Week 7.3 Semantic Attacks - Spear Phishing
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Privacy and Security in Online Social Media. Course on NPTEL. Week 7.3: Semantic attacks: Spear Phishing.
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First, we focus on devising different methods to Identify, a.k.a. detect fake news online, by extracting different feature sets from the given information. By designing foundational detection mechanisms, our work accelerates research innovations. Second, our research closely Inspects the fake stories from two perspectives. First, from the information point of view, one can inspect fabricated content to identify the patterns of false reports disseminating over the web, the modality used to create the fabricated content and the platform used for dissemination. Next, from the model point of view, we inspect detection mechanisms used in prior work and their generalizability to other datasets. The thesis also suggests Intervention techniques to help internet users broaden their comprehension of fake news. We discuss potential practical implications for social media platform owners and policymakers.
#ChatGPT #ResponsibleAI
Prompt engineering, Fine tuning, Indian languages, Code Mixing, Hallucination, Responsible AI, Facts, Writing email, Writing code, Breaking rules, Bias with #ChatGPT
Data Science for Social Good: #MentalHealth #CodeMix #LegalNLP #AISafety
Discuss work on using technology for Judiciary, Lawyers, etc. Analyse social media data, music listening habits for mental health. Bias and Safety in AI Systems.
Papers are available at https://precog.iiit.ac.in/pages/publications.html
It is our choices, Harry, that show what we truly are, far more than our abil...
This document appears to be the transcript from a B.Tech orientation presentation given by Ponnurangam Kumaraguru at IIIT Hyderabad. The presentation provides advice and encouragement to new students on managing their time at IIIT Hyderabad. It emphasizes making friends, trying new activities and clubs, controlling wants and FOMO, celebrating failures, and using social media to connect with others in a positive way. References are made to movies to illustrate points about perseverance, finding passion, and having a growth mindset during the transition to university life.
Beyond the Surface: A Computational Exploration of Linguistic Ambiguity
We investigate two specific forms of linguistic ambiguities - polysemy, which is the multiplicity of meanings for a specific word, and tautology, which are seemingly uninformative and ambiguous phrases used in conversations. Both phenomena are widely-known manifestations of linguistic ambiguity at the lexical and pragmatic level, respectively.
The first part of the thesis focuses on addressing this challenge by proposing a new method for quantifying the degree of polysemy in words, which refers to the number of distinct meanings that a word can have. The proposed approach is a novel, unsupervised framework to compute and estimate polysemy scores for words in multiple languages, infusing syntactic knowledge in the form of dependency structures. The proposed framework is tested on curated datasets controlling for different sense distributions of words in three typologically diverse languages - English, French, and Spanish. The framework leverages contextual language models and syntactic structures to empirically support the widely held theoretical linguistic notion that syntax is intricately linked to ambiguity/polysemy.
The second part of the thesis explores how language models handle colloquial tautologies, a type of redundancy commonly used in conversational speech. We first present a dataset of colloquial tautologies and evaluate several state-of-the-art language models on this dataset using perplexity scores. We conduct probing experiments while controlling for the noun type, context and form of tautologies. The results reveal that BERT and GPT2 perform better with modal forms and human nouns, which aligns with previous literature and human intuition.
Data Science for Social Good: #LegalNLP #AlgorithmicBias...
Talk describes legal NLP idea discusses the following papers:
HLDC: Hindi Legal Documents Corpus https://precog.iiit.ac.in/pubs/HLDC_ACL_2022.pdf
Drug consumption: https://precog.iiit.ac.in/pubs/Effect_oF_Feedback_on_Drug_Consumption_Disclosures_on_Social_Media___ICWSM2023___16Sept1730hrs.pdf
How to Write a (Good) Research Paper
This document provides tips for writing a good research paper. It discusses selecting an appropriate topic and audience, developing an outline, writing drafts for feedback, choosing a descriptive title, writing a literature review, crafting an introduction, including figures and tables, addressing reviewer comments, avoiding plagiarism, and acknowledging collaborators. The goal is to write papers that clearly communicate research and can be improved based on feedback from others.
