检索结果-内蒙古大学图书馆

Advanced Persistent Threats (APT): evolution, anatomy, attribution and countermeasures

Journal of Ambient Intelligence and Humanized computing 2023年第7期14卷 9355-9381页

作者： Sharma, Amit Gupta, Brij B. Singh, Awadhesh Kumar Saraswat, V.K. Department of Computer Engineering National Institute of Technology Kurukshetra Kurukshetra136119 India International Center for AI and Cyber Security Research and Innovations Department of Computer Science and Information Engineering Asia University Taichung Taiwan NITI Aayog New Delhi110001 India Lebanese American University Beirut Lebanon School of Computing Skyline University College Sharjah United Arab Emirates Department of Computer Engineering National Institute of Technology Kurukshetra Kurukshetra India Birkbeck University of London London United Kingdom

In today’s cyber warfare realm, every stakeholder in cyberspace is becoming more potent by developing advanced cyber weapons. They have equipped with the most advanced malware and maintain a hidden attribution. The precocious cyber weapons, targeted and motivated with some specific intention are called as Advanced Persistent Threats (APT). Developing defense mechanisms and performing attribution analysis of such advanced attacks are extremely difficult due to the intricate design of attack vector and sophisticated malware employed with high stealth and evasive techniques. These attacks also include advanced zero-day and negative-day exploits and payloads. This paper provides a comprehensive survey on the evolution of advanced malware design paradigms, APT attack vector and its anatomy, APT attack Tactics, Techniques, and Procedures (TTP) and specific case studies on open-ended APT attacks. The survey covers a detailed discussion on APT attack phases and comparative study on threat life-cycle specification by various organizations. This work also addresses the APT attack attribution and countermeasures against these attacks from classical signature and heuristic based detection to modern machine learning and genetics based detection mechanisms along with sophisticated zero-day and negative day malware countermeasure by various techniques like monitoring of network traffic and DNS logs, moving target based defense, and attack graph based defenses. Furthermore, the survey addresses various research scopes in the domain of APT cyber-attacks. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Life cycle

来源：评论

学校读者我要写书评

暂无评论

SOCA-DOM:A Mobile System-on-Chip Array System for Analyzing Big Data on the Move

引用

Journal of computer science & Technology 2022年第6期37卷 1271-1289页

作者： Le-Le Li Jiang-Yi Liu Jian-Ping Fan Xue-Hai Qian Kai Hwang Yeh-Ching Chung Zhi-Bin Yu Center for Heterogeneous and Intelligent Computing Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesShenzhen 518055China School of Science and Engineering The Chinese University of Hong KongShenzhenShenzhen 518172China Center for High Performance Computing Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences Shenzhen 518055China Ming Hsieh Department of Electrical and Computer Engineering University of Southern CaliforniaLos Angeles CA 90089-0001U.S.A. Department of Computer Science University of Southern CaliforniaLos AngelesCA 90089-0001U.S.A. School of Data and Science The Chinese University of Hong KongShenzhenShenzhen 518172China

Recently,analyzing big data on the move is *** requires that the hardware resource should be low volume,low power,light in weight,high-performance,and highly scalable whereas the management software should be flexible and consume little hardware *** meet these requirements,we present a system named SOCA-DOM that encompasses a mobile system-on-chip array architecture and a two-tier“software-defined”resource manager named ***,we design an Ethernet communication board to support an array of mobile ***,we propose a two-tier software architecture for Chameleon to make it ***,we devise data,configuration,and control planes for Chameleon to make it“software-defined”and in turn consume hardware resources on ***,we design an accurate synthetic metric that represents the computational power of a computing *** employ 12 Apache Spark benchmarks to evaluate ***,SOCA-DOM consumes up to 9.4x less CPU resources and 13.5x less memory than Mesos which is an existing resource *** addition,we show that a 16-node SOCA-DOM consumes up to 4x less energy than two standard Xeon *** on the results,we conclude that an array architecture with fine-grained hardware resources and a software-defined resource manager works well for analyzing big data on the move.

关键词： edge computing mobile architecture resource management big data analytics software-defined systems

来源：评论

学校读者我要写书评

暂无评论

Computational Modelling of Plurality and Definiteness in Chinese Noun Phrases 30

Computational Modelling of Plurality and Definiteness in Chi...

