Biblio

Tor is the most widely used anonymity network, currently serving millions of users each day. However, there is no access control in place for all these users, leaving the network vulnerable to botnet abuse and attacks. For example, criminals frequently use exit relays as stepping stones for attacks, causing service providers to serve CAPTCHAs to exit relay IP addresses or blacklisting them altogether, which leads to severe usability issues for legitimate Tor users. To address this problem, we propose TorPolice, the first privacy-preserving access control framework for Tor. TorPolice enables abuse-plagued service providers such as Yelp to enforce access rules to police and throttle malicious requests coming from Tor while still providing service to legitimate Tor users. Further, TorPolice equips Tor with global access control for relays, enhancing Tor's resilience to botnet abuse. We show that TorPolice preserves the privacy of Tor users, implement a prototype of TorPolice, and perform extensive evaluations to validate our design goals.

Authentication of smartphone users is important because a lot of sensitive data is stored in the smartphone and the smartphone is also used to access various cloud data and services. However, smartphones are easily stolen or co-opted by an attacker. Beyond the initial login, it is highly desirable to re-authenticate end-users who are continuing to access security-critical services and data. Hence, this paper proposes a novel authentication system for implicit, continuous authentication of the smartphone user based on behavioral characteristics, by leveraging the sensors already ubiquitously built into smartphones. We propose novel context-based authentication models to differentiate the legitimate smartphone owner versus other users. We systematically show how to achieve high authentication accuracy with different design alternatives in sensor and feature selection, machine learning techniques, context detection and multiple devices. Our system can achieve excellent authentication performance with 98.1% accuracy with negligible system overhead and less than 2.4% battery consumption.

In the present paper, a networked control system under both cyber and physical attacks Is considered. An adapted formulation of the problem under physical attacks, data deception and false data injection attacks, is used for controller synthesis. Based on the classical fault tolerant detection (FTD) tools, a residual generator for attack/fault detection based on observers is proposed. An event-triggered and Bilinear Matrix Inequality (BMI) implementation is proposed in order to achieve novel and better security strategy. The purpose in using this implementation would be to reduce (limit) the total number of transmissions to only instances when the networked control system (NCS) needs attention. It is important to note that the main contribution of this paper is to establish the adequate event-triggered and BMI-based methodology so that the particular structure of the mixed attacked/faulty structure can be re-formulated within the classical FTD paradigm. Experimental results are given to illustrate the developed approach efficiency on a pilot three-tank system. The plant model is presented and the proposed control design is applied to the system.

As a plethora of wearable devices are being introduced, significant concerns exist on the privacy and security of personal data stored on these devices. Expanding on recent works of using electrocardiogram (ECG) as a modality for biometric authentication, in this work, we investigate the possibility of using personal ECG signals as the individually unique source for physical unclonable function (PUF), which eventually can be used as the key for encryption and decryption engines. We present new signal processing and machine learning algorithms that learn and extract maximally different ECG features for different individuals and minimally different ECG features for the same individual over time. Experimental results with a large 741-subject in-house ECG database show that the distributions of the intra-subject (same person) Hamming distance of extracted ECG features and the inter-subject Hamming distance have minimal overlap. 256-b random numbers generated from the ECG features of 648 (out of 741) subjects pass the NIST randomness tests.

This paper investigates the physical layer security in a multibeam satellite communication system, where each legitimate user is surrounded by one eavesdropper. First of all, an optimization problem is formulated to maximize the sum of achievable secrecy rate, while satisfying the on-board satellite transmit power constraint. Then, two transmit beamforming(BF) schemes, namely, the zero-forcing (ZF) and the signal-to-leakage-and-noise ratio (SLNR) BF algorithms are proposed to obtain the BF weight vectors as well as power allocation coefficients. Finally, simulation results are provided to verify the validity of the two proposed methods and demonstrate that the SLNR BF algorithm outperforms the ZF BF algorithm.