Data Science for Social Good: #LegalNLP #AlgorithmicBias
This document summarizes research on evaluating algorithmic bias in models trained on Hindi legal documents. The researchers collected a dataset of 900k legal documents from Uttar Pradesh courts in Hindi. They trained a bail prediction model on this data and evaluated it for demographic parity bias related to religious attributes. The results showed the model predictions changed more when replacing Hindu names with Muslim names compared to the reverse, indicating a potential bias against Muslims. Overall, the study highlights the need to evaluate models trained on real-world legal data for fairness to avoid perpetuating societal biases.
Social Computing Research in India
I discussed our work on #LegalAI #CodeMixing #FakeNews #Elections and other cool projects that we are currently working on at https://precog.iiit.ac.in/
Social Computing Research in India
The document discusses social computing research in India, focusing on legal AI and natural language processing applications. It summarizes work analyzing over 900,000 Hindi legal documents from district courts in Uttar Pradesh. Models were developed for tasks like bail prediction and legal document summarization. The research also addresses challenges in processing code-mixed text and fact-checking social media. Overall, the document outlines current research areas and opportunities in social computing for Indian contexts and languages, and provides contact information for those interested in the work.
Modeling Online User Interactions and their Offline effects on Socio-Technica...
Do online interactions trigger reactions back in the offline world? How can these reactions be detected and quantified? Specifically, what insights can be extracted for users, platform owners, and policymakers to minimize the potential harm of such reactions?
Society functions based on the complex interactions between individuals, communities, and organizations. The advent of the Internet has enabled these interactions to move online. A website or an application that facilitates the digitization of social interactions is called a socio-technical platform. For instance, individuals converse with each other via direct messaging applications (e.g., WhatsApp, Telegram), share thoughts, and gather feedback from communities (e.g., Reddit, Twitter, Youtube). Trade of goods occurs via e-commerce (e.g., Flipkart, Amazon) and online marketplaces (e.g., Google Play store). At times interactions happening in the online world, trigger reactions in the offline world, which we call overflow. Such overflows can have either a positive or negative impact. Socio-technical platforms save every interaction and associated metadata, providing a unique opportunity to analyze rich data at scale. Discover interaction patterns, detect and quantify overflow of interactions, and extract insights for users and policymakers.
This report aims to study the interactions by keeping the individual as the focal point. We focus on two broad forms of interactions - i) the effect online community feedback can have on individual offline actions and ii) organizations leveraging individual customers' online presence to optimize business processes. In the first part, we work on two scenarios - (a) How does community feedback affect an individual future drug consumption frequency in a drug community forum? and (b) What changes does an individual undergo immediately after getting sudden popularity in Online social media? What actions help in maintaining popularity for longer? In the second part, we leverage online information about a customer to improve the prediction of Return-to-Origin in the e-commerce platform.
Privacy. Winter School on “Topics in Digital Trust”. IIT Bombay
The document provides an overview of privacy concepts including definitions of privacy, forms of privacy, social media privacy, data anonymity, and ethics around studying privacy. It discusses Westin's four states of privacy (solitude, intimacy, anonymity, reserve) and Solove's taxonomy of privacy harms. It also covers Westin's privacy indexes, privacy studies conducted in India, OECD and FTC privacy principles, and the costs of reading privacy policies.
The document then discusses privacy enhancing technologies like communication anonymizers, shared bogus online accounts, obfuscation, and anonymization. Examples of privacy invasive technologies like spyware and RFID are also provided. Privacy decision making frameworks like Platform for Privacy Preferences (P3P)
It is our choices, Harry, that show what we truly are, far more than our abil...
The document provides advice and guidance for students transitioning to campus life from PK, a professor at IIIT Hyderabad. It includes quotes and links related to time management, pursuing interests, controlling wants and FOMO, exploring options before deciding on majors, aiming high while making consistent small progress, and asking for help when needed. The document acknowledges students who provided inputs and the knowledge gained from others to help with advising students.
It is our choices, Harry, that show what we truly are, far more than our abil...
