Balancing schoolwork with gaming usually means finding a laptop that can do a little bit of everything. The best gaming laptops aren’t just built for high frame rates. They also need to handle long days of writing papers, running productivity apps and streaming lectures without slowing down. A good machine should feel reliable during class and powerful enough to jump into your favorite games once homework is out of the way.

There’s a wide range of options depending on how much performance you need. Some students prefer a slim, lightweight model that’s easy to carry to school, while others want a new gaming laptop with enough GPU power to handle AAA titles. If you’re watching your budget, there are plenty of solid choices that qualify as a budget gaming laptop without cutting too many corners.

It’s also worth looking at features that help with everyday use. A bright display makes long study sessions easier on the eyes, and a comfortable keyboard is essential if you type a lot. USB-C ports, decent battery life and a responsive trackpad can make a big difference during the school day. We’ve rounded up the best laptops that strike the right mix of performance, portability and value for both gaming and schoolwork.

Table of contents

• Best laptops for gaming and school in 2025

• Best laptop for gaming and schoolwork FAQs

Best laptops for gaming and school in 2025

Best laptop for gaming and schoolwork FAQs

Are gaming laptops good for school?

As we’ve mentioned, gaming laptops are especially helpful if you're doing any demanding work. Their big promise is powerful graphics performance, which isn't just limited to PC gaming. Video editing and 3D rendering programs can also tap into their GPUs to handle laborious tasks. While you can find decent GPUs on some productivity machines, like Dell's XPS 15, you can sometimes find better deals on gaming laptops. My general advice for any new workhorse: Pay attention to the specs; get at least 16GB of RAM and the largest solid state drive you can find (ideally 1TB or more). Those components are both typically hard to upgrade down the line, so it’s worth investing what you can up front to get the most out of your PC gaming experience long term. Also, don’t forget the basics like a webcam, which will likely be necessary for the schoolwork portion of your activities.

The one big downside to choosing a gaming notebook is portability. For the most part, we'd recommend 15-inch models to get the best balance of size and price. Those typically weigh in around 4.5 pounds, which is significantly more than a three-pound ultraportable. Today's gaming notebooks are still far lighter than older models, though, so at least you won't be lugging around a 10-pound brick. If you’re looking for something lighter, there are plenty of 14-inch options these days. And if you're not into LED lights and other gamer-centric bling, keep an eye out for more understated models that still feature essentials like a webcam (or make sure you know how to turn those lights off).

Do gaming laptops last longer than standard laptops?

Not necessarily — it really depends on how you define "last longer." In terms of raw performance, gaming laptops tend to pack more powerful components than standard laptops, which means they can stay relevant for longer when it comes to handling demanding software or modern games. That makes them a solid choice if you need a system that won’t feel outdated in a couple of years, especially for students or creators who also game in their downtime.

But there’s a trade-off. All that power generates heat, and gaming laptops often run hotter and put more strain on internal components than typical ultraportables. If they’re not properly cooled or regularly maintained (think dust buildup and thermal paste), that wear and tear can shorten their lifespan. They’re also usually bulkier and have shorter battery life, which can impact long-term usability depending on your daily needs.

Gaming laptops can last longer performance-wise, but only if you take good care of them. If your needs are light — browsing, writing papers and streaming — a standard laptop may actually last longer simply because it’s under less stress day-to-day.

What is the role of GPU in a computer for gaming and school?

The GPU plays a big role in how your laptop handles visuals — and it’s especially important if you’re using your computer for both gaming and school.

For gaming, the GPU is essential. It’s responsible for rendering graphics, textures, lighting and all the visual effects that make your favorite titles look smooth and realistic. A more powerful GPU means better frame rates, higher resolutions and the ability to play modern games without lag or stuttering.

For schoolwork, the GPU matters too — but its importance depends on what you're doing. If your school tasks mostly involve writing papers, browsing the web or using productivity tools like Google Docs or Microsoft Office, you don’t need a high-end GPU. But if you’re working with graphic design, video editing, 3D modeling or anything else that’s visually demanding, a good GPU can speed things up significantly and improve your workflow.

Georgie Peru contributed to this report.

The Office of Personnel Management is trying to address what it says are concerns from some managers and supervisors who worry they may be held personally liable for disciplining federal employees deemed poor performers.

In response to those concerns, a Nov. 21 memo from OPM clarified that managers and supervisors are generally acting on behalf of an agency when they “manage employees’ job performance and address unacceptable performance.” There is an “extremely limited scope” where managers or supervisors would be held individually responsible for those actions, OPM said.