In this paper, a simulation model of digital intermediate frequency (IF) GPS signal is presented. This design is developed based on mathematical model representing the digitized IF GPS signal. In details, C/A code, navigation data and P code, and the noise models are configured some initial settings simultaneously. Simulation results show that the simulated signals share the same properties with real signals (e.g. C/A code correlation properties, and the spread spectrum). The simulated GPS IF signal data can work as input for various signal processing algorithm of GPS receivers, such as acquisition, tracking, carrier-to-noise ratio (C/No) estimation, and GPS spoofing signal generation. Particularly, the simulated GPS signal can conduct scenarios by adjust SNR values of the noise generator during simulation (e.g. signal outages, sudden changes of GPS signal power), which can be used as setup experiments of spoofing/jamming interference to UAVs for drone security applications.

The conventional physical-layer (PHY) security approaches, e.g., transmit beamforming and artificial noise (AN)-based design, may fail when the channels of legitimate user (LU) and eavesdropper (Eve) are close correlated. Due to the highly directional transmission feature of millimeter-wave (mmWave), this may occur in mmWave transmissions as the transmitter, Eve and LU are aligned in the same direction exactly. To handle the PHY security problem with directionally-aligned LU and Eve, we propose a novel frequency diverse array (FDA) beamforming approach to differentiating the LU and Eve. By intentionally introducing some frequency offsets across the antennas, the FDA beamforming generates an angle-range dependent beampattern. As a consequence, it can degrade the Eve's reception and thus achieve PHY security. In this paper, we maximize the secrecy rate by jointly optimizing the frequency offsets and the beamformer. This secrecy rate maximization (SRM) problem is hard to solve due to the tightly coupled variables. Nevertheless, we show that it can be reformulated into a form depending only on the frequency offsets. Building upon this reformulation, we identify some cases where the SRM problem can be optimally solved in closed form. Numerical results demonstrate the efficacy of FDA beamforming in achieving PHY security, even for aligned LU and Eve.

The importance of the task of countering the means of unauthorized access is to preserve the integrity of restricted access information circulating in computer networks determines the relevance of investigating perspective methods of cryptographic transformations, which are characterized by high speed and reliability of encryption. The methods of information security in the telecommunication system were researched based on integration of encryption processes and noise-immune coding. The method for data encryption based on generic polynomials of cyclic codes, gamut of the dynamic chaos sequence, and timer coding was proposed. The expediency of using timer coding for increasing the cryptographic strength of the encryption system and compensating for the redundancy of the verification elements was substantiated. The method for cryptographic transformation of data based on the gamma sequence was developed, which is formed by combining numbers from different sources of dynamical chaos generators. The efficiency criterion was introduced for the integrated information transformation method.

In this paper, an improved cooperative jamming (CJ) strategy is developed for physical layer (PHY) security in a multi-hop wireless communication system which employs beamforming in the last hop. Users are assigned to independent groups based on the merger-and-split rule in a coalition game. The secrecy capacity for a valid coalition is a non-convex optimization problem which cannot easily be solved. Therefore, restrictions are added to transform this into a convex problem, and this is solved to obtain a suboptimal closed-form solution for the secrecy capacity. Simulation results are presented which show that the proposed strategy outperforms other methods such as non-cooperation, relay cooperation, and previous CJ approaches in terms of the secrecy capacity. Further, it is shown that the proposed multi-hop solution is suitable for long distance communication systems.

This paper describes and verifies a method of implementing bit error rate (BER) calculation for FPGA-based physical layer security techniques for Software Defined Radio (SDR). Specifically, we describe an independent source signal processing architecture for an efficient calculation of BER for wireless communication modules across the transmitter and receiver nodes. The source components at the transmitter and the receiver both generate identical random bits independently from each other, allowing for the received data to be compared to the original bit stream to calculate BER completely on hardware. The described method is implemented on a Xilinx Virtex-6 ML605 FPGA and reduces processing time by more than four orders of magnitude less than hardware simulation techniques in regression testing and validation over billions of bits, shortening design turn around times and accelerating Physical layer based security development for wireless communication research. The described independent source approach utilizes a minimal amount of board resources, allowing it to be integrated seamlessly into SDR hardware designs. Experimental validation of the independent source based BER calculation is performed for an Orthogonal Frequency Division Multiplexing signal, and a comparison between different stages of hardware design for the execution time required for BER testing of a large number of bits is provided.

