Biblio

The Internet of Things (IoT) is the latest Internet evolution that incorporates a diverse range of things such as sensors, actuators, and services deployed by different organizations and individuals to support a variety of applications. The information captured by IoT present an unprecedented opportunity to solve large-scale problems in those application domains to deliver services; example applications include precision agriculture, environment monitoring, smart health, smart manufacturing, and smart cities. Like all other Internet based services in the past, IoT-based services are also being developed and deployed without security consideration. By nature, IoT devices and services are vulnerable to malicious cyber threats as they cannot be given the same protection that is received by enterprise services within an enterprise perimeter. While IoT services will play an important role in our daily life resulting in improved productivity and quality of life, the trend has also “encouraged” cyber-exploitation and evolution and diversification of malicious cyber threats. Hence, there is a need for coordinated efforts from the research community to address resulting concerns, such as those presented in this special section. Several potential research topics are also identified in this special section.

Vehicle localization is important in many applications of vehicular networks. The Global Positioning System (GPS) has been critical for vehicle localization. However, the case where the GPS is spoofed through a false data injection attack can be lead to devastating consequences, especially in localization solutions that make use of cooperation among multiple vehicles. Hence, resilient localization algorithms are needed that can achieve a baseline of performance in the case of a false data injection attack. This poster presents preliminary results of an inter-vehicle communication assisted localization algorithm that is resilient to false data injection attacks for the vehicles not directly attacked. The algorithm makes use of V2V and V2I communication – along with on-board GPS receiver, odometer, and compass – to achieve precise localization results.

Intrusion detection using multiple security devices has received much attention recently. The large volume of information generated by these tools, however, increases the burden on both computing resources and security administrators. Moreover, attack detection does not improve as expected if these tools work without any coordination. In this work, we propose a simple method to join information generated by security monitors with diverse data formats. We present a novel intrusion detection technique that uses unsupervised clustering algorithms to identify malicious behavior within large volumes of diverse security monitor data. First, we extract a set of features from network-level and host-level security logs that aid in detecting malicious host behavior and flooding-based network attacks in an enterprise network system. We then apply clustering algorithms to the separate and joined logs and use statistical tools to identify anomalous usage behaviors captured by the logs. We evaluate our approach on an enterprise network data set, which contains network and host activity logs. Our approach correctly identifies and prioritizes anomalous behaviors in the logs by their likelihood of maliciousness. By combining network and host logs, we are able to detect malicious behavior that cannot be detected by either log alone.

Radio Frequency Identification (RFID) technology has been applied in many fields, such as tracking product through the supply chains, electronic passport (ePassport), proximity card, etc. Most companies will choose low-cost RFID tags. However, these RFID tags are almost no security mechanism so that criminals can easily clone these tags and get the user permissions. In this paper, we aim at more efficient detection proximity card be cloned and design a real-time intrusion detection system based on one tool of Complex Event Processing (Esper) in the RFID middleware. We will detect the cloned tags through training our system with the user's habits. When detected anomalous behavior which may clone tags have occurred, and then send the notification to user. We discuss the reliability of this intrusion detection system and describes in detail how to work.

Data generation and its utilization in important decision applications has been growing an extremely fast pace, which has made data a valuable resource that needs to be rigorously protected from attackers. Cloud storage systems claim to offer the promise of secure and elastic data storage services that can adapt to changing storage requirements. Despite diligent efforts being made to protect data, recent successful attacks highlight the need for going beyond the existing approaches centered on intrusion prevention, detection and recovery mechanisms. However, most security mechanisms have finite rate of failure, and with intrusion becoming more sophisticated and stealthy, the failure rate appears to be rising. In this paper we propose the use data fragmentation, followed by coding that introduces redundant fragments and dispersing fragments to multiple and independent cloud storage systems with each cloud handling only a single fragments. The paper proposes a multi-cloud fragmented cloud storage system architecture and design of the related software code. Probabilistic analysis is carried to quantify its intrusion tolerance abilities.
 