When a manager puts an employee on a performance improvement plan, demotes an employee or removes an employee from their job for poor performance, that’s technically considered the action of the agency, OPM said, and not the individual manager’s responsibility. If an employee challenges one of those actions, OPM said that the agency, not the manager, would be responsible for responding.

“In the unusual event that a manager or supervisor is sued personally for actions within the scope of their employment, the Department of Justice (DOJ) typically provides representation,” the memo reads.

But if a supervisor or manager misuses their authority — for example through discrimination, harassment or whistleblower-related prohibited personnel practices — OPM said the individual can then be held personally accountable for their actions.

In its memo, OPM also reminded supervisors and managers of the availability of professional liability insurance, which may help protect them in the rare cases where they may be held liable. Supervisors and managers are usually eligible for a government reimbursement amounting to up to half the cost of the insurance.

“But even in these situations Congress did not give employees the right to hold their managers or supervisors personally liable for any performance or conduct-related adverse action,” OPM said.

OPM’s clarification comes after the Trump administration earlier this year set new expectations for measuring federal employees’ job performance. In June, OPM told agencies they don’t have to use “progressive discipline” and that they should not substitute a suspension when a full removal of an employee from their job “would be appropriate.”

The administration’s new performance management standards also attempt to more strictly delineate between different levels of employee performance and encourage agencies to rate fewer employees as high performers.

OPM Director Scott Kupor has repeatedly argued that the government has inflated performance ratings, and has targeted the rating system as a key area for OPM to update.

“In the real world we are not all equally successful and differences in performance from one person to the next are in fact real,” Kupor wrote in a Sept. 15 blog post. “We simply can’t all get A’s because not everyone’s contributions to the success of the organization are the same. Some people simply perform better than others — whether by luck or skill.”

More recently, OPM also announced a new mandatory training program for all federal supervisors, intended to educate supervisors on how to better manage performance of federal employees. The one-hour online course will cover topics including recognition, awards, hiring, firing and discipline of federal employees, according to a memo OPM sent to agencies Wednesday.

“At the end of the training, supervisors will be ready to set clear expectations, deliver quality feedback, document fairly, reward excellence, and take timely action when needed—all while building an engaged, high-performing team through transparency, accountability, and collaboration,” the memo stated.

Federal supervisors are required to complete the training by Feb. 9, 2026, OPM said.

The required supervisor training comes shortly after OPM also launched two optional training programs, designed to educate senior executives in the federal workforce, while incorporating common themes from the Trump administration on “accountability,” performance management and adherence to the president’s priorities.

The post OPM attempts to ease manager concerns in addressing federal employees’ performance first appeared on Federal News Network.

If you have a white elephant gift exchange at work this year or with friends and family, there’s a good chance you’re scrambling right now to find a good gift — or decipher what even makes a good white elephant gift. The possible origins of the term “white elephant” provide one way of looking at it: According to legend, the King of Siam would give a white elephant to courtiers who had upset them. It was a far more devious punishment than simply having them executed. The recipient had no choice but to simply thank the king for such an opulent gift, knowing that they likely could not afford the upkeep for such an animal. It would inevitably lead them to financial ruin.

Whether or not that story is true, it gives us one way of looking at a white elephant gift: something just useful or amusing enough that it won’t immediately get tossed into the trash, but is also somewhat of a burden. However, there are plenty of other ways of interpreting this strange yet delightful tradition. Some compete to get a gift that others will surely want to steal, while others scavenge for the most niche and targeted gag gifts. Almost all of them, though, typically have a price limit that keeps the burden of gift giving to a minimum — usually $50 or less. So with all of that in mind, here are some white elephant gift ideas that will get you a few chuckles without requiring you to spend too much (or think too hard about it).

Best white elephant gift ideas

White elephant FAQs

What is white elephant?

A white elephant gift exchange is a party game typically played around the holidays in which people exchange funny, impractical gifts.

How does white elephant work?

A group of people each bring one wrapped gift to the white elephant gift exchange, and each gift is typically of a similar value. All gifts are then placed together and the group decides the order in which they will each claim a gift. The first person picks a white elephant gift from the pile, unwraps it and their turn ends. The following players can either decide to unwrap another gift and claim it as their own, or steal a gift from someone who has already taken a turn. The rules can vary from there, including the guidelines around how often a single item can be stolen — some say twice, max. The game ends when every person has a white elephant gift.

Why is it called white elephant?

The term “white elephant” is said to come from the legend of the King of Siam gifting white elephants to courtiers who upset him. While it seems like a lavish gift on its face, the belief is that the courtiers would be ruined by the animal’s upkeep costs.

