Biblio

Network-on-Chip (NoC) architecture is the communication heart of the processing cores in Multiprocessors System-on-Chip (MPSoC), where messages are routed from a source to a destination through intermediate nodes. Therefore, NoC has become a target to security attacks. By experiencing outsourcing design, NoC can be infected with a malicious Hardware Trojans (HTs) which potentially degrade the system performance or leave a backdoor for secret key leaking. In this paper, we propose a HT model that applies a denial of service attack by misrouting the packets, which causes deadlock and consequently degrading the NoC performance. We present a secure routing algorithm that provides a runtime HT detection and avoiding scheme. Results show that our proposed model has negligible overhead in area and power, 0.4% and 0.6%, respectively.

We would like to compute RSA signatures with the help of a Hardware Security Module (HSM). But what can we do when we want to use a certain public exponent that the HSM does not allow or support? Surprisingly, this scenario comes up in real-world settings such as code-signing of Intel SGX enclaves. Intel SGX enclaves have to be signed in order to execute in release mode, using 3072-bit RSA signature scheme with a particular public exponent. However, we encountered commercial hardware security modules that do not support storing RSA keys corresponding to this exponent. We ask whether it is possible to overcome such a limitation of an HSM and answer it in the affirmative (under stated assumptions). We show how to convert RSA signatures corresponding to one public exponent, to valid RSA signatures corresponding to another exponent. We define security and show that it is not compromised by the additional public knowledge available to an adversary in this setting.

In stream-based programming, data sources are abstracted as a stream of values that can be manipulated via callback functions. Stream-based programming is exploding in popularity, as it provides a powerful and expressive paradigm for handling asynchronous data sources in interactive software. However, high-level stream abstractions can also make it difficult for developers to reason about control- and data-flow relationships in their programs. This is particularly impactful when asynchronous stream-based code interacts with thread-limited features such as UI frameworks that restrict UI access to a single thread, since the threading behavior of streaming constructs is often non-intuitive and insufficiently documented. In this paper, we present a type-based approach that can statically prove the thread-safety of UI accesses in stream-based software. Our key insight is that the fluent APIs of stream-processing frameworks enable the tracking of threads via type-refinement, making it possible to reason automatically about what thread a piece of code runs on – a difficult problem in general. We implement the system as an annotation-based Java typechecker for Android programs built upon the popular ReactiveX framework and evaluate its efficacy by annotating and analyzing 8 open-source apps, where we find 33 instances of unsafe UI access while incurring an annotation burden of only one annotation per 186 source lines of code. We also report on our experience applying the typechecker to two much larger apps from the Uber Technologies, Inc. codebase, where it currently runs on every code change and blocks changes that introduce potential threading bugs.

The most promising way to improve the performance of dynamic information-flow tracking (DIFT) for machine code is to only track instructions when they process tainted data. Unfortunately, prior approaches to on-demand DIFT are a poor match for modern mobile platforms that rely heavily on parallelism to provide good interactivity in the face of computationally intensive tasks like image processing. The main shortcoming of these prior efforts is that they cannot support an arbitrary mix of parallel threads due to the limitations of page protections. In this paper, we identify parallel permissions as a key requirement for multithreaded, on-demand native DIFT, and we describe the design and implementation of a system called SandTrap that embodies this approach. Using our prototype implementation, we demonstrate that SandTrap's native DIFT overhead is proportional to the amount of tainted data that native code processes. For example, in the photo-sharing app Instagram, SandTrap's performance is close to baseline (1x) when the app does not access tainted data. When it does, SandTrap imposes a slowdown comparable to prior DIFT systems (\textasciitilde8x).

Software verification has been well applied in safety critical areas and has shown the ability to provide better quality assurance for modern software. However, as lines of code and complexity of software systems increase, the scalability of verification becomes a challenge. In this paper, we present an automatic software verification framework TSV to address the scalability issues: (i) the extended structural abstraction and property-guided program slicing to solve large-scale program verification problem, saving time and memory without losing accuracy; (ii) automatically select different verification methods according to the program and property context to improve the verification efficiency. For evaluation, we compare TSV's different configurations with existing C program verifiers based on open benchmarks. We found that TSV with auto-selection performs better than with bounded model checking only or with extended structural abstraction only. Compared to existing tools such as CMBC and CPAChecker, it acquires 10%-20% improvement of accuracy and 50%-90% improvement of memory consumption.