With cyber-physical systems opening to the outside world, security can no longer be considered a secondary issue. One of the key aspects in security of cyber-phyiscal systems is to deal with intrusions. In this paper, we highlight the several unique properties of control applications in cyber-physical systems. Using these unique properties, we propose a systematic intrusion-damage assessment and mitigation mechanism for the class of observable and controllable attacks. On the one hand, in cyber-physical systems, the plants follow certain laws of physics and this can be utilized to address the intrusion-damage assessment problem. That is, the states of the controlled plant should follow those expected according to the physics of the system and any major discrepancy is potentially an indication of intrusion. Here, we use a machine learning algorithm to capture the normal behavior of the system according to its dynamics. On the other hand, the control performance strongly depends on the amount of allocated resources and this can be used to address the intrusion-damage mitigation problem. That is, the intrusion-damage mitigation is based on the idea of allocating more resources to the control application under attack. This is done using a feedback-based approach including a convex optimization.

User engagement is recognized as an important component of the user experience, but relatively little is known about the effect of engagement on the learning outcomes of such interactions. This experimental user study examines the relationship between user engagement (UE) and comprehension in varied academic reading environments. Forty-one university students interacted with one of two sets of texts presented in 4 conditions in the context of preparing for a class assignment. Employing the User Engagement Scale (UES), we found evidence of a relationship between students' comprehension of the texts and their degree of engagement with them. However, this association was confined to one of the UES subscales and was not consistent across levels of engagement. An examination of additional variables found little evidence that system and content characteristics influenced engagement; however, we noted that all students' reported increased knowledge, but topical interest for non-engaged students declined. Results contribute to existing literature by adding further evidence that the relationship between engagement and comprehension is complex and mediated.

Multilateration techniques have been proposed to verify the integrity of unprotected location claims in wireless localization systems. A common assumption is that the adversary is equipped with only a single device from which it transmits location spoofing signals. In this paper, we consider a more advanced model where the attacker is equipped with multiple devices and performs a geographically distributed coordinated attack on the multilateration system. The feasibility of a distributed multi-device attack is demonstrated experimentally with a self-developed attack implementation based on multiple COTS software-defined radio (SDR) devices. We launch an attack against the OpenSky Network, an air traffic surveillance system that implements a time-difference-of-arrival (TDoA) multi-lateration method for aircraft localization based on ADS-B signals. Our experiments show that the timing errors for distributed spoofed signals are indistinguishable from the multilateration errors of legitimate aircraft signals, indicating that the threat of multi-device spoofing attacks is real in this and other similar systems. In the second part of this work, we investigate physical-layer features that could be used to detect multi-device attacks. We show that the frequency offset and transient phase noise of the attacker's radio devices can be exploited to discriminate between a received signal that has been transmitted by a single (legitimate) transponder or by multiple (malicious) spoofing sources. Based on that, we devise a multi-device spoofing detection system that achieves zero false positives and a false negative rate below 1%.

NoSQL solutions become emerging for large scaled, high performance, schema-flexible applications. WiredTiger is cost effective, non-locking, no-overwrite storage used as default storage engine in MongoDB. Understanding I/O characteristics of storage engine is important not only for choosing suitable solution with an application but also opening opportunities for researchers optimizing current working system, especially building more flash-awareness NoSQL DBMS. This paper explores background of MongoDB internals then analyze I/O characteristics of WiredTiger storage engine in detail. We also exploit space management mechanism in WiredTiger by using TRIM command.

The Internet of Things (IoT) presents itself as a promising set of key technologies to provide advanced smart applications. IoT has become a major trend lately and smart solutions can be found in a large variety of products. Since it provides a flexible and easy way to gather data from huge numbers of devices and exploit them ot provide new applications, it has become a central research area lately. However, due to the fact that IoT aims to interconnect millions of constrained devices that are monitoring the everyday life of people, acting upon physical objects around them, the security and privacy challenges are huge. Nevertheless, only lately the research focus has been on security and privacy solutions. Many solutions and IoT frameworks have only a minimum set of security, which is a basic access control. The EU FP7 project RERUM has a main focus on designing an IoT architecture based on the concepts of Security and Privacy by design. A central part of RERUM is the implementation of a middleware layer that provides extra functionalities for improved security and privacy. This work, presents the main elements of the RERUM middleware, which is based on the widely accepted OpenIoT middleware.

