Biblio

As cloud computing becomes increasingly pervasive, it is critical for cloud providers to support basic security controls. Although major cloud providers tout such features, relatively little is known in many cases about their design and implementation. In this paper, we describe several security features in OpenStack, a widely-used, open source cloud computing platform. Our contributions to OpenStack range from key management and storage encryption to guaranteeing the integrity of virtual machine (VM) images prior to boot. We describe the design and implementation of these features in detail and provide a security analysis that enumerates the threats that each mitigates. Our performance evaluation shows that these security features have an acceptable cost-in some cases, within the measurement error observed in an operational cloud deployment. Finally, we highlight lessons learned from our real-world development experiences from contributing these features to OpenStack as a way to encourage others to transition their research into practice.

To provide a comprehensive security analysis of modern networked systems, we need to take into account the combined effects of existing vulnerabilities and zero-day vulnerabilities. In addition to them, it is important to incorporate new vulnerabilities emerging from threats such as BYOD, USB file sharing. Consequently, there may be new dependencies between system components that could also create new attack paths, but previous work did not take into account those new attack paths in their security analysis (i.e., not all attack paths are taken into account). Thus, countermeasures may not be effective, especially against attacks exploiting the new attack paths. In this paper, we propose a Unified Vulnerability Risk Analysis Module (UV-RAM) to address the aforementioned problems by taking into account the combined effects of those vulnerabilities and capturing the new attack paths. The three main functionalities of UV-RAM are: (i) to discover new dependencies and new attack paths, (ii) to incorporate new vulnerabilities introduced and zero-day vulnerabilities into security analysis, and (iii) to formulate mitigation strategies for hardening the networked system. Our experimental results demonstrate and validate the effectiveness of UV-RAM.

Speech recognition (SR) systems such as Siri or Google Now have become an increasingly popular human-computer interaction method, and have turned various systems into voice controllable systems (VCS). Prior work on attacking VCS shows that the hidden voice commands that are incomprehensible to people can control the systems. Hidden voice commands, though "hidden", are nonetheless audible. In this work, we design a totally inaudible attack, DolphinAttack, that modulates voice commands on ultrasonic carriers (e.g., f textgreater 20 kHz) to achieve inaudibility. By leveraging the nonlinearity of the microphone circuits, the modulated low-frequency audio commands can be successfully demodulated, recovered, and more importantly interpreted by the speech recognition systems. We validated DolphinAttack on popular speech recognition systems, including Siri, Google Now, Samsung S Voice, Huawei HiVoice, Cortana and Alexa. By injecting a sequence of inaudible voice commands, we show a few proof-of-concept attacks, which include activating Siri to initiate a FaceTime call on iPhone, activating Google Now to switch the phone to the airplane mode, and even manipulating the navigation system in an Audi automobile. We propose hardware and software defense solutions, and suggest to re-design voice controllable systems to be resilient to inaudible voice command attacks.

As societies are becoming more dependent on the power grids, the security issues and blackout threats are more emphasized. This paper proposes a new graph model for online visualization and assessment of power grid security. The proposed model integrates topology and power flow information to estimate and visualize interdependencies between the lines in the form of line dependency graph (LDG) and immediate threats graph (ITG). These models enable the system operator to predict the impact of line outage and identify the most vulnerable and critical links in the power system. Line Vulnerability Index (LVI) and Line Criticality Index (LCI) are introduced as two indices extracted from LDG to aid the operator in decision making and contingency selection. This package can be useful in enhancing situational awareness in power grid operation by visualization and estimation of system threats. The proposed approach is tested for security analysis of IEEE 30-bus and IEEE 118-bus systems and the results are discussed.

The main goal of introducing an identity-based cryptosystem and certificateless cryptosystem was avoiding certificates' management costs. In turn, the goal of introducing a certificate-based cryptosystem was to solve the certificate revocation problem. In this paper, we propose a new digital Implicit and Explicit Certificates-Based Hess's Signature (IE-CBHS) scheme that combines the features of a standard public key infrastructure (PKI) and certificate-based cryptosystem. Our IE-CBHS scheme is an efficient certificates-based signature. The security analysis proves that the scheme is secure against two game attacks in the random oracle model. The security is closely related to the difficulty of solving the computational Diffie–Hellman and discrete logarithm problems. The IE-CBHS scheme, when compared with other signature schemes, has similar efficiency and is both more flexible and more useful in practice. It is possible to revoke the explicit certificate and use that fact during digital signature verification. Thus, our scheme is useful in applications where typical mechanisms of standard PKI are used. One of many important security features is resistance to denial of signature verification attack. Also, it is impossible for a trusted authority to recreate a partial private key, even with cooperation with the signer.