Check out the rest of our gift ideas here.

Read more of this story at Slashdot.

Read more of this story at Slashdot.

Read more of this story at Slashdot.

Read more of this story at Slashdot.

Session 4B: Audio Security

Authors, Creators & Presenters:

PAPER
VoiceRadar: Voice Deepfake Detection using Micro-Frequency And Compositional Analysis
Recent advancements in synthetic speech generation, including text-to-speech (TTS) and voice conversion (VC) models, allow the generation of convincing synthetic voices, often referred to as audio deepfakes. These deepfakes pose a growing threat as adversaries can use them to impersonate individuals, particularly prominent figures, on social media or bypass voice authentication systems, thus having a broad societal impact. The inability of state-of-the-art verification systems to detect voice deepfakes effectively is alarming. We propose a novel audio deepfake detection method, VoiceRadar, that augments machine learning with physical models to approximate frequency dynamics and oscillations in audio samples. This significantly enhances detection capabilities. VoiceRadar leverages two main physical models: (i) the Doppler effect to understand frequency changes in audio samples and (ii) drumhead vibrations to decompose complex audio signals into component frequencies. VoiceRadar identifies subtle variations, or micro-frequencies, in the audio signals by applying these models. These micro-frequencies are aggregated to compute the observed frequency, capturing the unique signature of the audio. This observed frequency is integrated into the machine learning algorithm's loss function, enabling the algorithm to recognize distinct patterns that differentiate human-produced audio from AI-generated audio. We constructed a new diverse dataset to comprehensively evaluate VoiceRadar, featuring samples from leading TTS and VC models. Our results demonstrate that VoiceRadar outperforms existing methods in accurately identifying AI-generated audio samples, showcasing its potential as a robust tool for audio deepfake detection.

ABOUT NDSS
The Network and Distributed System Security Symposium (NDSS) fosters information exchange among researchers and practitioners of network and distributed system security. The target audience includes those interested in practical aspects of network and distributed system security, with a focus on actual system design and implementation. A major goal is to encourage and enable the Internet community to apply, deploy, and advance the state of available security technologies.

Our thanks to the Network and Distributed System Security (NDSS) Symposium for publishing their Creators, Authors and Presenter’s superb NDSS Symposium 2025 Conference content on the Organizations' YouTube Channel.

Permalink

The post NDSS 2025 – VoiceRadar: Voice Deepfake Detection Using Micro-Frequency And Compositional Analysis appeared first on Security Boulevard.

Session4A: IoT Security

Authors, Creators & Presenters: Eman Maali (Imperial College London), Omar Alrawi (Georgia Institute of Technology), Julie McCann (Imperial College London)

PAPER
Evaluating Machine Learning-Based IoT Device Identification Models for Security Applications

With the proliferation of IoT devices, network device identification is essential for effective network management and security. Many exhibit performance degradation despite the potential of machine learning-based IoT device identification solutions. Degradation arises from the assumption of static IoT environments that do not account for the diversity of real-world IoT networks, as devices operate in various modes and evolve over time. In this paper, we evaluate current IoT device identification solutions using curated datasets and representative features across different settings. We consider key factors that affect real-world device identification, including modes of operation, spatio-temporal variations, and traffic sampling, and organise them into a set of attributes by which we can evaluate current solutions. We then use machine learning explainability techniques to pinpoint the key causes of performance degradation. This evaluation uncovers empirical evidence of what continuously identifies devices, provides valuable insights, and practical recommendations for network operators to improve their IoT device identification in operational deployments

ABOUT NDSS
The Network and Distributed System Security Symposium (NDSS) fosters information exchange among researchers and practitioners of network and distributed system security. The target audience includes those interested in practical aspects of network and distributed system security, with a focus on actual system design and implementation. A major goal is to encourage and enable the Internet community to apply, deploy, and advance the state of available security technologies.

Our thanks to the Network and Distributed System Security (NDSS) Symposium for publishing their Creators, Authors and Presenter’s superb NDSS Symposium 2025 Conference content on the Organizations' YouTube Channel.

Permalink

The post NDSS 2025 – Machine Learning-Based loT Device Identification Models For Security Applications appeared first on Security Boulevard.

In today’s classrooms, educators face a dual challenge: measuring learning effectively and responding to the individual needs of every student. With shifting standards, rising expectations, and increasing pressure on teachers, the traditional tools often fall short. Schools need platforms that don’t just collect data — but turn it into meaningful action.

FocalPoint Education was built exactly for this moment.

