. This method is cost-efficient and promotes video sharing among multiple subscribers, thus it can spur wide adoption.

The term Cloud Computing is not something that appeared overnight, it may come from the time when computer system remotely accessed the applications and services. Cloud computing is Ubiquitous technology and receiving a huge attention in the scientific and industrial community. Cloud computing is ubiquitous, next generation's in-formation technology architecture which offers on-demand access to the network. It is dynamic, virtualized, scalable and pay per use model over internet. In a cloud computing environment, a cloud service provider offers “house of resources” includes applications, data, runtime, middleware, operating system, virtualization, servers, data storage and sharing and networking and tries to take up most of the overhead of client. Cloud computing offers lots of benefits, but the journey of the cloud is not very easy. It has several pitfalls along the road because most of the services are outsourced to third parties with added enough level of risk. Cloud computing is suffering from several issues and one of the most significant is Security, privacy, service availability, confidentiality, integrity, authentication, and compliance. Security is a shared responsibility of both client and service provider and we believe security must be information centric, adaptive, proactive and built in. Cloud computing and its security are emerging study area nowadays. In this paper, we are discussing about data security in cloud at the service provider end and proposing a network storage architecture of data which make sure availability, reliability, scalability and security.

The term Cloud Computing is not something that appeared overnight, it may come from the time when computer system remotely accessed the applications and services. Cloud computing is Ubiquitous technology and receiving a huge attention in the scientific and industrial community. Cloud computing is ubiquitous, next generation's in-formation technology architecture which offers on-demand access to the network. It is dynamic, virtualized, scalable and pay per use model over internet. In a cloud computing environment, a cloud service provider offers “house of resources” includes applications, data, runtime, middleware, operating system, virtualization, servers, data storage and sharing and networking and tries to take up most of the overhead of client. Cloud computing offers lots of benefits, but the journey of the cloud is not very easy. It has several pitfalls along the road because most of the services are outsourced to third parties with added enough level of risk. Cloud computing is suffering from several issues and one of the most significant is Security, privacy, service availability, confidentiality, integrity, authentication, and compliance. Security is a shared responsibility of both client and service provider and we believe security must be information centric, adaptive, proactive and built in. Cloud computing and its security are emerging study area nowadays. In this paper, we are discussing about data security in cloud at the service provider end and proposing a network storage architecture of data which make sure availability, reliability, scalability and security.

Although there has been much research on the leakage of sensitive data in Android applications, most of the existing research focus on how to detect the malware or adware that are intentionally collecting user privacy. There are not much research on analyzing the vulnerabilities of apps that may cause the leakage of privacy. In this paper, we present a vulnerability analyzing method which combines taint analysis and cryptography misuse detection. The four steps of this method are decompile, taint analysis, API call record, cryptography misuse analysis, all of which steps except taint analysis can be executed by the existing tools. We develop a prototype tool PW Exam to analysis how the passwords are handled and if the app is vulnerable to password leakage. Our experiment shows that a third of apps are vulnerable to leak the users' passwords.

In era of information age, due to different electronic, information & communication technology devices and process like sensors, cloud, individual archives, social networks, internet activities and enterprise data are growing exponentially. The most challenging issues are how to effectively manage these large and different type of data. Big data is one of the term named for this large and different type of data. Due to its extraordinary scale, privacy and security is one of the critical challenge of big data. At the every stage of managing the big data there are chances that privacy may be disclose. Many techniques have been suggested and implemented for privacy preservation of large data set like anonymization based, encryption based and others but unfortunately due to different characteristic (large volume, high speed, and unstructured data) of big data all these techniques are not fully suitable. In this paper we have deeply analyzed, discussed and suggested how an existing approach "differential privacy" is suitable for big data. Initially we have discussed about differential privacy and later analyze how it is suitable for big data.

As the cornerstone of the future intelligent transportation system, vehicular ad hoc networks (VANETs) have attracted intensive attention from the academic and industrial research communities in recent years. For widespread deployment of VANETs, security and privacy issues must be addressed properly. In this paper, we introduce the notion of pseudonym-based cryptography, and present a provable secure pseudonym-based cryptosystems with a trusted authority that includes a pseudonym-based multi-receiver encryption scheme, a pseudonym-based signature scheme, and a pseudonym-based key establishment protocol. We then propose a secure and efficient data access scheme for VANETs based on cooperative caching technology and our proposed pseudonym-based cryptosystems. On the one hand, the efficiency of data access are greatly improved by allowing the sharing and coordination of cached data among multiple vehicles. On the other hand, anonymity of the vehicles, data confidentiality, integrity and non-repudiation are guaranteed by employing our proposed pseudonym-based cryptosystems. Simulation results have shown that our proposed pseudonym-based cryptosystems are suitable to the VANETs environment.