Public cloud data storage services were considered as a potential alternative to store low-cost digital data in the short term. They are offered by different providers on the Internet. Some providers offer limited free plans for the users who are starting the service. However, data security concern arises when data stored are considered as a valuable asset. This study explores the usage of secret sharing scheme: Rabin's IDA and Shamir's SSA to implement a tool called dCloud for file protection stored in public cloud storage in a seamless way. It addresses data security by hiding its complexities when targeting ordinary non-technical users. The secret key is automatically generated by dCloud in a secure random way on Rabin's IDA. Shamir's SSA completes the process through dispersing the key into each of Rabin's IDA output files. Moreover, the Hash value of the original file is added to each of those output files to confirm the integrity of the file during reconstruction. Besides, the authentication key is used to communicate with all of the defined service providers during storage and reconstruction as well. It is stored into local secure key-store. By having a key to access the key-store, an ordinary non-technical user will be able to use dCloud to store and retrieve targeted file within defined public cloud storage services securely.

We introduce the fraud de-anonymization problem, that goes beyond fraud detection, to unmask the human masterminds responsible for posting search rank fraud in online systems. We collect and study search rank fraud data from Upwork, and survey the capabilities and behaviors of 58 search rank fraudsters recruited from 6 crowdsourcing sites. We propose Dolos, a fraud de-anonymization system that leverages traits and behaviors extracted from these studies, to attribute detected fraud to crowdsourcing site fraudsters, thus to real identities and bank accounts. We introduce MCDense, a min-cut dense component detection algorithm to uncover groups of user accounts controlled by different fraudsters, and leverage stylometry and deep learning to attribute them to crowdsourcing site profiles. Dolos correctly identified the owners of 95% of fraudster-controlled communities, and uncovered fraudsters who promoted as many as 97.5% of fraud apps we collected from Google Play. When evaluated on 13,087 apps (820,760 reviews), which we monitored over more than 6 months, Dolos identified 1,056 apps with suspicious reviewer groups. We report orthogonal evidence of their fraud, including fraud duplicates and fraud re-posts.

In this paper, the security performance of a dual-hop underlay cognitive radio (CR) system is investigated. In this system, we consider that the transmitted information by a source node S is forwarded by a multi-antenna relay R to its intended destination D. The relay performs the maximal-ratio combining (MRC) technique to process the multiple copies of the received signal. We also consider the presence of an eavesdropper who is attempting to intercept the transmitted information at both communication links, (i.e, S-R and R-D). In underlay cognitive radio networks (CRN), the source and the relay are required to adjust their transmission power to avoid causing interference to the primary user. Under this constraint, a closed-form expression of the secrecy outage probability is derived subject to Nakagami-m fading model. The derived expression is validated using Monte-Carlo simulation for various values of fading severity parameters as well as the number of MRC branches.

In Ad hoc networks the main purpose is communication without infrastructure and there are many implementations already done on that. There is little effort done for security to prevent threats in ad hoc networks (like MANETs). It is already proven that; there is no any centralized mechanism for defence against threats, such as a firewall, an intrusion detection system, or a proxy in ad hoc networks. Ad hoc networks are very convenient due to its features like self-maintenance, self-organizing and providing wireless communication. In Ad hoc networks there is no fixed infrastructure in which every node works like simply a router which stores and forwards packet to final destination. Due to these dynamic topology features, Ad hoc networks are anywhere, anytime. Therefore, it is necessary to make a secure mechanism for the ad hoc components so that with flexibility they have that security also. This paper shows the secure and flexible implementation about to protect any ad hoc networks. This proposed system design is perfect solution to provide security with flexibility by providing a hybrid system which combines ECC and MAES to detect and prevent Ad hoc network attacks using Intrusion detection system. The complete proposed system designed on NS 2.35 software using Ubuntu (Linux) OS.