引用

Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Liu, Yuqi Chen, Guanyi van Deemter, Kees Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning National Language Resources Monitoring and Research Center for Network Media School of Computer Science Central China Normal University China Department of Information and Computing Sciences Utrecht University Netherlands

ISBN: (纸本)9782493814104

Theoretical linguists have suggested that some languages (e.g., Chinese and Japanese) are "cooler" than other languages based on the observation that the intended meaning of phrases in these languages depends more on their contexts. As a result, many expressions in these languages are shortened, and their meaning is inferred from the context. In this paper, we focus on the omission of the plurality and definiteness markers in Chinese noun phrases (NPs) to investigate the predictability of their intended meaning given the contexts. To this end, we built a corpus of Chinese NPs, each of which is accompanied by its corresponding context, and by labels indicating its singularity/plurality and definiteness/indefiniteness. We carried out corpus assessments and analyses. The results suggest that Chinese speakers indeed drop plurality and definiteness markers very frequently. Building on the corpus, we train a bank of computational models using both classic machine learning models and state-of-the-art pre-trained language models to predict the plurality and definiteness of each NP. We report on the performance of these models and analyse their behaviours. The code and data used in this paper are available at: https://***/andyzxq/chinese_np_def. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems

引用

Journal of Bionic Engineering 2023年第3期20卷 1263-1295页

作者： Jeffrey O.Agushaka Absalom E.Ezugwu Oyelade N.Olaide Olatunji Akinola Raed Abu Zitar Laith Abualigah School of Mathematics Statisticsand Computer ScienceUniversity of KwaZulu-NatalKing Edward AvenuePietermaritzburg CampusPietermaritzburg3201KwaZulu-NatalSouth Africa Department of Computer Science Federal University of LafiaLafia950101Nigeria Unit for Data Science and Computing North-West University11 Hoffman StreetPotchefstroom2520South Africa Sorbonne Center of Artificial Intelligence Sorbonne University-Abu Dhabi38044Abu DhabiUnited Arab Emirates Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan Faculty of Information Technology Middle East UniversityAmman11831Jordan Faculty of Information Technology Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains Malaysia11800Pulau PinangMalaysia

This paper proposes a modified version of the Dwarf Mongoose Optimization Algorithm (IDMO) for constrained engineering design problems. This optimization technique modifies the base algorithm (DMO) in three simple but effective ways. First, the alpha selection in IDMO differs from the DMO, where evaluating the probability value of each fitness is just a computational overhead and contributes nothing to the quality of the alpha or other group members. The fittest dwarf mongoose is selected as the alpha, and a new operator ω is introduced, which controls the alpha movement, thereby enhancing the exploration ability and exploitability of the IDMO. Second, the scout group movements are modified by randomization to introduce diversity in the search process and explore unvisited areas. Finally, the babysitter's exchange criterium is modified such that once the criterium is met, the babysitters that are exchanged interact with the dwarf mongoose exchanging them to gain information about food sources and sleeping mounds, which could result in better-fitted mongooses instead of initializing them afresh as done in DMO, then the counter is reset to zero. The proposed IDMO was used to solve the classical and CEC 2020 benchmark functions and 12 continuous/discrete engineering optimization problems. The performance of the IDMO, using different performance metrics and statistical analysis, is compared with the DMO and eight other existing algorithms. In most cases, the results show that solutions achieved by the IDMO are better than those obtained by the existing algorithms.

关键词： Improved dwarf mongoose Nature-inspired algorithms Constrained optimization Unconstrained optimization Engineering design problems

来源：评论

学校读者我要写书评

暂无评论

Dynamic Graph Neural Networks-Based Alert Link Prediction for Online Service Systems 23

Dynamic Graph Neural Networks-Based Alert Link Prediction fo...

引用

Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering

作者： Yiru Chen Chenxi Zhang Zhen Dong Dingyu Yang Xin Peng Jiayu Ou Hong Yang Zheshun Wu Xiaojun Qu Wei Li School of Computer Science Fudan University China and Shanghai Key Laboratory of Data Science Fudan University China and Shanghai Collaborative Innovation Center of Intelligent Visual Computing China Alibaba Group China

