MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM)最新文献_第4页

Cyber Vulnerability Implantation Revisited 重新审视网络漏洞植入

MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM) Pub Date : 2021-11-29 DOI: 10.1109/MILCOM52596.2021.9652921

J. Sigholm, Emil Larsson

{"title":"Cyber Vulnerability Implantation Revisited","authors":"J. Sigholm, Emil Larsson","doi":"10.1109/MILCOM52596.2021.9652921","DOIUrl":"https://doi.org/10.1109/MILCOM52596.2021.9652921","url":null,"abstract":"In this paper we revisit a study presented at MILCOM 2014. Our goal then was to determine the utility of implanting a vulnerability into a cybersecurity software protocol to an actor planning to execute an offensive cyber operation. Based on a case study describing the then recently discovered Heartbleed bug as an offensive cyber operation, a model was devised to estimate the adoption rate of an implanted flaw in OpenSSL. Using the adoption rate of the cryptographic protocol Transport Layer Security version 1.2 as a proxy, we predicted that the global adoption of the vulnerability of at least 50% would take approximately three years, while surpassing 75% adoption would take four years. Compared to subsequently collected real-world data, these forecasts turned out to be surprisingly accurate. An evaluation of our proposed model shows that it yields results with a root-mean-square error of only 1.2% over the forecasting period. Thus, it has a significant degree of predictive power. Although the model may not be generalizable to describe the adoption of any software protocol, the finding helps validate our previously drawn conclusion that exploiting implanted cyber vulnerabilities, in a scenario like the one presented, requires a planning horizon of multiple years. However, as society becomes further dependent on the cyber domain, the utility of intentional vulnerability implantation is likely an exercise in diminishing returns. For a defender, however, our model development process could be useful to forecast the time required for flawed protocols to be phased out.","PeriodicalId":187645,"journal":{"name":"MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124192484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Complementary Sequence Construction for Constant-Envelope OFDM Transmission Enabling Nonlinear Amplification and Clipping 支持非线性放大和裁剪的恒包络OFDM传输互补序列构建

MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM) Pub Date : 2021-11-29 DOI: 10.1109/MILCOM52596.2021.9653128

Kyle Willstatter, M. Zoltowski

引用次数: 0

Poisoning Attacks and Data Sanitization Mitigations for Machine Learning Models in Network Intrusion Detection Systems 网络入侵检测系统中机器学习模型的中毒攻击和数据消毒缓解

MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM) Pub Date : 2021-11-29 DOI: 10.1109/MILCOM52596.2021.9652916

S. Venkatesan, Harshvardhan Digvijay Sikka, R. Izmailov, R. Chadha, Alina Oprea, Michael J. de Lucia

{"title":"Poisoning Attacks and Data Sanitization Mitigations for Machine Learning Models in Network Intrusion Detection Systems","authors":"S. Venkatesan, Harshvardhan Digvijay Sikka, R. Izmailov, R. Chadha, Alina Oprea, Michael J. de Lucia","doi":"10.1109/MILCOM52596.2021.9652916","DOIUrl":"https://doi.org/10.1109/MILCOM52596.2021.9652916","url":null,"abstract":"Among many application domains of machine learning in real-world settings, cyber security can benefit from more automated techniques to combat sophisticated adversaries. Modern network intrusion detection systems leverage machine learning models on network logs to proactively detect cyber attacks. However, the risk of adversarial attacks against machine learning used in these cyber settings is not fully explored. In this paper, we investigate poisoning attacks at training time against machine learning models in constrained cyber environments such as network intrusion detection; we also explore mitigations of such attacks based on training data sanitization. We consider the setting of poisoning availability attacks, in which an attacker can insert a set of poisoned samples at training time with the goal of degrading the accuracy of the deployed model. We design a white-box, realizable poisoning attack that reduced the original model accuracy from 95% to less than 50 % by generating mislabeled samples in close vicinity of a selected subset of training points. We also propose a novel Nested Training method as a defense against these attacks. Our defense includes a diversified ensemble of classifiers, each trained on a different subset of the training set. We use the disagreement of the classifiers' predictions as a data sanitization method, and show that an ensemble of 10 SVM classifiers is resilient to a large fraction of poisoning samples, up to 30% of the training data.","PeriodicalId":187645,"journal":{"name":"MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129864840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Optimizing Flows in Changing Tree-based Sensor Networks 基于变化树的传感器网络流优化

MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM) Pub Date : 2021-11-29 DOI: 10.1109/MILCOM52596.2021.9653006

Albert Williams, D. Towsley

引用次数: 0

Propagator Rooting Method Direction of Arrival Estimation Based on Real Data 基于实际数据的传播子生根法到达方向估计

MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM) Pub Date : 2021-11-29 DOI: 10.1109/MILCOM52596.2021.9653081

N. Tayem, Ahmed A. Hussain, Vinay Reddy Veramareddy, A. Soliman, J. Alghazo

引用次数: 1

Towards a COTS-Enabled Federated Cloud Architecture for Adaptive C2 in Coalition Tactical Operations: A Performance Analysis of Kubernetes 在联盟战术作战中，面向自适应C2的支持cots的联邦云架构:Kubernetes的性能分析

MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM) Pub Date : 2021-11-29 DOI: 10.1109/MILCOM52596.2021.9653050

Mattia Fogli, Geert L. J. Pingen, Thomas Kudla, S. Webb, Niranjan Suri, H. Bastiaansen