Today 2.9 billion people, or 40% of the world's population are online. By 2020, at least 40 billion more devices will become smart via embedded processors. The impact of such Internet of Things (IoT) on our society will be extraordinary. It will influence most consumer and business sectors, impact education, healthcare and safety. However, it certainly will also pose a challenge from a security point of view. Not only will the devices themselves become more complex, also the interaction between devices, the networks and the variance in topology will grow. Finally, with increasing amounts of data and assets at stake the incentive for attackers will increase. The costs of cyber attacks in such setting are estimated to reach about 2 trillion USD by 2020. Today, the IoT is just beginning to emerge. Unfortunately, when looking at its security, there is lots of room for improvement. Exploits reported at a steady pace clearly suggest that security is a major challenge when the world wants to successfully switch from an IoT hype to a real IoT deployment. Security, and security risk awareness, insufficiently present in today's consumer and developer mindset, are only a starting point. Once the requirement for strong security is widely accepted, there will be still the economical question of who is going to pay for security and its maintenance. Without enforcing certain standards by means of third party evaluation this problem is expected to be hard to get under control.

We discuss a key engineering challenge in implementing the Identifier- Locator Network Protocol (ILNP), as described in IRTF Experimental RFCs 6740–6748: enabling legacy applications that use the C sockets API. We have built the first two OS kernel implementations of ILNPv6 (ILNP as a superset of IPv6), in both the Linux OS kernel and the FreeBSD OS kernel. Our evaluation is in comparison with IPv6, in the context of a topical and challenging scenario: host mobility implemented as a purely end-to-end function. Our experiments show that ILNPv6 has excellent potential for deployment using existing IPv6 infrastructure, whilst offering the new properties and functionality of ILNP.

Biometric is uses to identify authorized person based on specific physiological or behavioral features. Template protection is a crucial requirement when designing an authentication system, where the template could be modified by attacker. Hill Cipher is a block cipher and symmetric key algorithm it has several advantages such as simplicity, high speed and high throughput can be used to protect Biometric Template. Unfortunately, Hill Cipher has some disadvantages such as takes smaller sizes of blocks, very simple and vulnerable for exhaustive key search attack and known plain text attack, also the key matrix which entered should be invertible. This paper proposed an enhancement to overcome these drawbacks of Hill Cipher by using a large and random key with large data block, beside overcome the Invertible-key Matrix problem. The efficiency of encryption has been checked out by Normalized Correlation Coefficient (NCC) and running time.

Code diversification is an effective mitigation against return-oriented programming attacks, which breaks the assumptions of attackers about the location and structure of useful instruction sequences, known as "gadgets". Although a wide range of code diversification techniques of varying levels of granularity exist, most of them rely on the availability of source code, debug symbols, or the assumption of fully precise code disassembly, limiting their practical applicability for the protection of closed-source third-party applications. In-place code randomization has been proposed as an alternative binary-compatible diversification technique that is tolerant of partial disassembly coverage, in the expense though of leaving some gadgets intact, at the disposal of attackers. Consequently, the possibility of constructing robust ROP payloads using only the remaining non-randomized gadgets is still open. In this paper we present instruction displacement, a code diversification technique based on static binary instrumentation that does not rely on complete code disassembly coverage. Instruction displacement aims to improve the randomization coverage and entropy of existing binary-level code diversification techniques by displacing any remaining non-randomized gadgets to random locations. The results of our experimental evaluation demonstrate that instruction displacement reduces the number of non-randomized gadgets in the extracted code regions from 15.04% for standalone in-place code randomization, to 2.77% for the combination of both techniques. At the same time, the additional indirection introduced due to displacement incurs a negligible runtime overhead of 0.36% on average for the SPEC CPU2006 benchmarks.

Additive Manufacturing (AM) uses Cyber-Physical Systems (CPS) (e.g., 3D Printers) that are vulnerable to kinetic cyber-attacks. Kinetic cyber-attacks cause physical damage to the system from the cyber domain. In AM, kinetic cyber-attacks are realized by introducing flaws in the design of the 3D objects. These flaws may eventually compromise the structural integrity of the printed objects. In CPS, researchers have designed various attack detection method to detect the attacks on the integrity of the system. However, in AM, attack detection method is in its infancy. Moreover, analog emissions (such as acoustics, electromagnetic emissions, etc.) from the side-channels of AM have not been fully considered as a parameter for attack detection. To aid the security research in AM, this paper presents a novel attack detection method that is able to detect zero-day kinetic cyber-attacks on AM by identifying anomalous analog emissions which arise as an outcome of the attack. This is achieved by statistically estimating functions that map the relation between the analog emissions and the corresponding cyber domain data (such as G-code) to model the behavior of the system. Our method has been tested to detect potential zero-day kinetic cyber-attacks in fused deposition modeling based AM. These attacks can physically manifest to change various parameters of the 3D object, such as speed, dimension, and movement axis. Accuracy, defined as the capability of our method to detect the range of variations introduced to these parameters as a result of kinetic cyber-attacks, is 77.45%.

