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class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2409.07444">arXiv:2409.07444</a> <span> [<a href="https://arxiv.org/pdf/2409.07444">pdf</a>, <a href="https://arxiv.org/format/2409.07444">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Networking and Internet Architecture">cs.NI</span> </div> </div> <p class="title is-5 mathjax"> Echoes of Privacy: Uncovering the Profiling Practices of Voice Assistants </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Khezresmaeilzadeh%2C+T">Tina Khezresmaeilzadeh</a>, <a href="/search/?searchtype=author&query=Zhu%2C+E">Elaine Zhu</a>, <a href="/search/?searchtype=author&query=Grieco%2C+K">Kiersten Grieco</a>, <a href="/search/?searchtype=author&query=Dubois%2C+D+J">Daniel J. Dubois</a>, <a href="/search/?searchtype=author&query=Psounis%2C+K">Konstantinos Psounis</a>, <a href="/search/?searchtype=author&query=Choffnes%2C+D">David Choffnes</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2409.07444v2-abstract-short" style="display: inline;"> Many companies, including Google, Amazon, and Apple, offer voice assistants as a convenient solution for answering general voice queries and accessing their services. These voice assistants have gained popularity and can be easily accessed through various smart devices such as smartphones, smart speakers, smartwatches, and an increasing array of other devices. However, this convenience comes with… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.07444v2-abstract-full').style.display = 'inline'; document.getElementById('2409.07444v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2409.07444v2-abstract-full" style="display: none;"> Many companies, including Google, Amazon, and Apple, offer voice assistants as a convenient solution for answering general voice queries and accessing their services. These voice assistants have gained popularity and can be easily accessed through various smart devices such as smartphones, smart speakers, smartwatches, and an increasing array of other devices. However, this convenience comes with potential privacy risks. For instance, while companies vaguely mention in their privacy policies that they may use voice interactions for user profiling, it remains unclear to what extent this profiling occurs and whether voice interactions pose greater privacy risks compared to other interaction modalities. In this paper, we conduct 1171 experiments involving a total of 24530 queries with different personas and interaction modalities over the course of 20 months to characterize how the three most popular voice assistants profile their users. We analyze factors such as the labels assigned to users, their accuracy, the time taken to assign these labels, differences between voice and web interactions, and the effectiveness of profiling remediation tools offered by each voice assistant. Our findings reveal that profiling can happen without interaction, can be incorrect and inconsistent at times, may take several days to weeks for changes to occur, and can be influenced by the interaction modality. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.07444v2-abstract-full').style.display = 'none'; document.getElementById('2409.07444v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 13 September, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 11 September, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2401.14332">arXiv:2401.14332</a> <span> [<a href="https://arxiv.org/pdf/2401.14332">pdf</a>, <a href="https://arxiv.org/format/2401.14332">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> SunBlock: Cloudless Protection for IoT Systems </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Safronov%2C+V">Vadim Safronov</a>, <a href="/search/?searchtype=author&query=Mandalari%2C+A+M">Anna Maria Mandalari</a>, <a href="/search/?searchtype=author&query=Dubois%2C+D+J">Daniel J. Dubois</a>, <a href="/search/?searchtype=author&query=Choffnes%2C+D">David Choffnes</a>, <a href="/search/?searchtype=author&query=Haddadi%2C+H">Hamed Haddadi</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2401.14332v1-abstract-short" style="display: inline;"> With an increasing number of Internet of Things (IoT) devices present in homes, there is a rise in the number of potential information leakage channels and their associated security threats and privacy risks. Despite a long history of attacks on IoT devices in unprotected home networks, the problem of accurate, rapid detection and prevention of such attacks remains open. Many existing IoT protecti… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2401.14332v1-abstract-full').style.display = 'inline'; document.getElementById('2401.14332v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2401.14332v1-abstract-full" style="display: none;"> With an increasing number of Internet of Things (IoT) devices present in homes, there is a rise in the number of potential information leakage channels and their associated security threats and privacy risks. Despite a long history of attacks on IoT devices in unprotected home networks, the problem of accurate, rapid detection and prevention of such attacks remains open. Many existing IoT protection solutions are cloud-based, sometimes ineffective, and might share consumer data with unknown third parties. This paper investigates the potential for effective IoT threat detection locally, on a home router, using AI tools combined with classic rule-based traffic-filtering algorithms. Our results show that with a slight rise of router hardware resources caused by machine learning and traffic filtering logic, a typical home router instrumented with our solution is able to effectively detect risks and protect a typical home IoT network, equaling or outperforming existing popular solutions, without any effects on benign IoT functionality, and without relying on cloud services and third parties. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2401.14332v1-abstract-full').style.display = 'none'; document.getElementById('2401.14332v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 25 January, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">This paper is accepted at Passive and Active Measurement (PAM) conference 2024</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2304.03045">arXiv:2304.03045</a> <span> [<a href="https://arxiv.org/pdf/2304.03045">pdf</a>, <a href="https://arxiv.org/format/2304.03045">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> </div> </div> <p class="title is-5 mathjax"> Protected or Porous: A Comparative Analysis of Threat Detection Capability of IoT Safeguards </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Mandalari%2C+A+M">Anna Maria Mandalari</a>, <a href="/search/?searchtype=author&query=Haddadi%2C+H">Hamed Haddadi</a>, <a href="/search/?searchtype=author&query=Dubois%2C+D+J">Daniel J. Dubois</a>, <a href="/search/?searchtype=author&query=Choffnes%2C+D">David Choffnes</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2304.03045v1-abstract-short" style="display: inline;"> Consumer Internet of Things (IoT) devices are increasingly common, from smart speakers to security cameras, in homes. Along with their benefits come potential privacy and security threats. To limit these threats a number of commercial services have become available (IoT safeguards). The safeguards claim to provide protection against IoT privacy risks and security threats. However, the effectivenes… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2304.03045v1-abstract-full').style.display = 'inline'; document.getElementById('2304.03045v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2304.03045v1-abstract-full" style="display: none;"> Consumer Internet of Things (IoT) devices are increasingly common, from smart speakers to security cameras, in homes. Along with their benefits come potential privacy and security threats. To limit these threats a number of commercial services have become available (IoT safeguards). The safeguards claim to provide protection against IoT privacy risks and security threats. However, the effectiveness and the associated privacy risks of these safeguards remains a key open question. In this paper, we investigate the threat detection capabilities of IoT safeguards for the first time. We develop and release an approach for automated safeguards experimentation to reveal their response to common security threats and privacy risks. We perform thousands of automated experiments using popular commercial IoT safeguards when deployed in a large IoT testbed. Our results indicate not only that these devices may be ineffective in preventing risks, but also their cloud interactions and data collection operations may introduce privacy risks for the households that adopt them. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2304.03045v1-abstract-full').style.display = 'none'; document.getElementById('2304.03045v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 6 April, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2107.10830">arXiv:2107.10830</a> <span> [<a href="https://arxiv.org/pdf/2107.10830">pdf</a>, <a href="https://arxiv.org/format/2107.10830">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> </div> </div> <p class="title is-5 mathjax"> ZLeaks: Passive Inference Attacks on Zigbee based Smart Homes </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Shafqat%2C+N">Narmeen Shafqat</a>, <a href="/search/?searchtype=author&query=Dubois%2C+D+J">Daniel J. Dubois</a>, <a href="/search/?searchtype=author&query=Choffnes%2C+D">David Choffnes</a>, <a href="/search/?searchtype=author&query=Schulman%2C+A">Aaron Schulman</a>, <a href="/search/?searchtype=author&query=Bharadia%2C+D">Dinesh Bharadia</a>, <a href="/search/?searchtype=author&query=Ranganathan%2C+A">Aanjhan Ranganathan</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2107.10830v2-abstract-short" style="display: inline;"> Zigbee is an energy-efficient wireless IoT protocol that is increasingly being deployed in smart home settings. In this work, we analyze the privacy guarantees of Zigbee protocol. Specifically, we present ZLeaks, a tool that passively identifies in-home devices or events from the encrypted Zigbee traffic by 1) inferring a single application layer (APL) command in the event's traffic, and 2) exploi… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2107.10830v2-abstract-full').style.display = 'inline'; document.getElementById('2107.10830v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2107.10830v2-abstract-full" style="display: none;"> Zigbee is an energy-efficient wireless IoT protocol that is increasingly being deployed in smart home settings. In this work, we analyze the privacy guarantees of Zigbee protocol. Specifically, we present ZLeaks, a tool that passively identifies in-home devices or events from the encrypted Zigbee traffic by 1) inferring a single application layer (APL) command in the event's traffic, and 2) exploiting the device's periodic reporting pattern and interval. This enables an attacker to infer user's habits or determine if the smart home is vulnerable to unauthorized entry. We evaluated ZLeaks' efficacy on 19 unique Zigbee devices across several categories and 5 popular smart hubs in three different scenarios; controlled RF shield, living smart-home IoT lab, and third-party Zigbee captures. We were able to i) identify unknown events and devices (without a-priori device signatures) using command inference approach with 83.6% accuracy, ii) automatically extract device's reporting signatures, iii) determine known devices using the reporting signatures with 99.8% accuracy, and iv) identify APL commands in a public capture with 91.2% accuracy. In short, we highlight the trade-off between designing a low-power, low-cost wireless network and achieving privacy guarantees. We have also released ZLeaks tool for the benefit of the research community. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2107.10830v2-abstract-full').style.display = 'none'; document.getElementById('2107.10830v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 26 November, 2021; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 22 July, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2021. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">An updated version of the authors' previous submission (arXiv:2107.10830). It has been accepted at the 20th International Conference on Applied Cryptography and Network Security, ACNS 2022</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2105.05162">arXiv:2105.05162</a> <span> [<a href="https://arxiv.org/pdf/2105.05162">pdf</a>, <a href="https://arxiv.org/format/2105.05162">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Networking and Internet Architecture">cs.NI</span> </div> </div> <p class="title is-5 mathjax"> Blocking without Breaking: Identification and Mitigation of Non-Essential IoT Traffic </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Mandalari%2C+A+M">Anna Maria Mandalari</a>, <a href="/search/?searchtype=author&query=Dubois%2C+D+J">Daniel J. Dubois</a>, <a href="/search/?searchtype=author&query=Kolcun%2C+R">Roman Kolcun</a>, <a href="/search/?searchtype=author&query=Paracha%2C+M+T">Muhammad Talha Paracha</a>, <a href="/search/?searchtype=author&query=Haddadi%2C+H">Hamed Haddadi</a>, <a href="/search/?searchtype=author&query=Choffnes%2C+D">David Choffnes</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2105.05162v1-abstract-short" style="display: inline;"> Despite the prevalence of Internet of Things (IoT) devices, there is little information about the purpose and risks of the Internet traffic these devices generate, and consumers have limited options for controlling those risks. A key open question is whether one can mitigate these risks by automatically blocking some of the Internet connections from IoT devices, without rendering the devices inope… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2105.05162v1-abstract-full').style.display = 'inline'; document.getElementById('2105.05162v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2105.05162v1-abstract-full" style="display: none;"> Despite the prevalence of Internet of Things (IoT) devices, there is little information about the purpose and risks of the Internet traffic these devices generate, and consumers have limited options for controlling those risks. A key open question is whether one can mitigate these risks by automatically blocking some of the Internet connections from IoT devices, without rendering the devices inoperable. In this paper, we address this question by developing a rigorous methodology that relies on automated IoT-device experimentation to reveal which network connections (and the information they expose) are essential, and which are not. We further develop strategies to automatically classify network traffic destinations as either required (i.e., their traffic is essential for devices to work properly) or not, hence allowing firewall rules to block traffic sent to non-required destinations without breaking the functionality of the device. We find that indeed 16 among the 31 devices we tested have at least one blockable non-required destination, with the maximum number of blockable destinations for a device being 11. We further analyze the destination of network traffic and find that all third parties observed in our experiments are blockable, while first and support parties are neither uniformly required or non-required. Finally, we demonstrate the limitations of existing blocklists on IoT traffic, propose a set of guidelines for automatically limiting non-essential IoT traffic, and we develop a prototype system that implements these guidelines. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2105.05162v1-abstract-full').style.display = 'none'; document.getElementById('2105.05162v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 11 May, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2021. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Privacy Enhancing Technologies Symposium (PETS) 2021 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2009.01880">arXiv:2009.01880</a> <span> [<a href="https://arxiv.org/pdf/2009.01880">pdf</a>, <a href="https://arxiv.org/format/2009.01880">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Networking and Internet Architecture">cs.NI</span> </div> </div> <p class="title is-5 mathjax"> A Haystack Full of Needles: Scalable Detection of IoT Devices in the Wild </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Saidi%2C+S+J">Said Jawad Saidi</a>, <a href="/search/?searchtype=author&query=Mandalari%2C+A+M">Anna Maria Mandalari</a>, <a href="/search/?searchtype=author&query=Kolcun%2C+R">Roman Kolcun</a>, <a href="/search/?searchtype=author&query=Haddadi%2C+H">Hamed Haddadi</a>, <a href="/search/?searchtype=author&query=Dubois%2C+D+J">Daniel J. Dubois</a>, <a href="/search/?searchtype=author&query=Choffnes%2C+D">David Choffnes</a>, <a href="/search/?searchtype=author&query=Smaragdakis%2C+G">Georgios Smaragdakis</a>, <a href="/search/?searchtype=author&query=Feldmann%2C+A">Anja Feldmann</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2009.01880v3-abstract-short" style="display: inline;"> Consumer Internet of Things (IoT) devices are extremely popular, providing users with rich and diverse functionalities, from voice assistants to home appliances. These functionalities often come with significant privacy and security risks, with notable recent large scale coordinated global attacks disrupting large service providers. Thus, an important first step to address these risks is to know w… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2009.01880v3-abstract-full').style.display = 'inline'; document.getElementById('2009.01880v3-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2009.01880v3-abstract-full" style="display: none;"> Consumer Internet of Things (IoT) devices are extremely popular, providing users with rich and diverse functionalities, from voice assistants to home appliances. These functionalities often come with significant privacy and security risks, with notable recent large scale coordinated global attacks disrupting large service providers. Thus, an important first step to address these risks is to know what IoT devices are where in a network. While some limited solutions exist, a key question is whether device discovery can be done by Internet service providers that only see sampled flow statistics. In particular, it is challenging for an ISP to efficiently and effectively track and trace activity from IoT devices deployed by its millions of subscribers --all with sampled network data. In this paper, we develop and evaluate a scalable methodology to accurately detect and monitor IoT devices at subscriber lines with limited, highly sampled data in-the-wild. Our findings indicate that millions of IoT devices are detectable and identifiable within hours, both at a major ISP as well as an IXP, using passive, sparsely sampled network flow headers. Our methodology is able to detect devices from more than 77% of the studied IoT manufacturers, including popular devices such as smart speakers. While our methodology is effective for providing network analytics, it also highlights significant privacy consequences. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2009.01880v3-abstract-full').style.display = 'none'; document.getElementById('2009.01880v3-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 30 September, 2020; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 3 September, 2020; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2020. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Accepted at the ACM Internet Measurement Conference 2020 (IMC'20)</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2003.07133">arXiv:2003.07133</a> <span> [<a href="https://arxiv.org/pdf/2003.07133">pdf</a>, <a href="https://arxiv.org/format/2003.07133">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Networking and Internet Architecture">cs.NI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> </div> </div> <p class="title is-5 mathjax"> Towards Automatic Identification and Blocking of Non-Critical IoT Traffic Destinations </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Mandalari%2C+A+M">Anna Maria Mandalari</a>, <a href="/search/?searchtype=author&query=Kolcun%2C+R">Roman Kolcun</a>, <a href="/search/?searchtype=author&query=Haddadi%2C+H">Hamed Haddadi</a>, <a href="/search/?searchtype=author&query=Dubois%2C+D+J">Daniel J. Dubois</a>, <a href="/search/?searchtype=author&query=Choffnes%2C+D">David Choffnes</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2003.07133v1-abstract-short" style="display: inline;"> The consumer Internet of Things (IoT) space has experienced a significant rise in popularity in the recent years. From smart speakers, to baby monitors, and smart kettles and TVs, these devices are increasingly found in households around the world while users may be unaware of the risks associated with owning these devices. Previous work showed that these devices can threaten individuals' privacy… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2003.07133v1-abstract-full').style.display = 'inline'; document.getElementById('2003.07133v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2003.07133v1-abstract-full" style="display: none;"> The consumer Internet of Things (IoT) space has experienced a significant rise in popularity in the recent years. From smart speakers, to baby monitors, and smart kettles and TVs, these devices are increasingly found in households around the world while users may be unaware of the risks associated with owning these devices. Previous work showed that these devices can threaten individuals' privacy and security by exposing information online to a large number of service providers and third party analytics services. Our analysis shows that many of these Internet connections (and the information they expose) are neither critical, nor even essential to the operation of these devices. However, automatically separating out critical from non-critical network traffic for an IoT device is nontrivial, and requires expert analysis based on manual experimentation in a controlled setting. In this paper, we investigate whether it is possible to automatically classify network traffic destinations as either critical (essential for devices to function properly) or not, hence allowing the home gateway to act as a selective firewall to block undesired, non-critical destinations. Our initial results demonstrate that some IoT devices contact destinations that are not critical to their operation, and there is no impact on device functionality if these destinations are blocked. We take the first steps towards designing and evaluating IoTrimmer, a framework for automated testing and analysis of various destinations contacted by devices, and selectively blocking the ones that do not impact device functionality. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2003.07133v1-abstract-full').style.display = 'none'; document.getElementById('2003.07133v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 16 March, 2020; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2020. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">5 pages, 1 figure, 3 tables</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1202.2509">arXiv:1202.2509</a> <span> [<a href="https://arxiv.org/pdf/1202.2509">pdf</a>, <a href="https://arxiv.org/format/1202.2509">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Distributed, Parallel, and Cluster Computing">cs.DC</span> </div> </div> <p class="title is-5 mathjax"> DEPAS: A Decentralized Probabilistic Algorithm for Auto-Scaling </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Calcavecchia%2C+N+M">Nicolo M. Calcavecchia</a>, <a href="/search/?searchtype=author&query=Caprarescu%2C+B+A">Bogdan Alexandru Caprarescu</a>, <a href="/search/?searchtype=author&query=Di+Nitto%2C+E">Elisabetta Di Nitto</a>, <a href="/search/?searchtype=author&query=Dubois%2C+D+J">Daniel J. Dubois</a>, <a href="/search/?searchtype=author&query=Petcu%2C+D">Dana Petcu</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1202.2509v1-abstract-short" style="display: inline;"> The dynamic provisioning of virtualized resources offered by cloud computing infrastructures allows applications deployed in a cloud environment to automatically increase and decrease the amount of used resources. This capability is called auto-scaling and its main purpose is to automatically adjust the scale of the system that is running the application to satisfy the varying workload with minimu… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1202.2509v1-abstract-full').style.display = 'inline'; document.getElementById('1202.2509v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1202.2509v1-abstract-full" style="display: none;"> The dynamic provisioning of virtualized resources offered by cloud computing infrastructures allows applications deployed in a cloud environment to automatically increase and decrease the amount of used resources. This capability is called auto-scaling and its main purpose is to automatically adjust the scale of the system that is running the application to satisfy the varying workload with minimum resource utilization. The need for auto-scaling is particularly important during workload peaks, in which applications may need to scale up to extremely large-scale systems. Both the research community and the main cloud providers have already developed auto-scaling solutions. However, most research solutions are centralized and not suitable for managing large-scale systems, moreover cloud providers' solutions are bound to the limitations of a specific provider in terms of resource prices, availability, reliability, and connectivity. In this paper we propose DEPAS, a decentralized probabilistic auto-scaling algorithm integrated into a P2P architecture that is cloud provider independent, thus allowing the auto-scaling of services over multiple cloud infrastructures at the same time. Our simulations, which are based on real service traces, show that our approach is capable of: (i) keeping the overall utilization of all the instantiated cloud resources in a target range, (ii) maintaining service response times close to the ones obtained using optimal centralized auto-scaling approaches. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1202.2509v1-abstract-full').style.display = 'none'; document.getElementById('1202.2509v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 12 February, 2012; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2012. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Submitted to Springer Computing</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Report number:</span> Technical Report 2012.5, Politecnico di Milano </p> </li> </ol> <div class="is-hidden-tablet">  <span class="help" style="display: inline-block;"><a href="https://github.com/arXiv/arxiv-search/releases">Search v0.5.6 released 2020-02-24</a>  </span> </div> </div> </main> <footer> <div class="columns is-desktop" role="navigation" aria-label="Secondary">  <div class="column"> <div class="columns"> <div class="column"> <ul class="nav-spaced"> <li><a href="https://info.arxiv.org/about">About</a></li> <li><a href="https://info.arxiv.org/help">Help</a></li> </ul> </div> <div class="column"> <ul class="nav-spaced"> <li> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" class="icon filter-black" role="presentation"><title>contact arXiv</title><desc>Click here to contact arXiv</desc><path d="M502.3 190.8c3.9-3.1 9.7-.2 9.7 4.7V400c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48V195.6c0-5 5.7-7.8 9.7-4.7 22.4 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