27 research outputs found

    Preserving Both Privacy and Utility in Network Trace Anonymization

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    As network security monitoring grows more sophisticated, there is an increasing need for outsourcing such tasks to third-party analysts. However, organizations are usually reluctant to share their network traces due to privacy concerns over sensitive information, e.g., network and system configuration, which may potentially be exploited for attacks. In cases where data owners are convinced to share their network traces, the data are typically subjected to certain anonymization techniques, e.g., CryptoPAn, which replaces real IP addresses with prefix-preserving pseudonyms. However, most such techniques either are vulnerable to adversaries with prior knowledge about some network flows in the traces, or require heavy data sanitization or perturbation, both of which may result in a significant loss of data utility. In this paper, we aim to preserve both privacy and utility through shifting the trade-off from between privacy and utility to between privacy and computational cost. The key idea is for the analysts to generate and analyze multiple anonymized views of the original network traces; those views are designed to be sufficiently indistinguishable even to adversaries armed with prior knowledge, which preserves the privacy, whereas one of the views will yield true analysis results privately retrieved by the data owner, which preserves the utility. We present the general approach and instantiate it based on CryptoPAn. We formally analyze the privacy of our solution and experimentally evaluate it using real network traces provided by a major ISP. The results show that our approach can significantly reduce the level of information leakage (e.g., less than 1\% of the information leaked by CryptoPAn) with comparable utility

    Stay Connected, Leave no Trace: Enhancing Security and Privacy in WiFi via Obfuscating Radiometric Fingerprints

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    The intrinsic hardware imperfection of WiFi chipsets manifests itself in the transmitted signal, leading to a unique radiometric fingerprint. This fingerprint can be used as an additional means of authentication to enhance security. In fact, recent works propose practical fingerprinting solutions that can be readily implemented in commercial-off-the-shelf devices. In this paper, we prove analytically and experimentally that these solutions are highly vulnerable to impersonation attacks. We also demonstrate that such a unique device-based signature can be abused to violate privacy by tracking the user device, and, as of today, users do not have any means to prevent such privacy attacks other than turning off the device. We propose RF-Veil, a radiometric fingerprinting solution that not only is robust against impersonation attacks but also protects user privacy by obfuscating the radiometric fingerprint of the transmitter for non-legitimate receivers. Specifically, we introduce a randomized pattern of phase errors to the transmitted signal such that only the intended receiver can extract the original fingerprint of the transmitter. In a series of experiments and analyses, we expose the vulnerability of adopting naive randomization to statistical attacks and introduce countermeasures. Finally, we show the efficacy of RF-Veil experimentally in protecting user privacy and enhancing security. More importantly, our proposed solution allows communicating with other devices, which do not employ RF-Veil.Comment: ACM Sigmetrics 2021 / In Proc. ACM Meas. Anal. Comput. Syst., Vol. 4, 3, Article 44 (December 2020

    Enhanced cryptographic approaches for SCADA network security.

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    Due to the overwhelming increase in open source code, off-the-shelf software packages, third party and vendor codes, along with the ease of getting information about hacking network security systems and attacking the well known holes in security systems, the problem of having a secure network system is much more difficult than before this boom in technology and information broadcast. What makes the problem even worse is trying to secure a network for real time control, such as a network using supervisory control and data acquisition (SCADA) systems, because now the problem has two faces: securing the real time control system and at the same time keeping the response time of the system in the acceptable range for the transactions\u27 level of service. There is a strong trend to chose security frameworks that have been popular in the e-commerce sites of the web, particularly because they proven to be very mature and secure for more than one and half decades. Examples include the transport level security (TLS) and its predecessor secured socket layer (SSL) framework that is based on the very popular public key cryptography and key distribution algorithms, such as Rivest, Shamir and Adleman (RSA), elliptic curve cryptography (ECC), and Diffie-Hellman. Despite the fact that these algorithms proved to be very powerful against most types of attacks, they are not tailored to secure SCADA networks, and consequently cause a significant degradation in the performance time of real time transactions. This dissertation offers two novel encryption algorithms for securing a SCADA network, the N-Secrecy and the Security Spectrum algorithms. N-Secrecy gave very good results when compared with the SSL; with N-Secrecy performance time in the range of one thousandth of the SSL. The Security Spectrum approach moved the encryption methodology from using numerical representations into using a physical representation based on modeling the conditions of the two communicating parties with a system of non-linear polynomials and then using computer algebra techniques. Both approaches have the potential to significantly enhance the security of commercial SCADA installations

    Development of a Security-Focused Multi-Channel Communication Protocol and Associated Quality of Secure Service (QoSS) Metrics