We present a method for key compression in quantumresistant isogeny-based cryptosystems, which allows a reduction in and transmission costs of per-party public information by a factor of two, with no e ect on security. We achieve this reduction by associating a canonical choice of elliptic curve to each j-invariant, and representing elements on the curve as linear combinations with respect to a canonical choice of basis. This method of compressing public information can be applied to numerous isogeny-based protocols, such as key exchange, zero-knowledge identi cation, and public-key encryption. We performed personal computer and ARM implementations of the key exchange with compression and decompression in C and provided timing results, showing the computational cost of key compression and decompression at various security levels. Our results show that isogeny-based cryptosystems achieve by far the smallest possible key sizes among all existing families of post-quantum cryptosystems at practical security levels; e.g. 3073-bit public keys at the quantum 128-bit security level, comparable to (non-quantum) RSA key sizes.

We present a method for key compression in quantumresistant isogeny-based cryptosystems, which allows a reduction in and transmission costs of per-party public information by a factor of two, with no e ect on security. We achieve this reduction by associating a canonical choice of elliptic curve to each j-invariant, and representing elements on the curve as linear combinations with respect to a canonical choice of basis. This method of compressing public information can be applied to numerous isogeny-based protocols, such as key exchange, zero-knowledge identi cation, and public-key encryption. We performed personal computer and ARM implementations of the key exchange with compression and decompression in C and provided timing results, showing the computational cost of key compression and decompression at various security levels. Our results show that isogeny-based cryptosystems achieve by far the smallest possible key sizes among all existing families of post-quantum cryptosystems at practical security levels; e.g. 3073-bit public keys at the quantum 128-bit security level, comparable to (non-quantum) RSA key sizes.

A Mobile Ad hoc Network (MANET) is a spontaneous network consisting of wireless nodes which are mobile and self-configuring in nature. Devices in MANET can move freely in any direction independently and change its link frequently to other devices. MANET does not have centralized infrastructure and its characteristics makes this network vulnerable to various kinds of attacks. Data transfer is a major problem due to its nature of unreliable wireless medium. Commonly used technique for secure transmission in wireless network is cryptography. Use of cryptography key is often involved in most of cryptographic techniques. Key management is main component in security issues of MANET and various schemes have been proposed for it. In this paper, a study on various kinds of key management techniques in MANET is presented.

In the context of service-oriented applications, the self-healing property provides reliable execution in order to support failures and assist automatic recovery techniques. This paper presents a knowledge-based approach for self-healing Composite Service (CS) applications. A CS is an application composed by a set of services interacting each other and invoked on the Web. Our approach is supported by Service Agents, which are in charge of the CS fault-tolerance execution control, making decisions about the selection of recovery and proactive strategies. Service Agents decisions are based on the information they have about the whole application, about themselves, and about what it is expected and what it is really happening at run-time. Hence, application knowledge for decision making comprises off-line precomputed global and local information, user QoS preferences, and propagated actual run-time information. Our approach is evaluated experimentally using a case study.

We show that the Kolmogorov extension theorem and the Doob martingale convergence theorem are two aspects of a common generalization, namely a colimit-like construction in a category of Radon spaces and reversible Markov kernels. The construction provides a compositional denotational semantics for lossless iteration in probabilistic programming languages, even in the absence of a natural partial order.

Aliasing is a known source of challenges in the context of imperative object-oriented languages, which have led to important advances in type systems for aliasing control. However, their large-scale adoption has turned out to be a surprisingly difficult challenge. While new language designs show promise, they do not address the need of aliasing control in existing languages. This paper presents a new approach to isolation and uniqueness in an existing, widely-used language, Scala. The approach is unique in the way it addresses some of the most important obstacles to the adoption of type system extensions for aliasing control. First, adaptation of existing code requires only a minimal set of annotations. Only a single bit of information is required per class. Surprisingly, the paper shows that this information can be provided by the object-capability discipline, widely-used in program security. We formalize our approach as a type system and prove key soundness theorems. The type system is implemented for the full Scala language, providing, for the first time, a sound integration with Scala's local type inference. Finally, we empirically evaluate the conformity of existing Scala open-source code on a corpus of over 75,000 LOC.