The document is a transcript of a talk given by PK to B.Tech orientation students at IIIT Hyderabad. Some key points from the talk include:
- Encouraging students to make friends, participate in clubs and extracurricular activities.
- Emphasizing time management and not missing out on opportunities in the first two semesters.
- Advising students to explore different projects and areas before deciding on a focus or specialization.
- Noting that managing courses, social life, hobbies and more will be challenging but important during their time at IIIT.
Leveraging Social Media for Financial Advice
Talk covering our work on NFT https://cdn.iiit.ac.in/cdn/precog.iiit.ac.in/pubs/Finweb_WWW_2022.pdf and ESG. Connecting social media for Fintech.
Development of Stress Induction and Detection System to Study its Effect on B...
Stress has become a significant mental health problem of the 21st century. The number of people suffering from stress is increasing rapidly. Thus, easy-to-use, inexpensive, and accurate biomarkers are needed to detect stress during its inception. Early detection of stress-related diseases allows people to access healthcare services. This thesis focuses on the development of stress stimuli and the detection of stress induced by these stimuli. Identifying brain regions affected while exposing the subject to these stressful stimuli has also been done. Three different stimuli, viz. videos, gamified application, and a game, are investigated to study their effect as stress induction stimuli. To this end, in this thesis, a system is proposed to classify participants into stressed and non-stressed categories using machine learning, deep learning, and statistical techniques. The statistical significance between stressed and non-stressed was found using Higuchi Fractal Dimensions (HFD) feature extracted from EEG. This feature also helped identify the brain’s most affected region due to stress. Another outcome of this thesis is the extra annotation of the ground truth which further helps to validate the participant’s experience under the influence of stressful stimuli. This annotation was performed by evaluating participant performance under time pressure. In addition, a technique based on in-game analytics is presented to complement the betterment of self-reported data. Further, another dimension utilizing signatures from WiFi Media Access Control (MAC) layer traffic is presented to detect stress indicators in a device-agnostic way.
A Framework for Automatic Question Answering in Indian Languages
The distribution of research efforts done in the field of Natural Language
Processing (NLP) has not been uniform across all natural languages. It has
been observed that there is a significant gap between the development of
NLP tools in Indic languages (indic-NLP), and in European languages. We
aim to explore different directions to develop an automatic question answering system for Indic languages. We built a FAQ-retrieval based chatbot for
healthcare workers and young mothers of India. It supported Hindi language in either Devanagri script or Roman script. We observed that, in our
FAQ database, if there exists a question similar to the query asked by the
user, then the developed chatbot is able to find a relevant Question-Answer
pair (QnA) among its top-3 suggestions 70% of the time. We also observed
that performance of our chatbot is dependent on the diversity in the FAQ
database. Since database creation requires substantial manual efforts, we decided to explore other ways to curate knowledge from raw text irrespective
of domain.
We developed an Open Information Extraction (OIE) tool for Indic languages. During the preprocessing, chunking of text is performed with our
fine-tuned chunker, and the phrase-level dependency tree was constructed
using the predicted chunks. In order to generate triples, various rules were
handcrafted using the dependency relations in Indic languages. Our method
performed better than other multilingual OIE tools on manual and automatic evaluations. The contextual embeddings used in this work does not
take syntactic structure of sentence into consideration. Hence, we devised
an architecture that takes the dependency tree of the sentence into consideration to calculate Dependency-aware Transformer (DaT) embeddings.
Since the dependency tree is also a graph, we used Graph Convolution
Network (GCN) to incorporate the dependency information into the contextual embeddings, thus producing DaT embeddings. We used a hate-speech
detection task to evaluate the effectiveness of DaT embeddings. Our future
plan is to evaluate the applicability of DaT embeddings for the task of chunking. Moreover, the broader aim for the future is to develop an end-to-end
pronoun resolution model to improve the quality of triples and DaT embeddings. We also aim to explore the applicability of all our works to solve the
problem of long-context question answering.