Recently, the home healthcare system has emerged as one of the most useful technology for e-healthcare. Contrary to classical recording methods of patient's medical data, which are, based on paper documents, nowadays all this sensitive data can be managed and forwarded through digital systems. These make possible for both patients and healthcare workers to access medical data or receive remote medical treatment using wireless interfaces whenever and wherever. However, simplifying access to these sensitive and private data can directly put patient's health and life in danger. In this paper, we propose a secure and lightweight biometric-based remote patient authentication scheme using elliptic curve encryption through which two mobile healthcare system communication parties could authenticate each other in public mobile healthcare environments. The security and performance analysis demonstrate that our proposal achieves better security than other concurrent schemes, with lower storage, communication and computation costs.

Modern cyber-physical systems are complex networked computing systems that electronically control physical systems. Autonomous road vehicles are an important and increasingly ubiquitous instance. Unfortunately, their increasing complexity often leads to security vulnerabilities. Network connectivity exposes these vulnerable systems to remote software attacks that can result in real-world physical damage, including vehicle crashes and loss of control authority. We introduce an integrated architecture to provide provable security and safety assurance for cyber-physical systems by ensuring that safety-critical operations and control cannot be unintentionally affected by potentially malicious parts of the system. Fine-grained information flow control is used to design both hardware and software, determining how low-integrity information can affect high-integrity control decisions. This security assurance is used to improve end-to-end security across the entire cyber-physical system. We demonstrate this integrated approach by developing a mobile robotic testbed modeling a self-driving system and testing it with a malicious attack.

Many security and forensic analyses rely on the ability to fetch memory snapshots from a target machine. To date, the security community has relied on virtualization, external hardware or trusted hardware to obtain such snapshots. These techniques either sacrifice snapshot consistency or degrade the performance of applications executing atop the target. We present SnipSnap, a new snapshot acquisition system based on on-package DRAM technologies that offers snapshot consistency without excessively hurting the performance of the target's applications. We realize SnipSnap and evaluate its benefits using careful hardware emulation and software simulation, and report our results.

In Smart Grids (SGs), data aggregation process is essential in terms of limiting packet size, data transmission amount and data storage requirements. This paper presents a novel Domingo-Ferrer additive privacy based Secure Data Aggregation (SDA) scheme for Fog Computing based SGs (FCSG). The proposed protocol achieves end-to-end confidentiality while ensuring low communication and storage overhead. Data aggregation is performed at fog layer to reduce the amount of data to be processed and stored at cloud servers. As a result, the proposed protocol achieves better response time and less computational overhead compared to existing solutions. Moreover, due to hierarchical architecture of FCSG and additive homomorphic encryption consumer privacy is protected from third parties. Theoretical analysis evaluates the effects of packet size and number of packets on transmission overhead and the amount of data stored in cloud server. In parallel with the theoretical analysis, our performance evaluation results show that there is a significant improvement in terms of data transmission and storage efficiency. Moreover, security analysis proves that the proposed scheme successfully ensures the privacy of collected data.

Nowadays, the proliferation of smart, communication-enable devices is opening up many new opportunities of pervasive applications. A major requirement of pervasive applications is to be secured. The complexity to secure pervasive systems is to address a end-to-end security level: from the device to the services according to the entire life cycle of devices, applications and platform. In this article, we propose a solution combining both hardware and software elements to secure communications between devices and pervasive platform based on certificates issued from a Public Key Infrastructure. Our solution is implemented and validated with a real device extended by a secure element and our own Public Key Infrastructure.

Secure network coding realizes the secrecy of the message when the message is transmitted via noiseless network and a part of edges or a part of intermediate nodes are eavesdropped. In this framework, if the channels of the network has noise, we apply the error correction to noisy channel before applying the secure network coding. In contrast, secure physical layer network coding is a method to securely transmit a message by a combination of coding operation on nodes when the network is given as a set of noisy channels. In this paper, we give several examples of network, in which, secure physical layer network coding realizes a performance that cannot be realized by secure network coding.