The number of resource-limited wireless devices utilized in many areas of Internet of Things is growing rapidly; there is a concern about privacy and security. Various lightweight block ciphers are proposed; this work presents a modified lightweight block cipher algorithm. A Linear Feedback Shift Register is used to replace the key generation function in the XTEA1 Algorithm. Using the same evaluation conditions, we analyzed the software implementation of the modified XTEA using FELICS (Fair Evaluation of Lightweight Cryptographic Systems) a benchmarking framework which calculates RAM footprint, ROM occupation and execution time on three largely used embedded devices: 8-bit AVR microcontroller, 16-bit MSP microcontroller and 32-bit ARM microcontroller. Implementation results show that it provides less software requirements compared to original XTEA. We enhanced the security level and the software performance.

Internet of Things (IoT) is an emerging trend that is changing the way devices connect and communicate. Integration of cloud computing with IoT i.e. Cloud of Things (CoT) provide scalability, virtualized control and access to the services provided by IoT. Security issues are a major obstacle in widespread deployment and application of CoT. Among these issues, authentication and identification of user is crucial. In this study paper, survey of various authentication schemes is carried out. The aim of this paper is to study a multifactor authentication system which uses secret splitting in detail. The system uses exclusive-or operations, encryption algorithms and Diffie-Hellman key exchange algorithm to share key over the network. Security analysis shows the resistance of the system against different types of attacks.

Homomorphic encryption technology can settle a dispute of data privacy security in cloud environment, but there are many problems in the process of access the data which is encrypted by a homomorphic algorithm in the cloud. In this paper, on the premise of attribute encryption, we propose a fully homomorphic encrypt scheme which based on attribute encryption with LSSS matrix. This scheme supports fine-grained cum flexible access control along with "Query-Response" mechanism to enable users to efficiently retrieve desired data from cloud servers. In addition, the scheme should support considerable flexibility to revoke system privileges from users without updating the key client, it reduces the pressure of the client greatly. Finally, security analysis illustrates that the scheme can resist collusion attack. A comparison of the performance from existing CP-ABE scheme, indicates that our scheme reduces the computation cost greatly for users.

Unattended Wireless Sensor Networks (UWSN) are usually deployed in human-hostile environments. Such architectures raise a challenge to data protection for two main reasons. First, sensors have limited capacities in terms of performance and memory, so not all cryptographic mechanisms can be applied. Moreover, the measurements cannot be immediately gathered, so they have to be kept inside the devices until a mobile sink comes to collect them. This paper introduces a new method for secure and resilient data protection inside UWSN. It is based on a lightweight fragmentation scheme that transforms data collected by a sensor into multiple secure fragments that are distributed over sensor's neighboring nodes in a way that only a certain amount of these fragments is required for data recovery. Moreover, data security is reinforced by the use of a dynamic key refreshed after each visit of the mobile sink. Authentication and integrity information are dispersed within the fragments to protected data from active attacks. Homomorphic properties of the algorithm allow to significantly reduce storage space inside the nodes. Performance and empirical security evaluation results show that the proposed scheme achieves a good trade-off between performance, data protection and memory occupation.

We present in this paper a security analysis of electronic devices which considers the lifecycle properties of embedded systems. We first define a generic model of electronic devices lifecycle showing the complex interactions between the numerous assets and the actors. The method is illustrated through a case study: a connected insulin pump. The lifecycle induced vulnerabilities are analyzed using the EBIOS methodology. An analysis of associated countermeasures points out the lack of consideration of the life cycle in order to provide an acceptable security level of each assets of the device.