Lattice-based cryptography has gained credence recently as a replacement for current public-key cryptosystems, due to its quantum-resilience, versatility, and relatively low key sizes. To date, encryption based on the learning with errors (LWE) problem has only been investigated from an ideal lattice standpoint, due to its computation and size efficiencies. However, a thorough investigation of standard lattices in practice has yet to be considered. Standard lattices may be preferred to ideal lattices due to their stronger security assumptions and less restrictive parameter selection process. In this paper, an area-optimised hardware architecture of a standard lattice-based cryptographic scheme is proposed. The design is implemented on a FPGA and it is found that both encryption and decryption fit comfortably on a Spartan-6 FPGA. This is the first hardware architecture for standard lattice-based cryptography reported in the literature to date, and thus is a benchmark for future implementations. Additionally, a revised discrete Gaussian sampler is proposed which is the fastest of its type to date, and also is the first to investigate the cost savings of implementing with λ/2-bits of precision. Performance results are promising compared to the hardware designs of the equivalent ring-LWE scheme, which in addition to providing stronger security proofs; generate 1272 encryptions per second and 4395 decryptions per second.

In this paper we propose a protocol that allows end-users in a decentralized setup (without requiring any trusted third party) to protect data shipped to remote servers using two factors - knowledge (passwords) and possession (a time based one time password generation for authentication) that is portable. The protocol also supports revocation and recreation of a new possession factor if the older possession factor is compromised, provided the legitimate owner still has a copy of the possession factor. Furthermore, akin to some other recent works, our approach naturally protects the outsourced data from the storage servers themselves, by application of encryption and dispersal of information across multiple servers. We also extend the basic protocol to demonstrate how collaboration can be supported even while the stored content is encrypted, and where each collaborator is still restrained from accessing the data through a multi-factor access mechanism. Such techniques achieving layered security is crucial to (opportunistically) harness storage resources from untrusted entities.

Causality inference, such as dynamic taint anslysis, has many applications (e.g., information leak detection). It determines whether an event e is causally dependent on a preceding event c during execution. We develop a new causality inference engine LDX. Given an execution, it spawns a slave execution, in which it mutates c and observes whether any change is induced at e. To preclude non-determinism, LDX couples the executions by sharing syscall outcomes. To handle path differences induced by the perturbation, we develop a novel on-the-fly execution alignment scheme that maintains a counter to reflect the progress of execution. The scheme relies on program analysis and compiler transformation. LDX can effectively detect information leak and security attacks with an average overhead of 6.08% while running the master and the slave concurrently on separate CPUs, much lower than existing systems that require instruction level monitoring. Furthermore, it has much better accuracy in causality inference.

We describe our experiences in the classroom using the internet to collaboratively verify a significant safety and security property across the entire Linux kernel. With 66,609 instances to check across three versions of Linux, the naive approach of simply dividing up the code and assigning it to students does not scale, and does little to educate. However, by teaching and applying analytical reasoning, the instances can be categorized effectively, the problems of scale can be managed, and students can collaborate and compete with one another to achieve an unprecedented level of verification. We refer to our approach as Evidence-Enabled Collaborative Verification (EECV). A key aspect of this approach is the use of visual software models, which provide mathematically rigorous and critical evidence for verification. The visual models make analytical reasoning interactive, interesting and applicable to large software. Visual models are generated automatically using a tool we have developed called L-SAP [14]. This tool generates an Instance Verification Kit (IVK) for each instance, which contains all of the verification evidence for the instance. The L-SAP tool is implemented on a software graph database platform called Atlas [6]. This platform comes with a powerful query language and interactive visualization to build and apply visual models for software verification. The course project is based on three recent versions of the Linux operating system with altogether 37 MLOC and 66,609 verification instances. The instances are accessible through a website [2] for students to collaborate and compete. The Atlas platform, the L-SAP tool, the structured labs for the project, and the lecture slides are available upon request for academic use.