Delay and security are both highly concerned in the Internet of Things (IoT). In this paper, we set up a secure analytical framework for IoT networks to characterize the network delay performance and secrecy performance. Firstly, stochastic geometry and queueing theory are adopted to model the location of IoT devices and the temporal arrival of packets. Based on this model, a low-complexity secure on-off scheme is proposed to improve the network performance. Then, the delay performance and secrecy performance are evaluated in terms of packet delay and packet secrecy outage probability. It is demonstrated that the intensity of IoT devices arouse a tradeoff between the delay and security and the secure on-off scheme can improve the network delay performance and secrecy performance. Moreover, secrecy transmission rate is adopted to reflect the delay-security tradeoff. The analytical and simulation results show the effects of intensity of IoT devices and secure on-off scheme on the network delay performance and secrecy performance.

Honeynet is deployed to trap attackers and learn their behavior patterns and motivations. Conventional honeynet is implemented by dedicated hardware and software. It suffers from inflexibility, high CAPEX and OPEX. There have been several virtualized honeynet architectures to solve those problems. But they lack a standard operating environment and common architecture for dynamic scheduling and adaptive resource allocation. Software Defined Security (SDS) framework has a centralized control mechanism and intelligent decision making ability for different security functions. In this paper, we present a new intelligent honeynet architecture based on SDS framework. It implements security functions over Network Function Virtualization Infrastructure (NFVI). Under uniform and intelligent control, security functional modules can be dynamically deployed and collaborated to complete different tasks. It migrates resources according to the workloads of each honeypot and power off unused modules. Simulation results show that intelligent honeynet has a better performance in conserving resources and reducing energy consumption. The new architecture can fit the needs of future honeynet development and deployment.

This paper discusses possible approaches to address the loss of user privacy when browsing the web and being tracked by websites which compute a browser fingerprint identifying the user computer. The key problem is that the current fingerprinting countermeasures are insufficient to prevent fingerprinting tracking and also frequently produce side-effects on the web browser. The advantages and disadvantages of possible countermeasures are discussed in the context of improving resistance against browser fingerprinting. Finally, using a new browser extension is proposed as the best way to inhibit fingerprinting as it could probably inhibit some of the fingerprinting techniques used and also diminish the side-effects on the user browser experience, compared with existing techniques.

The de facto approach to Web security today is HTTPS. While HTTPS ensures complete security for clients and servers, it also interferes with transparent content-caching at middleboxes. To address this problem and support both security and caching, we propose a new approach to Web security and privacy called GroupSec. The key innovation of GroupSec is that it replaces the traditional session-based security model with a new model based on content group membership. We introduce the GroupSec security model and show how HTTP can be easily adapted to support GroupSec without requiring changes to browsers, servers, or middleboxes. Finally, we present results of a threat analysis and performance experiments which show that GroupSec achieves notable performance benefits at the client and server while remaining as secure as HTTPS.

The exponential growth in the number of mobile devices, combined with the rapid demand for wireless services, has steadily stressed the wireless spectrum, calling for new techniques to improve spectrum utilization. A geo-location database has been proposed as a viable solution for wireless users to determine spectrum availability in cognitive radio networks. The protocol used by secondary users (SU) to request spectral availability for a specific location, time and duration, may reveal confidential information about these users. In this paper, we focus on SUs' location privacy in database-enabled wireless networks and propose a framework to address this threat. The basic tenet of the framework is obfuscation, whereby channel requests for valid locations are interwoven with requests for fake locations. Traffic redirection is also used to deliberately confuse potential query monitors from inferring users' location information. Within this framework, we propose two privacy-preserving schemes. The Master Device Enabled Location Privacy Preserving scheme utilizes trusted master devices to prevent leaking information of SUs' locations to attackers. The Crowd Sourced Location Privacy Preserving scheme builds a guided tour of randomly selected volunteers to deliver users channel availability queries and ensure location privacy. Security analysis and computational and communication overhead of these schemes are discussed.