More from IIIT Hyderabad (20)
Responsible & Safe AI Systems at ACM India ROCS at IIT Bombay
Responsible & Safe AI Systems at ACM India ROCS at IIT Bombay
International Collaboration: Experiences, Challenges, Success stories
International Collaboration: Experiences, Challenges, Success stories
Responsible & Safe AI: #LegalBias #Inconsistency #BiasinLLMs #MultiModalBias
Responsible & Safe AI: #LegalBias #Inconsistency #BiasinLLMs #MultiModalBias
Identify, Inspect and Intervene Multimodal Fake News
Identify, Inspect and Intervene Multimodal Fake News
Data Science for Social Good: #MentalHealth #CodeMix #LegalNLP #AISafety
Data Science for Social Good: #MentalHealth #CodeMix #LegalNLP #AISafety
It is our choices, Harry, that show what we truly are, far more than our abil...
It is our choices, Harry, that show what we truly are, far more than our abil...
Beyond the Surface: A Computational Exploration of Linguistic Ambiguity
Beyond the Surface: A Computational Exploration of Linguistic Ambiguity
Data Science for Social Good: #LegalNLP #AlgorithmicBias...
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Modeling Online User Interactions and their Offline effects on Socio-Technica...
Modeling Online User Interactions and their Offline effects on Socio-Technica...
Privacy. Winter School on “Topics in Digital Trust”. IIT Bombay
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It is our choices, Harry, that show what we truly are, far more than our abil...
It is our choices, Harry, that show what we truly are, far more than our abil...
It is our choices, Harry, that show what we truly are, far more than our abil...
It is our choices, Harry, that show what we truly are, far more than our abil...
Development of Stress Induction and Detection System to Study its Effect on B...
Development of Stress Induction and Detection System to Study its Effect on B...
A Framework for Automatic Question Answering in Indian Languages
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deductive approach to theory development and a survey research strategy. Findings reveal that work stress
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留信认证全称全国留学生信息服务网认证,隶属于北京中科院。①留信认证门槛条件更低,费用更美丽,并且包过,完单周期短,效率高②留信认证虽然不能去国企,但是一般的公司都没有问题,因为国内很多公司连基本的留学生学历认证都不了解。这对于留学生来说,这就比自己光拿一个证书更有说服力,因为留学学历可以在留信网站上进行查询!
B.为什么我们提供的毕业证成绩单具有使用价值？
查询留服认证是国内鉴别留学生海外学历的唯一途径但认证只是个体行为不是所有留学生都操作所以没有办理认证的留学生的学历在国内也是查询不到的他们也仅仅只有一张文凭。所以这时候我们提供的和学校颁发的一模一样的毕业证成绩单就有了使用价值。却也灵机一动立马仰起头双手拢在嘴边朝楼上大喊：“爸爸爸——有人找——那人一听朝山娃尴尬地笑笑悻悻地走了山娃立马“嘭的一声将铁门锁死心却咚咚地乱跳当山娃跟父亲说起这事时父亲很吃惊抚摸着山娃的头说还好醒得及时要不家早被人掏空了到时连电视也没得看啰不过父亲还是夸山娃能临危不乱随机应变有胆有谋山娃笑笑说那都是书上学的看童话和小说时学的不管如何父亲再也不许山娃敞开门坐到门口了父亲递给山娃钥匙说一出门就将门山
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HMS Facebook Stories All V1 06092024.docx
The conversations on Facebook from the Herringswell Manor School group from 2009 to the first half of 2024
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学校原件一模一样【微信：741003700 】《(worcester毕业证书)伍斯特大学毕业证PDF成绩单》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
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四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
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◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
Factors affecting undergraduate students’ motivation at a university in Tra Vinh
ABSTRACT: Motivation plays an important role in foreign language learning process. This study aimed to
investigate student’s motivation patterns towards English language learning at a University in Tra Vinh, and factors
affecting their motivation change toward English language learning of non-English-major students in the semester.