In large-scale systems, user authentication usually needs the assistance from a remote central authentication server via networks. The authentication service however could be slow or unavailable due to natural disasters or various cyber attacks on communication channels. This has raised serious concerns in systems which need robust authentication in emergency situations. The contribution of this paper is two-fold. In a slow connection situation, we present a secure generic multi-factor authentication protocol to speed up the whole authentication process. Compared with another generic protocol in the literature, the new proposal provides the same function with significant improvements in computation and communication. Another authentication mechanism, which we name stand-alone authentication, can authenticate users when the connection to the central server is down. We investigate several issues in stand-alone authentication and show how to add it on multi-factor authentication protocols in an efficient and generic way.

Electric vehicle is the automobile that powered by electrical energy stored in batteries. Due to the frequent recharging, vehicles need to be connected to the recharging infrastructure while they are parked. This may disclose drivers' privacy, such as their location that drivers may want to keep secret. In this paper, we propose a scheme to enhance the privacy of the drivers using anonymous credential technique and Trusted Platform Module(TPM). We use anonymous credential technique to achieve the anonymity of vehicles such that drivers can anonymously and unlinkably recharge their vehicles. We add some attributes to the credential such as the type of the battery in the vehicle in case that the prices of different batteries are different. We use TPM to omit a blacklist such that the company that offer the recharging service(Energy Provider Company, EPC) does not need to conduct a double spending detection.
 

In this paper we introduce PADAVAN, a novel anonymous data collection scheme for Vehicular Ad Hoc Networks (VANETs). PADAVAN allows users to submit data anonymously to a data consumer while preventing adversaries from submitting large amounts of bogus data. PADAVAN is comprised of an n-times anonymous authentication scheme, mix cascades and various principles to protect the privacy of the submitted data itself. Furthermore, we evaluate the effectiveness of limiting an adversary to a fixed amount of messages.

Data is one of the most valuable assets for organization. It can facilitate users or organizations to meet their diverse goals, ranging from scientific advances to business intelligence. Due to the tremendous growth of data, the notion of big data has certainly gained momentum in recent years. Cloud computing is a key technology for storing, managing and analyzing big data. However, such large, complex, and growing data, typically collected from various data sources, such as sensors and social media, can often contain personally identifiable information (PII) and thus the organizations collecting the big data may want to protect their outsourced data from the cloud. In this paper, we survey our research towards development of efficient and effective privacy-enhancing (PE) techniques for management and analysis of big data in cloud computing.We propose our initial approaches to address two important PE applications: (i) privacy-preserving data management and (ii) privacy-preserving data analysis under the cloud environment. Additionally, we point out research issues that still need to be addressed to develop comprehensive solutions to the problem of effective and efficient privacy-preserving use of data.
 

Our vision in this paper is that agency, as the individual ability to intervene and tailor the system, is a crucial element in building trust in IoT technologies. Following up on this vision, we will first address the issue of agency, namely the individual capability to adopt free decisions, as a relevant driver in building trusted human-IoT relations, and how agency should be embedded in digital systems. Then we present the main challenges posed by existing approaches to implement this vision. We show then our proposal for a model-based approach that realizes the agency concept, including a prototype implementation.

It can get the user's privacy and home energy use information by analyzing the user's electrical load information in smart grid, and this is an area of concern. A rechargeable battery may be used in the home network to protect user's privacy. In this paper, the battery can neither charge nor discharge, and the power of battery is adjustable, at the same time, we model the real user's electrical load information and the battery power information and the recorded electrical power of smart meters which are processed with discrete way. Then we put forward a heuristic algorithm which can make the rate of information leakage less than existing solutions. We use statistical methods to protect user's privacy, the theoretical analysis and the examples show that our solution makes the scene design more reasonable and is more effective than existing solutions to avoid the leakage of the privacy.

Privacy has become a critical topic in the engineering of electric systems. This work proposes an approach for smart-grid-specific privacy requirements engineering by extending previous general privacy requirements engineering frameworks. The proposed extension goes one step further by focusing on privacy in the smart grid. An alignment of smart grid privacy requirements, dependability issues and privacy requirements engineering methods is presented. Starting from this alignment a Threat Tree Analysis is performed to obtain a first set of generic, high level privacy requirements. This set is formulated mostly on the data instead of the information level and provides the basis for further project-specific refinement.