ISBN: (纸本)9798350329964

A fault in large online service systems often triggers numerous alerts due to the complex business and component dependencies among services, which is known as "alert storm". In a short time, an online service system may generate a huge amount of alert data. This poses a challenge for on-call engineers to identify alerts that are associated with a system failure for root cause analysis. In this paper, we propose DyAlert, a dynamic graph neural networks-based approach for linking alerts that might be triggered by a same fault to reduce the burden of on-call engineers in the fault analysis. Our insight is that alerts are often triggered by alert propagation when a system failure occurs, e.g., alert a would lead to the occurrence of alert b. Whether two alerts should be linked depends on if one alert is triggered by the propagation of the other. Leveraging this insight, we design a dynamic graph (namely Alert-Metric Dynamic Graph) that describes the propagation process of alerts. Based on the dynamic graph, we train a neural networks-based model to predict alert links. We evaluate DyAlert with real-world data collected from an online service system running 85 business units and about 30,000 different services in a large enterprise. The results show that DyAlert is effective in predicting alert links and it outperforms the state-of-the-art approaches with an average increase of 0.259 in F1-score.

关键词： linked alerts

来源：评论

学校读者我要写书评

暂无评论

Fitweet: Arduino-Based Smartwatch for Early Anticipatory Anxiety Notification System 9th

Fitweet: Arduino-Based Smartwatch for Early Anticipatory Anx...

引用

9th International Conference on Computational science and Technology, ICCST 2022

作者： Abdulmanab, Muhammad Rahiman Nor’Azman, Nur Faidz Hazirah Meon, Hasni Razak, Chempaka Seri Abdul Ab Hamid, Siti Hafizah Department of Software Engineering Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur Malaysia Department of Communication Faculty of Communication Visual Art and Computing Universiti Selangor Bestari Jaya Malaysia School of Pre-University Studies Taylor’s College Lakeside Campus Subang Jaya Malaysia

ISBN: (纸本)9789811984051

As anxiety becomes increasingly prevalent among youths especially university students, early prevention via anxiety disorder profiling is crucial. Nevertheless, most screening tools to date are not automated, labour-intensive and time-consuming. Mental health detection in online social networks (OSNs) using artificial intelligence (AI) can provide means for capturing overlooked behavioural attributes, but few are centred around anxiety detection. Internet of Things (IoT)’s increasing popularity enables bio-signals monitoring to aid in mental health care. However, minimum research has been devoted to IoT-based assistive technologies for anxiety, which currently are only used by individuals already diagnosed and actively monitored. This study proposes a novel approach to anticipatory anxiety detection for Malaysian university students aged between 18 and 25 inclusive as an early notification system using AI and IoT for bilingual Malay and English tweets and vital signs analysis respectively. Our result shows that Logistic Regression with Bag-of-Words (BoW) is the overall best performing model with 81.06% accuracy. The Arduino smartwatch sensor readings from the MAX30102 pulse oximeter sensor are used to determine different body conditions using a rule-based approach. The comparison test result between the prototype and conventional measuring devices shows the prototype’s ability to accurately distinguish vital signs with a relatively low Mean Absolute Percent Error (MAPE) rate of 10.92% and 1.51% for pulse rate and temperature respectively. Together, our proof-of-concept results indicate the potential of AI and IoT in deriving new measures of anxiety, by analysing social data combined with bio-signals monitoring to alert users regarding their anxiety state. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

PipeEdge: A Trusted Pipelining Collaborative Edge Training based on Blockchain 23

PipeEdge: A Trusted Pipelining Collaborative Edge Training b...

引用

32nd ACM World Wide Web Conference, WWW 2023

作者： Yuan, Liang He, Qiang Chen, Feifei Dou, Ruihan Jin, Hai Yang, Yun School of Computer Science and Technology Huazhong University of Science and Technology China Department of Computing Technologies Swinburne University of Technology Australia School of Information Technology Deakin University Australia Faculty of Mathematics University of Waterloo Canada National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781450394161

Powered by the massive data generated by the blossom of mobile and Web-of-Things (WoT) devices, Deep Neural Networks (DNNs) have developed both in accuracy and size in recent years. Conventional cloud-based DNN training incurs rapidly-increasing data and model transmission overheads as well as privacy issues. Mobile edge computing (MEC) provides a promising solution by facilitating DNN model training on edge servers at the network edge. However, edge servers often suffer from constrained resources and need to collaborate on DNN training. Unfortunately, managed by different telecoms, edge servers cannot properly collaborate with each other without incentives and trust. In this paper, we introduce PipeEdge, a scheme that promotes collaborative edge training between edge servers by introducing incentives and trust based on blockchain. Under the PipeEdge scheme, edge servers can hire trustworthy workers for pipelined DNN training tasks based on model parallelism. We implement PipeEdge and evaluate it comprehensively with four different DNN models. The results show that it outperforms state-of-the-art schemes by up to 173.98% with negligible overheads. © 2023 ACM.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Exploring Gaze Dynamics: Initial Findings on the Role of Listening Bystanders in Conversational Interactions

Exploring Gaze Dynamics: Initial Findings on the Role of Lis...