In distributed systems, there is often a need to combine the heterogeneous access control policies to offer more comprehensive services to users in the local or national level. A large scale healthcare system is usually distributed in a computer network and might require sophisticated access control policies to protect the system. Therefore, the need for integrating the electronic healthcare systems might be important to provide a comprehensive care for patients while preserving patients' privacy and data security. However, there are major impediments in healthcare systems concerning not well-defined and flexible access control policy implementations, hindering the progress towards secure integrated systems. In this paper, we introduce an access control policy combination framework for EHR systems that preserves patients' privacy and ensures data security. We achieve our goal through an access control mechanism which handles multiple access control policies through a similarity analysis phase. In that phase, we evaluate different XACML policies to decide whether or not a policy combination is applicable. We have provided a case study to show the applicability of our proposed approach based on XACML. Our study results can be applied to the electronic health record (EHR) access control policy, which fosters interoperability and scalability among healthcare providers while preserving patients' privacy and data security. 

Internet plays a crucial role in today's life, so the usage of online social network monotonically increasing. People can share multimedia information's fastly and keep in touch or communicate with friend's easily through online social network across the world. Security in authentication is a big challenge in online social network and authentication is a preliminary process for identifying legitimate user. Conventionally, we are using alphanumeric textbased password for authentication approach. But the main flaw points of text based password is highly vulnerable to attacks and difficulty of recalling password during authentication time due to the irregular use of passwords. To overcome the shortcoming of text passwords, we propose a Graphical Password authentication. An approach of Graphical Password is an authentication of amalgam of pictures. It is less vulnerable to attacks and human can easily recall pictures better than text. So the graphical password is a better alternative to text passwords. As the image uploads are increasing by users share through online site, privacy preserving has become a major problem. So we need a Caption Based Metadata Stratification of images for delivers an automatic suggestion of similar category already in database, it works by comparing the caption metadata of album with caption metadata already in database or extract the synonyms of caption metadata of new album for checking the similarity with caption metadata already in database. This stratification offers an enhanced automatic privacy prediction for uploaded images in online social network, privacy is an inevitable factor for uploaded images, and privacy violation is a major concern. So we propose an Automatic Policy Prediction for uploaded images that are classified by caption metadata. An automatic policy prediction is a hassle-free privacy setting proposed to the user.

There are billions of Internet of things (IoT) devices connecting to the Internet and the number is increasing. As a still ongoing technology, IoT can be used in different fields, such as agriculture, healthcare, manufacturing, energy, retailing and logistics. IoT has been changing our world and the way we live and think. However, IoT has no uniform architecture and there are different kinds of attacks on the different layers of IoT, such as unauthorized access to tags, tag cloning, sybil attack, sinkhole attack, denial of service attack, malicious code injection, and man in middle attack. IoT devices are more vulnerable to attacks because it is simple and some security measures can not be implemented. We analyze the privacy and security challenges in the IoT and survey on the corresponding solutions to enhance the security of IoT architecture and protocol. We should focus more on the security and privacy on IoT and help to promote the development of IoT.

Internet of things (IOT) is a kind of advanced information technology which has drawn societies' attention. Sensors and stimulators are usually recognized as smart devices of our environment. Simultaneously IOT security brings up new issues. Internet connection and possibility of interaction with smart devices cause those devices to involve more in human life. Therefore, safety is a fundamental requirement in designing IOT. IOT has three remarkable features: overall perception, reliable transmission and intelligent processing. Because of IOT span, security of conveying data is an essential factor for system security. Hybrid encryption technique is a new model that can be used in IOT. This type of encryption generates strong security and low computation. In this paper, we have proposed a hybrid encryption algorithm which has been conducted in order to reduce safety risks and enhancing encryption's speed and less computational complexity. The purpose of this hybrid algorithm is information integrity, confidentiality, non-repudiation in data exchange for IOT. Eventually suggested encryption algorithm has been simulated by MATLAB software and its speed and safety efficiency were evaluated in comparison with conventional encryption algorithm.