Despite the benefits offered by smart grids, energy producers, distributors and consumers are increasingly concerned about possible security and privacy threats. These threats typically manifest themselves at runtime as new usage scenarios arise and vulnerabilities are discovered. Adaptive security and privacy promise to address these threats by increasing awareness and automating prevention, detection and recovery from security and privacy requirements' failures at runtime by re-configuring system controls and perhaps even changing requirements. This paper discusses the need for adaptive security and privacy in smart grids by presenting some motivating scenarios. We then outline some research issues that arise in engineering adaptive security. We particularly scrutinize published reports by NIST on smart grid security and privacy as the basis for our discussions.

In this paper, we implemented a mobile augmented reality system based on cloud computing. This system uses a mobile device with a camera to capture images of book spines and sends processed features to the cloud. In the cloud, the features are compared with the database and the information of the best matched book would be sent back to the mobile device. The information will then be rendered on the display via augmented reality. In order to reduce the transmission cost, the mobile device is used to perform most of the image processing tasks, such as the preprocessing, resizing, corner detection, and augmented reality rendering. On the other hand, the cloud is used to realize routine but large quantity feature comparisons. Using the cloud as the database also makes the future extension much more easily. For our prototype system, we use an Android smart phone as our mobile device, and Chunghwa Telecoms hicloud as the cloud.

Smart mobile devices such as smartphones and tablets have become an integral part of our society. However, it also becomes a prime target for attackers with malicious intents. There have been a number of efforts on developing innovative courseware to promote cybersecurity education and to improve student learning; however, hands-on labs are not well developed for smart mobile devices and for mobile security topics. In this paper, we propose to design and develop a mobile security labware with smart mobile devices to promote the cybersecurity education. The integration of mobile computing technologies and smart devices into cybersecurity education will connect the education to leading-edge information technologies, motivate and engage students in security learning, fill in the gap with IT industry need, and help faculties build expertise on mobile computing. In addition, the hands-on experience with mobile app development will promote student learning and supply them with a better understanding of security knowledge not only in classical security domains but also in the emerging mobile security areas.

We consider the setting of HTTP traffic over encrypted tunnels, as used to conceal the identity of websites visited by a user. It is well known that traffic analysis (TA) attacks can accurately identify the website a user visits despite the use of encryption, and previous work has looked at specific attack/countermeasure pairings. We provide the first comprehensive analysis of general-purpose TA countermeasures. We show that nine known countermeasures are vulnerable to simple attacks that exploit coarse features of traffic (e.g., total time and bandwidth). The considered countermeasures include ones like those standardized by TLS, SSH, and IPsec, and even more complex ones like the traffic morphing scheme of Wright et al. As just one of our results, we show that despite the use of traffic morphing, one can use only total upstream and downstream bandwidth to identify – with 98% accuracy - which of two websites was visited. One implication of what we find is that, in the context of website identification, it is unlikely that bandwidth-efficient, general-purpose TA countermeasures can ever provide the type of security targeted in prior work.

The home computer user is often said to be the weakest link in computer security. They do not always follow security advice, and they take actions, as in phishing, that compromise themselves. In general, we do not understand why users do not always behave safely, which would seem to be in their best interest. This paper reviews the literature of surveys and studies of factors that influence security decisions for home computer users. We organize the review in four sections: understanding of threats, perceptions of risky behavior, efforts to avoid security breaches and attitudes to security interventions. We find that these studies reveal a lot of reasons why current security measures may not match the needs or abilities of home computer users and suggest future work needed to inform how security is delivered to this user group.

In the early days of the web, content was designed and hosted by a single person, group, or organization. No longer. Webpages are increasingly composed of content from myriad unrelated "third-party" websites in the business of advertising, analytics, social networking, and more. Third-party services have tremendous value: they support free content and facilitate web innovation. But third-party services come at a privacy cost: researchers, civil society organizations, and policymakers have increasingly called attention to how third parties can track a user's browsing activities across websites. This paper surveys the current policy debate surrounding third-party web tracking and explains the relevant technology. It also presents the FourthParty web measurement platform and studies we have conducted with it. Our aim is to inform researchers with essential background and tools for contributing to public understanding and policy debates about web tracking.