引用

Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Jonathan Ehret Valentin Dasbach Jan-Nikjas Hartmann Janina Fels Torsten W. Kuhlen Andrea Bönsch Visual Computing Institute RWTH Aachen University Germany Department of Computer Science RWTH Aachen University Germany Institute for Hearing Technology and Acoustics RWTH Aachen University Germany

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

This work-in-progress paper investigates how virtual listening bystanders influence participants’ gaze behavior and their perception of turn-taking during scripted conversations with embodied conversational agents (ECAs). 25 participants interacted with five ECAs – two speakers and three bystanders – across three conditions: no bystanders, bystanders exhibiting random gazing behavior, and social bystanders engaging in mutual gaze and backchanneling. Participants either observed the conversation or actively participated as speakers by reciting prompted *** results indicated that bystanders reduced the participants’ attention to speakers, hindering their ability to anticipate turn changes and resulting in longer delays in shifting their gaze to the new speaker after an ECA yielded the turn. Random gazing bystanders were particularly noted for obscuring conversational flow. These findings underscore the challenges of designing effective and natural conversational environments, highlighting the need for careful consideration of ECA behaviors to enhance user engagement.

关键词： visualization Three-dimensional displays Social groups Conferences Oral communication Virtual reality Gaze tracking User interfaces Delays Complexity theory

来源：评论

学校读者我要写书评

暂无评论

A Case-Based-Reasoning Analysis of the COMPAS Dataset 37

A Case-Based-Reasoning Analysis of the COMPAS Dataset

引用

37th Annual Conference on Legal Knowledge and Information Systems, JURIX 2024

作者： van Woerkom, Wijnand Grossi, Davide Prakken, Henry Verheij, Bart Department of Information and Computing Sciences Utrecht University Netherlands Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Netherlands Amsterdam Center for Law and Economics University of Amsterdam Netherlands Institute for Logic Language and Computation University of Amsterdam Netherlands

ISBN: (纸本)9781643685625

In this paper we build on a formal model of reasoning with dimensions to analyze data from the COMPAS program—a widely used and studied tool for predicting recidivism. We extend the underlying theory of the model by introducing a notion of consistency and apply it to assess whether COMPAS follows this principle in its risk assessments and supervision level recommendations. Our analysis yields three key findings. First, the program’s risk score assignments appear highly inconsistent, but we argue this is due to important input features missing from the dataset. Second, the program’s recommended supervision levels do exhibit a high degree of consistency. Third, we uncover errors in the dataset related to the conversion of raw scores to decile scores. These findings cast doubts on previous studies conducted on the COMPAS dataset, and demonstrate the need for evaluation studies like ours. © 2024 The Authors.

关键词： case-based reasoning COMPAS dataset consistency analysis explainable artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Downstream Task-agnostic Transferable Attacks on Language-Image Pre-training Models

Downstream Task-agnostic Transferable Attacks on Language-Im...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Yiqiang Lv Jingjing Chen Zhipeng Wei Kai Chen Zuxuan Wu Yu-Gang Jiang Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University Shanghai Collaborative Innovation Center of Intelligent Visual Computing

Vision-language pre-trained models (e.g., CLIP) trained on large-scale datasets via self-supervised learning, are drawing increasing research attention since they can achieve superior performances on multi-modal downstream tasks. Nevertheless, we find that the adversarial perturbations crafted on vision-language pre-trained models can be used to attack different corresponding downstream task models. Specifically, to investigate such adversarial transferability, we introduce a task-agnostic method named Global and Local Augmentation (GLA) attack to generate highly transferable adversarial examples on CLIP, to attack black-box downstream task models. GLA adopts random crop and resize at both global and local patch levels, to create more diversity and make adversarial noises robust. Then GLA generates the adversarial perturbations by minimizing the cosine similarity between intermediate features from augmented adversarial and benign examples. Extensive experiments on three CLIP image encoders with different backbones and three different downstream tasks demonstrate the superiority of our method compared with other strong baselines. The code is available at https://***/yqlvcoding/GLAattack.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：