Security Evaluation and Management (SEM) is considerably important process to protect the Embedded System (ES) from various kinds of security's exploits. In general, SEM's processes have some challenges, which limited its efficiency. Some of these challenges are system-based challenges like the hetero-geneity among system's components and system's size. Some other challenges are expert-based challenges like mis-evaluation possibility and experts non-continuous availability. Many of these challenges were addressed by the Multi Metric (MM) framework, which depends on experts' or subjective evaluation for basic evaluations. Despite of its productivity, subjective evaluation has some drawbacks (e.g. expert misevaluation) foster the need for considering objective evaluations in the MM framework. In addition, the MM framework is system centric framework, thus, by modelling complex and huge system using the MM framework a guide is needed indicating changes toward desirable security's requirements. This paper proposes extensions for the MM framework consider the usage of objective evaluations and work as guide for needed changes to satisfy desirable security requirements.

Security and privacy of big data becomes challenging as data grows and more accessible by more and more clients. Large-scale data storage is becoming a necessity for healthcare, business segments, government departments, scientific endeavors and individuals. Our research will focus on the privacy, security and how we can make sure that big data is secured. Managing security policy is a challenge that our framework will handle for big data. Privacy policy needs to be integrated, flexible, context-aware and customizable. We will build a framework to receive data from customer and then analyze data received, extract privacy policy and then identify the sensitive data. In this paper we will present the techniques for privacy policy which will be created to be used in our framework.

Increasing cyber-security presents an ongoing challenge to security professionals. Research continuously suggests that online users are a weak link in information security. This research explores the relationship between cyber-security and cultural, personality and demographic variables. This study was conducted in four different countries and presents a multi-cultural view of cyber-security. In particular, it looks at how behavior, self-efficacy and privacy attitude are affected by culture compared to other psychological and demographics variables (such as gender and computer expertise). It also examines what kind of data people tend to share online and how culture affects these choices. This work supports the idea of developing personality based UI design to increase users' cyber-security. Its results show that certain personality traits affect the user cyber-security related behavior across different cultures, which further reinforces their contribution compared to cultural effects.

This paper presents a framework for privacy-preserving video delivery system to fulfill users' privacy demands. The proposed framework leverages the inference channels in sensitive behavior prediction and object tracking in a video surveillance system for the sequence privacy protection. For such a goal, we need to capture different pieces of evidence which are used to infer the identity. The temporal, spatial and context features are extracted from the surveillance video as the observations to perceive the privacy demands and their correlations. Taking advantage of quantifying various evidence and utility, we let users subscribe videos with a viewer-dependent pattern. We implement a prototype system for off-line and on-line requirements in two typical monitoring scenarios to construct extensive experiments. The evaluation results show that our system can efficiently satisfy users' privacy demands while saving over 25% more video information compared to traditional video privacy protection schemes.

A smart city uses information technology to integrate and manage physical, social, and business infrastructures in order to provide better services to its dwellers while ensuring efficient and optimal utilization of available resources. With the proliferation of technologies such as Internet of Things (IoT), cloud computing, and interconnected networks, smart cities can deliver innovative solutions and more direct interaction and collaboration between citizens and the local government. Despite a number of potential benefits, digital disruption poses many challenges related to information security and privacy. This paper proposes a security framework that integrates the blockchain technology with smart devices to provide a secure communication platform in a smart city.

Most of the existing authentication protocols are based on either asymmetric cryptography like public-key infrastructure (PKI) or symmetric cryptography. The PKI-based authentication protocols are strongly recommended for solving security issues in VANETs. However, they have following shortcomings: (1) lengthy certificates lead to transmission and computation overheads, and (2) lack of privacy-preservation due to revealing of vehicle identity, communicated in broadcasting safety-message. Symmetric cryptography based protocols are faster because of a single secret key and simplicity; however, it does not ensure non-repudiation. In this paper, we present an Efficient, Scalable and Privacy-preserving Authentication (ESPA) protocol for secure vehicular ad hoc networks (VANETs). The protocol employs hybrid cryptography. In ESPA, the asymmetric PKI based pre-authentication and the symmetric hash message authentication code (HMAC) based authentication are adopted during vehicle to infrastructure (V2I) and vehicle to vehicle (V2V) communications, respectively. Extensive simulations are conducted to validate proposed ESPA protocol and compared with the existing work based on PKI and HMAC. The performance analysis showed that ESPA is more efficient, scalable and privacy-preserving secured protocol than the existing work.