Due to expansion of Internet and huge dataset, many organizations started to use cloud. Cloud Computing moves the application software and databases to the centralized large data centers, where the management of the data and services may not be fully trustworthy. Due to this cloud faces many threats. In this work, we study the problem of ensuring the integrity of data storage in Cloud Computing. To reduce the computational cost at user side during the integrity verification of their data, the notion of public verifiability has been proposed. Our approach is to create a new entity names Cloud Service Controller (CSC) which will help us to reduce the trust on the Third Party Auditor (TPA). We have strengthened the security model by using AES Encryption with SHA-S12 & tag generation. In this paper we get a brief introduction about the file upload phase, integrity of the file & Proof of Retrievability of the file.

This paper presents a contemporary review of communication architectures and topographies for MANET-connected Internet-of-Things (IoT) systems. Routing protocols for multi-hop MANETs are analyzed with a focus on the standardized Routing Protocol for Low-power and Lossy Networks. Various security threats and vulnerabilities in current MANET routing are described and security enhanced routing protocols and trust models presented as methodologies for supporting secure routing. Finally, the paper identifies some key research challenges in the emerging domain of MANET-IoT connectivity.

This study examines the secure transition for robotic surgery session. Surgeon sends set of instructions as data. The data is encapsulated with surgeon secure signature to conform surgeon identity. At the same time, patient information sends to the surgeon as a secure row of frames to estimate patient situation dependent on the real medical reports. Elliptic Curve Diffie-Hellman is use as an asymmetric encryption method. Here the session between surgeon console and interactive robot arm was achieved and supported with four secret keys. Two private keys are chosen on each side and two public keys are calculated from these private keys. These results indicate that the level of the security was improved by use asymmetric encryption rather than symmetric encryption. And by contributed four secret keys the patient information must be safer.

Permissionless blockchains allow the execution of arbitrary programs (called smart contracts), enabling mutually untrusted entities to interact without relying on trusted third parties. Despite their potential, repeated security concerns have shaken the trust in handling billions of USD by smart contracts. To address this problem, we present Securify, a security analyzer for Ethereum smart contracts that is scalable, fully automated, and able to prove contract behaviors as safe/unsafe with respect to a given property. Securify's analysis consists of two steps. First, it symbolically analyzes the contract's dependency graph to extract precise semantic information from the code. Then, it checks compliance and violation patterns that capture sufficient conditions for proving if a property holds or not. To enable extensibility, all patterns are specified in a designated domain-specific language. Securify is publicly released, it has analyzed 18K contracts submitted by its users, and is regularly used to conduct security audits by experts. We present an extensive evaluation of Securify over real-world Ethereum smart contracts and demonstrate that it can effectively prove the correctness of smart contracts and discover critical violations.

A mobile ad hoc network (MANET) is vulnerable to many types of attacks. Thus, security has turned out to be an important factor to facilitate secured communication between mobile nodes in a wireless environment. In this paper we propose a new approach to provide reliable and secure data transmission in MANETs under possible blackhole attacks based on ad hoc on-demand multipath distance vector (AOMDV) protocol and homomorphic encryption scheme for security. The performance of the proposed scheme is stable but that of AOMDV is found to be degrading with the intrusion of malicious nodes in the network. Simulation results show the improvement of packet delivery ratio and network throughput in the presence of blackhole nodes in our proposed scheme.

Data security in smart metering applications is important not only to secure the customer privacy but also to protect the power utility against fraud attempts. Usual deployment of metering applications rely on the power utility infrastructure, assuming its Advanced Metering Infrastructure (AMI) as trustworthy. This paper describes the design and deployment of a smart metering system focusing on the security of the AMI (smart meters, data aggregator on the field, Metering Data Collection system and metering database) considering the data processing on untrusted clouds. We discuss one use case of the SecureCloud project, an ongoing project that investigates how security and privacy requirements of smart grid applications can be met with a secure cloud platform based on Intel SGX enclaves. The paper describes the components of the advanced metering system as well as the security approach adopted to meet its requirements. A smart metering application has been prototyped in the SecureCloud platform and the integration challenges are discussed from the perspectives of security, privacy and scalability.