Location-Based Service (LBS) becomes increasingly important for our daily life. However, the localization information in the air is vulnerable to various attacks, which result in serious privacy concerns. To overcome this problem, we formulate a multi-objective optimization problem with considering both the query probability and the practical dummy location region. A low complexity dummy location selection scheme is proposed. We first find several candidate dummy locations with similar query probabilities. Among these selected candidates, a cloaking area based algorithm is then offered to find K - 1 dummy locations to achieve K-anonymity. The intersected area between two dummy locations is also derived to assist to determine the total cloaking area. Security analysis verifies the effectiveness of our scheme against the passive and active adversaries. Compared with other methods, simulation results show that the proposed dummy location scheme can improve the privacy level and enlarge the cloaking area simultaneously.

In the Internet of Things (IoT), smart devices are connected using various communication protocols, such as Wi-Fi, ZigBee. Some IoT devices have multiple built-in communication modules. If an IoT device equipped with multiple communication protocols is compromised by an attacker using one communication protocol (e.g., Wi-Fi), it can be exploited as an entry point to the IoT network. Another protocol (e.g., ZigBee) of this IoT device could be used to exploit vulnerabilities of other IoT devices using the same communication protocol. In order to find potential attacks caused by this kind of cross-protocol devices, we group IoT devices based on their communication protocols and construct a graphical security model for each group of devices using the same communication protocol. We combine the security models via the cross-protocol devices and compute hidden attack paths traversing different groups of devices. We use two use cases in the smart home scenario to demonstrate our approach and discuss some feasible countermeasures.

The Internet of Things (IoT) is a new paradigm in which every-day objects are interconnected between each other and to the Internet. This paradigm is receiving much attention of the scientific community and it is applied in many fields. In some applications, it is useful to prove that a number of objects are simultaneously present in a group. For example, an individual might want to authorize NFC payment with his mobile only if k of his devices are present to ensure that he is the right person. This principle is known as Grouping-Proofs. However, existing Grouping-Proofs schemes are mostly designed for RFID systems and don't fulfill the IoT characteristics. In this paper, we propose a Threshold Grouping-Proofs for IoT applications. Our scheme uses the Key-Policy Attribute-Based Encryption (KP-ABE) protocol to encrypt a message so that it can be decrypted only if at least k objects are simultaneously present in the same location. A security analysis and performance evaluation is conducted to show the effectiveness of our proposal solution.

Named Data Networking (NDN) is a content-oriented future Internet architecture, which well suits the increasingly mobile and information-intensive applications that dominate today's Internet. NDN relies on in-network caching to facilitate content delivery. This makes it challenging to enforce access control since the content has been cached in the routers and the content producer has lost the control over it. Due to its salient advantages in content delivery, network coding has been introduced into NDN to improve content delivery effectiveness. In this paper, we design ACNC, the first Access Control solution specifically for Network Coding-based NDN. By combining a novel linear AONT (All Or Nothing Transform) and encryption, we can ensure that only the legitimate user who possesses the authorization key can successfully recover the encoding matrix for network coding, and hence can recover the content being transmitted. In addition, our design has two salient merits: 1) the linear AONT well suits the linear nature of network coding; 2) only one vector of the encoding matrix needs to be encrypted/decrypted, which only incurs small computational overhead. Security analysis and experimental evaluation in ndnSIM show that our design can successfully enforce access control on network coding-based NDN with an acceptable overhead.

In this paper, we introduce a fast, secure and robust scheme for digital image encryption using chaotic system of Lorenz, 4D hyper-chaotic system and the Secure Hash Algorithm SHA-1. The encryption process consists of three layers: sub-vectors confusion and two-diffusion process. In the first layer we divide the plainimage into sub-vectors then, the position of each one is changed using the chaotic index sequence generated with chaotic attractor of Lorenz, while the diffusion layers use hyper-chaotic system to modify the values of pixels using an XOR operation. The results of security analysis such as statistical tests, differential attacks, key space, key sensitivity, entropy information and the running time are illustrated and compared to recent encryption schemes where the highest security level and speed are improved.