The researcher used semi-structured interview at the first phase of choosing the participants and writing reflection
through the instrument called “My English Learning Motivation History” adapted from Sawyer (2007) to collect
qualitative data within 15 weeks. The participants consisted of nine first year non-English-major students who learning
General English at pre-intermediate level. They were chosen and divided into three groups of three members each
(high motivation group; average motivation group; and low motivation group). The results of the present study
identified six visual motivation patterns of three groups of students with different motivation fluctuation, through the
use of cluster analysis. The study also indicated a diversity of factors affecting students’ motivation involving internal
factors as influencing factors (cognitive, psychology, and emotion) and external factors as social factors (instructor,
peers, family, and learning environment) during English language learning in a period of 15 weeks. The findings of
the study helped teacher understand relationship of motivation change and its influential factors. Furthermore, the
findings also inspired next research about motivation development in learning English process.
KEY WORDS: language learning motivation, motivation change, motivation patterns, influential factors, students’
motivation.
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Week 7.3 Semantic Attacks - Spear Phishing
- 3. Security attacks Physical Semantic Syntactic Phishing Mules Nigerian Verification Security alertUpdate info PaypalAmazon eBay BOA Mortgage Semantic attacks
- 4. Subject: eBay: Urgent Notification From Billing Department Features in the email
- 5. Features in the email We regret to inform you that you eBay account could be suspended if you don’t update your account information.
- 6. https://signin.ebay.com/ws/eBayISAPI.dll?SignIn&sid=verify&co_partnerid=2&sidteid=0 Features in the email
- 7. Website to collect information http://www.kusi.org/hcr/eBay/ws23/eBayISAPI.htm
- 9. Types of Phishing Attacks ⚫Phishing ⚫Context-aware phishing / spear phishing ⚫Whaling ⚫Vishing ⚫Smsishing ⚫Social Phishing? 37
- 10. Until now, work that we have seen? ⚫Using voters database ⚫Using Medical health database ⚫Using Pictures from FB 38
- 11. Goal ⚫To see how phishing attacks can be performed by collecting personal information from social networks -How easily or effectively can phisher use this information? 39
- 12. 40
- 13. Methodology ⚫Collected publicly available personal information using simple tools like Perl LWP library ⚫Correlated this data with IU’s address book database ⚫Launched in April 2005 ⚫Age between 18 – 24 41
- 14. 42
- 15. Control Vs. Experiment ⚫Control: The email from IU email ID, but, from an unknown person ⚫Experiment: From a friend in IU 43
- 16. Methodology ⚫ Blogging, social network, and other public data is harvested ⚫ Data is correlated and stored in a relational database ⚫ Heuristics are used to craft spoofed email message by Eve “as Alice” to Bob (a friend) ⚫ Message is sent to Bob ⚫ Bob follows the link contained within the email message and is sent to an unchecked redirect ⚫ Bob is sent to attacker whuffo.com site ⚫ Bob is prompted for his University credentials ⚫ Bob’s credentials are verified with the University authenticator ⚫ a. Bob is successfully phished b. Bob is not phished in this session; he could try again. 44
- 17. Victims ⚫Control group high – sender email ID was IU ⚫Experimental condition consistent with other studies 45
- 18. Success rate 46 ⚫70% authentications in first 12 hrs ⚫Takedown has to be successful
- 19. Repeated authentications 47 ⚫ Subject tried multiple times ⚫ Tried again because “overload” message was shown ⚫ Lower bound of users to fall, continued to be deceived ⚫ Some tried 80 times
- 20. Gender 48 ⚫18,294 Ms and 19,527 Fs ⚫Overall F more victims ⚫More successful if it came from opposite gender ⚫F to M (13%) was more effect than M to F (2%)
- 21. 49 ⚫Younger targets more vulnerable
- 22. 50 ⚫All majors significant difference between control and experimental ⚫Max difference in Science ⚫Technology lowest #satisfying ☺
- 23. Reactions ⚫Anger -Unethical, inappropriate, illegal, fraudulent -Researchers fired -Psychological cost ⚫Denial -Nobody accepted that they fell for it -Admitting our vulnerability is hard ⚫Misunderstanding over spoofing emails ⚫Underestimation of publicly available information 51
- 24. Conclusions ⚫Extensive educational campaigns ⚫Browser solutions ⚫Digitally signed emails ⚫OSM provides lot more information for making the attack successful 52