Implantable medical devices (IMDs) typically rely on proprietary protocols to wirelessly communicate with external device programmers. In this paper, we fully reverse engineer the proprietary protocol between a device programmer and a widely used commercial neurostimulator from one of the leading IMD manufacturers. For the reverse engineering, we follow a black-box approach and use inexpensive hardware equipment. We document the message format and the protocol state-machine, and show that the transmissions sent over the air are neither encrypted nor authenticated. Furthermore, we conduct several software radio-based attacks that could compromise the safety and privacy of patients, and investigate the feasibility of performing these attacks in real scenarios. Motivated by our findings, we propose a security architecture that allows for secure data exchange between the device programmer and the neurostimulator. It relies on using a patient»s physiological signal for generating a symmetric key in the neurostimulator, and transporting this key from the neurostimulator to the device programmer through a secret out-of-band (OOB) channel. Our solution allows the device programmer and the neurostimulator to agree on a symmetric session key without these devices needing to share any prior secrets; offers an effective and practical balance between security and permissive access in emergencies; requires only minor hardware changes in the devices; adds minimal computation and communication overhead; and provides forward and backward security. Finally, we implement a proof-of-concept of our solution.

Implementing a secure development lifecycle (SDL) presents increasing challenges to software developers as they must ensure software correctly integrates both underlying operating system security features while also managing dependencies on third-party libraries or executables. There are a growing number of security functions that require a close integration between the OS security features and software builds to ensure strong protection. Furthermore, as software platforms grow in complexity, they present many opportunities for misconfigurations and inadequate defenses. This challenge is especially prevalent for industrial control systems (ICS), which oten depend on both legacy sotware platforms, or out of date operating systems. This paper presents the AttackSurface Host Analyzer (AHA) tool, which is used to assess the security of a software platform through its integration with a host operating system. The tool collects data from the various platforms running on an OS, evaluates an array of security properties, and then introduces metrics and visualizations to provide feedback on the system's attack surface based on the external interconnections and the completeness of the available security protections. The paper then explores the attack surface of a variety of industry-standard ICS platforms to provide insight into the current degree of protection enabled by them.

Modern vehicles in Intelligent Transportation Systems (ITS) can communicate with each other as well as roadside infrastructure units (RSUs) in order to increase transportation efficiency and road safety. For example, there are techniques to alert drivers in advance about traffic incidents and to help them avoid congestion. Threats to these systems, on the other hand, can limit the benefits of these technologies. Securing ITS itself is an important concern in ITS design and implementation. In this paper, we provide a security model of ITS which extends the classic layered network security model with transportation security and information security, and gives a reference for designing ITS architectures. Based on this security model, we also present a classification of ITS threats for defense. Finally a proof-of-concept example with malicious nodes in an ITS system is also given to demonstrate the impact of attacks. We analyzed the threat of malicious nodes and their effects to commuters, like increasing toll fees, travel distances, and travel times etc. Experimental results from simulations based on Veins shows the threats will bring about 43.40% more total toll fees, 39.45% longer travel distances, and 63.10% more travel times.

Nowadays, Vehicular ad hoc network confronts many challenges in terms of security and privacy, due to the fact that data transmitted are diffused in an open access environment. However, highest of drivers want to maintain their information discreet and protected, and they do not want to share their confidential information. So, the private information of drivers who are distributed in this network must be protected against various threats that may damage their privacy. That is why, confidentiality, integrity and availability are the important security requirements in VANET. This paper focus on security threat in vehicle network especially on the availability of this network. Then we regard the rational attacker who decides to lead an attack based on its adversary's strategy to maximize its own attack interests. Our aim is to provide reliability and privacy of VANET system, by preventing attackers from violating and endangering the network. to ensure this objective, we adopt a tree structure called attack tree to model the attacker's potential attack strategies. Also, we join the countermeasures to the attack tree in order to build attack-defense tree for defending these attacks.