The most of the organizations tend to accumulate the data related to security, which goes up-to terabytes in every month. They collect this data to meet the security requirements. The data is mostly in the shape of logs like Dns logs, Pcap files, and Firewall data etc. The data can be related to any communication network like cloud, telecom, or smart grid network. Generally, these logs are stored in databases or warehouses which becomes ultimately gigantic in size. Such a huge size of data upsurge the importance of security analytics in big data. In surveys, the security experts grumble about the existing tools and recommend for special tools and methods for big data security analysis. In this paper, we are using a big data analysis tool, which is known as apache spark. Although this tool is used for general purpose but we have used this for security analysis. It offers a very good library for machine learning algorithms including the clustering which is the main algorithm used in our work. In this work, we have developed a novel model, which combines rule based and clustering analysis for security analysis of big dataset. The dataset we are using in our experiment is the Kddcup99 which is a widely used dataset for intrusion detection. It is of MBs in size but can be used as a test case for big data security analysis.

When created, the Java platform was among the first runtimes designed with security in mind. Yet, numerous Java versions were shown to contain far-reaching vulnerabilities, permitting denial-of-service attacks or even worse allowing intruders to bypass the runtime's sandbox mechanisms, opening the host system up to many kinds of further attacks. This paper presents a systematic in-depth study of 87 publicly available Java exploits found in the wild. By collecting, minimizing and categorizing those exploits, we identify their commonalities and root causes, with the goal of determining the weak spots in the Java security architecture and possible countermeasures. Our findings reveal that the exploits heavily rely on a set of nine weaknesses, including unauthorized use of restricted classes and confused deputies in combination with caller-sensitive methods. We further show that all attack vectors implemented by the exploits belong to one of three categories: single-step attacks, restricted-class attacks, and information hiding attacks. The analysis allows us to propose ideas for improving the security architecture to spawn further research in this area.

This tutorial will introduce participants to Grounded Theory, which is a qualitative framework to discover new theory from an empirical analysis of data. This form of analysis is particularly useful when analyzing text, audio or video artifacts that lack structure, but contain rich descriptions. We will frame Grounded Theory in the context of qualitative methods and case studies, which complement quantitative methods, such as controlled experiments and simulations. We will contrast the approaches developed by Glaser and Strauss, and introduce coding theory - the most prominent qualitative method for performing analysis to discover Grounded Theory. Topics include coding frames, first- and second-cycle coding, and saturation. We will use examples from security interview scripts to teach participants: developing a coding frame, coding a source document to discover relationships in the data, developing heuristics to resolve ambiguities between codes, and performing second-cycle coding to discover relationships within categories. Then, participants will learn how to discover theory from coded data. Participants will further learn about inter-rater reliability statistics, including Cohen's and Fleiss' Kappa, Krippendorf's Alpha, and Vanbelle's Index. Finally, we will review how to present Grounded Theory results in publications, including how to describe the methodology, report observations, and describe threats to validity.

In the area of the Internet of Things, cloud-based camera surveillance systems are ubiquitously available for industrial and private environments. However, the sensitive nature of the surveillance use case imposes high requirements on privacy/confidentiality, authenticity, and availability of such systems. In this work, we investigate how currently available mass-market camera systems comply with these requirements. Considering two attacker models, we test the cameras for weaknesses and analyze for their implications. We reverse-engineered the security implementation and discovered several vulnerabilities in every tested system. These weaknesses impair the users' privacy and, as a consequence, may also damage the camera system manufacturer's reputation. We demonstrate how an attacker can exploit these vulnerabilities to blackmail users and companies by denial-of-service attacks, injecting forged video streams, and by eavesdropping private video data - even without physical access to the device. Our analysis shows that current systems lack in practice the necessary care when implementing security for IoT devices.

Implementation attacks and more specifically Power Analysis (PA) (the dominant type of side channel attack) and fault injection (FA) attacks constitute a pragmatic hazard for scalar multiplication, the main operation behind Elliptic Curve Cryptography. There exists a wide variety of countermeasures attempting to thwart such attacks that, however, few of them explore the potential of alternative number systems like the Residue Number System (RNS). In this paper, we explore the potential of RNS as an PA-FA countermeasure and propose an PA-FA resistant scalar multiplication algorithm and provide an extensive security analysis against the most effective PA-FA techniques. We argue through a security analysis that combining traditional PA-FA countermeasures with lightweight RNS countermeasures can provide strong PA-FA resistance.