What does it mean to trust, or not trust, an augmented reality system? Froma computer security point of view, trust in augmented reality represents a real threat to real people. The fact that augmented reality allows the programmer to tinker with the user's senses creates many opportunities for malfeasance. It might be natural to think that if we warn users to be careful it will lower their trust in the system, greatly reducing risk.

Protecting critical infrastructure from cyberattacks by other nations is a matter of considerable concern. Can deterrence play a role in such protection? Can lessons from nuclear deterrence-the most elaborated and successful version of deterrence-be adapted to the cyber case? Currently, little overlap exists between the two, although that might change in the aftermath of an extensive, destructive cyberattack. The most effective way to protect the cyber-dependent infrastructure is a comprehensive defense (deterrence by denial), which was impractical in the nuclear regime. However, this approach presents challenges. Existing legal norms, particularly those related to controlling collateral damage, might provide some deterrence. Another option might be a new international agreement, but that would involve several difficult issues.

Protecting energy consumers's data and privacy is a key factor for the further adoption and diffusion of smart grid technologies and applications. However, current smart grid initiatives and implementations around the globe tend to either focus on the need for technical security to the detriment of privacy or consider privacy as a feature to add after system design. This paper aims to contribute towards filling the gap between this fact and the accepted wisdom that privacy concerns should be addressed as early as possible (preferably when modeling system's requirements). We present a methodological framework for tackling privacy concerns throughout all phases of the smart grid system development process. We describe methods and guiding principles to help smart grid engineers to elicit and analyze privacy threats and requirements from the outset of the system development, and derive the best suitable countermeasures, i.e. privacy enhancing technologies (PETs), accordingly. The paper also provides a summary of modern PETs, and discusses their context of use and contributions with respect to the underlying privacy engineering challenges and the smart grid setting being considered.

Anonymous communications networks, such as Tor, help to solve the real and important problem of enabling users to communicate privately over the Internet. However, in doing so, anonymous communications networks introduce an entirely new problem for the service providers - such as websites, IRC networks or mail servers - with which these users interact, in particular, since all anonymous users look alike, there is no way for the service providers to hold individual misbehaving anonymous users accountable for their actions. Recent research efforts have focused on using anonymous blacklisting systems (which are sometimes called anonymous revocation systems) to empower service providers with the ability to revoke access from abusive anonymous users. In contrast to revocable anonymity systems, which enable some trusted third party to deanonymize users, anonymous blacklisting systems provide users with a way to authenticate anonymously with a service provider, while enabling the service provider to revoke access from any users that misbehave, without revealing their identities. In this paper, we introduce the anonymous blacklisting problem and survey the literature on anonymous blacklisting systems, comparing and contrasting the architecture of various existing schemes, and discussing the tradeoffs inherent with each design. The literature on anonymous blacklisting systems lacks a unified set of definitions, each scheme operates under different trust assumptions and provides different security and privacy guarantees. Therefore, before we discuss the existing approaches in detail, we first propose a formal definition for anonymous blacklisting systems, and a set of security and privacy properties that these systems should possess. We also outline a set of new performance requirements that anonymous blacklisting systems should satisfy to maximize their potential for real-world adoption, and give formal definitions for several optional features already supported by some sche- - mes in the literature.

Dynamic taint analysis and forward symbolic execution are quickly becoming staple techniques in security analyses. Example applications of dynamic taint analysis and forward symbolic execution include malware analysis, input filter generation, test case generation, and vulnerability discovery. Despite the widespread usage of these two techniques, there has been little effort to formally define the algorithms and summarize the critical issues that arise when these techniques are used in typical security contexts. The contributions of this paper are two-fold. First, we precisely describe the algorithms for dynamic taint analysis and forward symbolic execution as extensions to the run-time semantics of a general language. Second, we highlight important implementation choices, common pitfalls, and considerations when using these techniques in a security context.

Trusting a computer for a security-sensitive task (such as checking email or banking online) requires the user to know something about the computer's state. We examine research on securely capturing a computer's state, and consider the utility of this information both for improving security on the local computer (e.g., to convince the user that her computer is not infected with malware) and for communicating a remote computer's state (e.g., to enable the user to check that a web server will adequately protect her data). Although the recent "Trusted Computing" initiative has drawn both positive and negative attention to this area, we consider the older and broader topic of bootstrapping trust in a computer. We cover issues ranging from the wide collection of secure hardware that can serve as a foundation for trust, to the usability issues that arise when trying to convey computer state information to humans. This approach unifies disparate research efforts and highlights opportunities for additional work that can guide real-world improvements in computer security.