{"title":"Towards a COTS-Enabled Federated Cloud Architecture for Adaptive C2 in Coalition Tactical Operations: A Performance Analysis of Kubernetes","authors":"Mattia Fogli, Geert L. J. Pingen, Thomas Kudla, S. Webb, Niranjan Suri, H. Bastiaansen","doi":"10.1109/MILCOM52596.2021.9653050","DOIUrl":"https://doi.org/10.1109/MILCOM52596.2021.9653050","url":null,"abstract":"Nowadays, ever-increasing processing and storage resources are available at all echelons, from operations centers to tactical units. However, tactical-edge communications still suffer from scarce network resources such as limited bandwidth, intermittent connectivity, and variable latency. In addition, modern military missions typically involve coalition operations, where heterogeneous mission partners (even belonging to different nations) cooperate in the field. As a result, the distribution of mission-critical information is more complicated than ever. On the one hand, the dynamic nature of the tactical environment frequently disrupts communications. On the other hand, individual resource-sharing policies prevent mission partners from taking full advantage of the available resources in situ. The NATO IST-168 RTG has been exploring commercial-off-the-shelf orchestration technologies for implementing a federated cloud architecture that enables adaptive information processing and dissemination while living within the constraints of the tactical domain. This paper is a follow-up study that assesses the behaviour of Kubernetes under the disadvantaged network conditions characterizing tactical edge networks.","PeriodicalId":187645,"journal":{"name":"MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122389480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Congestion Aware Intent-Based Routing using Graph Neural Networks for Improved Quality of Experience in Heterogeneous Networks 基于拥塞感知意图路由的图神经网络在异构网络中的应用

MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM) Pub Date : 2021-11-29 DOI: 10.1109/MILCOM52596.2021.9652977

Suzanna Lamar, J. Gosselin, Ivan Caceres, Sarah Kapple, A. Jayasumana

{"title":"Congestion Aware Intent-Based Routing using Graph Neural Networks for Improved Quality of Experience in Heterogeneous Networks","authors":"Suzanna Lamar, J. Gosselin, Ivan Caceres, Sarah Kapple, A. Jayasumana","doi":"10.1109/MILCOM52596.2021.9652977","DOIUrl":"https://doi.org/10.1109/MILCOM52596.2021.9652977","url":null,"abstract":"Making use of spectrally diverse communications links to re-route traffic in response to dynamic environments to manage network bottlenecks has become essential in order to guarantee message delivery across heterogeneous networks. We propose an innovative, proactive Congestion Aware Intent-Based Routing (CONAIR) architecture that can select among available communication link resources based on quality of service (QoS) metrics to support continuous information exchange between networked participants. The CONAIR architecture utilizes a Network Controller (NC) and artificial intelligence (AI) to re-route traffic based on traffic priority, fundamental to increasing end user quality of experience (QoE) and mission effectiveness. The CONAIR architecture provides network behavior prediction, and can mitigate congestion prior to its occurrence unlike traditional static routing techniques, e.g. Open Shortest Path First (OSPF), which are prone to congestion due to infrequent routing table updates. Modeling and simulation (M&S) was performed on a multi-hop network in order to characterize the resiliency and scalability benefits of CONAIR over OSPF routing-based frameworks. Results demonstrate that for varying traffic profiles, packet loss and end-to-end latency is minimized.","PeriodicalId":187645,"journal":{"name":"MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121115491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Direct-Sequence Spread Spectrum with Signal Space Diversity for High Resistance to Jamming 具有信号空间分集的直接序列扩频具有高抗干扰性

MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM) Pub Date : 2021-11-29 DOI: 10.1109/MILCOM52596.2021.9652967

Tarak Arbi, B. Geller, O. Pasquero

引用次数: 0

Massive MIMO: review and a case for the 12 GHz band 大规模MIMO:回顾和12ghz频段的案例

MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM) Pub Date : 2021-11-29 DOI: 10.1109/MILCOM52596.2021.9652931

D. Erricolo, William P. Alberth

引用次数: 0

Solving the Cross Domain Problem with Functional Encryption 用功能加密解决跨域问题

MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM) Pub Date : 2021-11-29 DOI: 10.1109/MILCOM52596.2021.9652958

A. Kaminsky, M. Kurdziel, Steven Farris, M. Lukowiak, S. Radziszowski

{"title":"Solving the Cross Domain Problem with Functional Encryption","authors":"A. Kaminsky, M. Kurdziel, Steven Farris, M. Lukowiak, S. Radziszowski","doi":"10.1109/MILCOM52596.2021.9652958","DOIUrl":"https://doi.org/10.1109/MILCOM52596.2021.9652958","url":null,"abstract":"A Cross Domain Problem (CDP) is the question of how to securely access and exchange information between the domains of varying security levels. A Cross Domain Solution (CDS) addresses the CDP by designing the framework and protocols for such access and transfers. Most existing CDS methods rely on policies and trusted parties to manage different security levels. A CDS that can function in the presence of untrusted parties is a challenge. Functional Encryption (FE) is an encryption scheme in which a secret key allows one to compute a specific function of plaintext from the ciphertext. FE is a generalization of identity-based and attribute-based encryption frameworks. General and simultaneously practical FE is an emerging area, and only special types of encryption schemes and functions are effectively handled within existing systems. We apply the concepts of FE to explore a new solution to the CDP, and we argue that our solution does not leak information, provided that widely accepted assumptions about standard digital signatures hold. We built a practical software case study application using a trusted Key Distribution Center (KDC), a standard symmetric key block cipher component (like the AES), and using the Elliptic Curve Digital Signature Algorithm (ECDSA). The experiments show that the computational overhead introduced to routing by our method is cost effective, where the additional cost is equivalent to just a few applications of standard digital signatures.","PeriodicalId":187645,"journal":{"name":"MILCOM 2021 - 2021 IEEE Military Communications Conference (MILCOM)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129167258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0