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    The threat of eavesdropping, and the challenge of recognizing and correcting for corrupted or suppressed information in communication systems is a consistent challenge. Effectively managing protection mechanisms requires an ability to accurately gauge the likelihood or severity of a threat, and adapt the security features available in a system to mitigate the threat. This research focuses on the design and development of a security-focused communication protocol at the session-layer based on a re-prioritized communication architecture model and associated metrics. From a probabilistic model that considers data leakage and data corruption as surrogates for breaches of confidentiality and integrity, a set of metrics allows the direct and repeatable quantification of the security available in single- or multi-channel networks. The quantification of security is based directly upon the probabilities that adversarial listeners and malicious disruptors are able to gain access to or change the original message. Fragmenting data across multiple channels demonstrates potential improvements to confidentiality, while duplication improves the integrity of the data against disruptions. Finally, the model and metrics are exercised in simulation. The ultimate goal is to minimize the information available to adversaries

    LoRaWAN Physical Layer-Based Attacks and Countermeasures, A Review

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    As LoRaWAN is one of the most popular long-range wireless protocols among low-power IoT applications, more and more focus is shifting towards security. In particular, physical layer topics become relevant to improve the security of LoRaWAN nodes, which are often limited in terms of computational power and communication resources. To this end, e.g., detection methods for wireless attacks improve the integrity and robustness of LoRaWAN access. Further, wireless physical layer techniques have potential to enhance key refreshment and device authentication. In this work, we aim to provide a comprehensive review of various vulnerabilities, countermeasures and security enhancing features concerning the LoRaWAN physical layer. Afterwards, we discuss the impact of the reviewed topics on LoRaWAN security and, subsequently, we identify research gaps as well as promising future research directions

    SUTMS - Unified Threat Management Framework for Home Networks

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    Home networks were initially designed for web browsing and non-business critical applications. As infrastructure improved, internet broadband costs decreased, and home internet usage transferred to e-commerce and business-critical applications. Today’s home computers host personnel identifiable information and financial data and act as a bridge to corporate networks via remote access technologies like VPN. The expansion of remote work and the transition to cloud computing have broadened the attack surface for potential threats. Home networks have become the extension of critical networks and services, hackers can get access to corporate data by compromising devices attacked to broad- band routers. All these challenges depict the importance of home-based Unified Threat Management (UTM) systems. There is a need of unified threat management framework that is developed specifically for home and small networks to address emerging security challenges. In this research, the proposed Smart Unified Threat Management (SUTMS) framework serves as a comprehensive solution for implementing home network security, incorporating firewall, anti-bot, intrusion detection, and anomaly detection engines into a unified system. SUTMS is able to provide 99.99% accuracy with 56.83% memory improvements. IPS stands out as the most resource-intensive UTM service, SUTMS successfully reduces the performance overhead of IDS by integrating it with the flow detection mod- ule. The artifact employs flow analysis to identify network anomalies and categorizes encrypted traffic according to its abnormalities. SUTMS can be scaled by introducing optional functions, i.e., routing and smart logging (utilizing Apriori algorithms). The research also tackles one of the limitations identified by SUTMS through the introduction of a second artifact called Secure Centralized Management System (SCMS). SCMS is a lightweight asset management platform with built-in security intelligence that can seamlessly integrate with a cloud for real-time updates

    Security and Privacy in Bluetooth Low Energy

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    Scalable reconfigurable computing leveraging latency-insensitive channels

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 190-197).Traditionally, FPGAs have been confined to the limited role of small, low-volume ASIC replacements and as circuit emulators. However, continued Moore's law scaling has given FPGAs new life as accelerators for applications that map well to fine-grained parallel substrates. Examples of such applications include processor modelling, compression, and digital signal processing. Although FPGAs continue to increase in size, some interesting designs still fail to fit in to a single FPGA. Many tools exist that partition RTL descriptions across FPGAs. Unfortunately, existing tools have low performance due to the inefficiency of maintaining the cycle-by-cycle behavior of RTL among discrete FPGAs. These tools are unsuitable for use in FPGA program acceleration, as the purpose of an accelerator is to make applications run faster. This thesis presents latency-insensitive channels, a language-level mechanism by which programmers express points in their their design at which the cycle-by-cycle behavior of the design may be modified by the compiler. By decoupling the timing of portions of the RTL from the high-level function of the program, designs may be mapped to multiple FPGAs without suffering the performance degradation observed in existing tools. This thesis demonstrates, using a diverse set of large designs, that FPGA programs described in terms of latency-insensitive channels obtain significant gains in design feasibility, compilation time, and run-time when mapped to multiple FPGAs.by Kermin Elliott Fleming, Jr.Ph.D
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