Radio Frequency Identification (RFID) systems are widely used today because of their low price, usability and being wireless. As RFID systems use wireless communication, they may encounter challenging security problems. Several lightweight encryption algorithms have been proposed so far to solve these problems. The RBS block cipher is one of these algorithms. In designing RBS, conventional block cipher elements such as S-box and P-box are not used. RBS is based on inserting redundant bits between altered plaintext bits using an encryption key Kenc. In this paper, considering not having a proper diffusion as the main defect of RBS, we propose a chosen ciphertext attack against this algorithm. The data complexity of this attack equals to N pairs of text and its time complexity equals to N decryptions, where N is the size of the encryption key Kenc.

This tutorial will introduce participants to Grounded Theory, which is a qualitative framework to discover new theory from an empirical analysis of data. This form of analysis is particularly useful when analyzing text, audio or video artifacts that lack structure, but contain rich descriptions. We will frame Grounded Theory in the context of qualitative methods and case studies, which complement quantitative methods, such as controlled experiments and simulations. We will contrast the approaches developed by Glaser and Strauss, and introduce coding theory - the most prominent qualitative method for performing analysis to discover Grounded Theory. Topics include coding frames, first- and second-cycle coding, and saturation. We will use examples from security interview scripts to teach participants: developing a coding frame, coding a source document to discover relationships in the data, developing heuristics to resolve ambiguities between codes, and performing second-cycle coding to discover relationships within categories. Then, participants will learn how to discover theory from coded data. Participants will further learn about inter-rater reliability statistics, including Cohen's and Fleiss' Kappa, Krippendorf's Alpha, and Vanbelle's Index. Finally, we will review how to present Grounded Theory results in publications, including how to describe the methodology, report observations, and describe threats to validity.

In recent years, more and more multimedia data are generated and transmitted in various fields. So, many encryption methods for multimedia content have been put forward to satisfy various applications. However, there are still some open issues. Each encryption method has its advantages and drawbacks. Our main goal is expected to provide a solution for multimedia encryption which satisfies the target application constraints and performs metrics of the encryption algorithm. The Advanced Encryption Standard (AES) is the most popular algorithm used in symmetric key cryptography. Furthermore, chaotic encryption is a new research direction of cryptography which is characterized by high initial-value sensitivity and good randomness. In this paper we propose a hybrid video cryptosystem which combines two encryption techniques. The proposed cryptosystem realizes the video encryption through the chaos and AES in CTR mode. Experimental results and security analysis demonstrate that this cryptosystem is highly efficient and a robust system for video encryption.

This paper presents an efficiency and adaptive cryptographic protocol to ensure users' privacy and data integrity in RFID system. Radio Frequency Identification technology offers more intelligent systems and applications, but privacy and security issues have to be addressed before and after its adoption. The design of the proposed model is based on clustering configuration of the involved tags where they interchange the data with the reader whenever it sends a request. This scheme provides a strong mutual authentication framework that suits for real heterogeneous RFID applications such as in supply-chain management systems, healthcare monitoring and industrial environment. In addition, we contribute with a mathematical analysis to the delay analysis and optimization in a clustering topology tag-based. Finally, a formal security and proof analysis is demonstrated to prove the effectiveness of the proposed protocol and that achieves security and privacy.

EPC Gen2 tags are working as international RFID standards for the use in the supply chain worldwide, such tags are computationally weak devices and unable to perform even basic symmetric-key cryptographic operations. For this reason, to implement robust and secure pseudo-random number generators (PRNG) is a challenging issue for low-cost Radio-frequency identification (RFID) tags. In this paper, we study the security of LFSR-based PRNG implemented on EPC Gen2 tags and exploit LFSR-based PRNG to provide a better constructions. We provide a cryptanalysis against the J3Gen which is LFSR-based PRNG and proposed by Sugei et al. [1], [2] for EPC Gen2 tags using distinguish attack and make observations on its input using NIST randomness test. We also test the PRNG in EPC Gen2 RFID Tags by using the NIST SP800-22. As a counter-measure, we propose two modified models based on the security analysis results. We show that our results perform better than J3Gen in terms of computational and statistical property.