FocalPoint is an integrated EdTech ecosystem designed to help districts track learning outcomes, personalize instruction, and empower students through every stage of their academic journey. From assessments to daily learning, each product works together to give educators visibility, clarity, and control.

Let’s explore how FocalPoint is reimagining modern K–12 learning.

A Holistic EdTech Ecosystem — Not Just Another Tool

Most platforms do one thing. FocalPoint does what actually matters:
it connects assessments, analytics, and personalized learning into one seamless flow.

1. AssessCloud — Assessment Without the Overload

AssessCloud simplifies district-wide assessments — whether formative, benchmark, or summative — by bringing them into one unified space.
Educators can build tests, assign them to classes, auto-grade responses, and access real-time performance insights.

Why it matters:
Teachers save hours every week, and admin teams get instant visibility into what’s working and what’s not.

2. Lens — Data That Makes Sense

Data is only useful if it’s actionable. Lens turns complex performance data into practical insights that help schools identify strengths, weaknesses, and learning gaps.

With powerful dashboards, proficiency visualizations, and student-level analytics, Lens supports MTSS, RTI, and personalized intervention planning.

Why it matters:
Schools can spot hidden gaps early — and respond before they grow.

3. LearningTree — Adaptive Learning for Every Student

Every student learns differently, and LearningTree embraces that. It delivers personalized learning paths based on performance, mastery level, and classroom progress.

Students get lessons tailored to their pace.
Teachers get progress insights they can trust.
Administrators get visibility into school-wide mastery trends.

Why it matters:
Personalized learning becomes practical — not overwhelming.

4. Backpacker — A Digital Learning Hub for Students

Backpacker equips students with a modern space to practice, revise, and explore content aligned to their curriculum. It strengthens classroom learning with interactive tasks and topic-wise exercises.

Why it matters:
Students stay engaged, confident, and ready for assessments.

Supporting MTSS and Data-Driven Instruction

FocalPoint isn’t just a set of tools. It’s a framework that supports MTSS by helping educators:

• Identify students at risk
• Monitor progress over time
• Deliver timely interventions
• Measure the impact of instructional strategies

From Tier-I classrooms to Tier-III interventions, FocalPoint gives schools the evidence and structure they need to support every learner.

Built for District Leaders. Loved by Teachers. Trusted by Students.

What sets FocalPoint apart isn’t just its technology — it’s the impact.

• District leaders gain clarity over performance across schools.
• Teachers finally get tools that reduce workload instead of adding to it.
• Students receive a learning experience that adapts to them — not the other way around.

Whether a district is struggling with fragmented data, inconsistent assessments, or limited visibility into student mastery, FocalPoint bridges those gaps.

FocalPoint Education: Transforming How Schools Assess, Teach, and Personalize Learning was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story.

Session4A: IoT Security

Authors, Creators & Presenters: Haoqiang Wang, Yiwei Fang (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyber Security, University of Chinese Academy of Sciences; Indiana University Bloomington), Yichen Liu (Indiana University Bloomington), Ze Jin (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyber Security, University of Chinese Academy of Sciences; Indiana University Bloomington), Emma Delph (Indiana University Bloomington), Xiaojiang Du (Stevens Institute of Technology), Qixu Liu (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyber Security, University of Chinese Academy of Sciences), Luyi Xing (Indiana University Bloomington)

PAPER

Hidden and Lost Control: on Security Design Risks in IoT User-Facing Matter Controller

Matter is emerging as an IoT industry--unifying standard, aiming to enhance the interoperability among diverse smart home products, enabling them to work securely and seamlessly together. With many popular IoT vendors increasingly supporting Matter in consumer IoT products, we perform a systematic study to investigate how and whether vendors can integrate Matter securely into IoT systems and how well Matter as a standard supports vendors' secure integration. By analyzing Matter development model in the wild, we reveal a new kind of design flaw in user-facing Matter control capabilities and interfaces, called UMCCI flaws, which are exploitable vulnerabilities in the design space and seriously jeopardize necessary control and surveillance capabilities of Matter-enabled devices for IoT users. Therefore we built an automatic tool called UMCCI Checker, enhanced by the large-language model in UI analysis, which enables automatically detecting UMCCI flaws without relying on real IoT devices. Our tool assisted us with studying and performing proof-of-concept attacks on 11 real Matter devices of 8 popular vendors to confirm that the UMCCI flaws are practical and common. We reported UMCCI flaws to related vendors, which have been acknowledged by CSA, Apple, Tuya, Aqara, etc. To help CSA and vendors better understand and avoid security flaws in developing and integrating IoT standards like Matter, we identify two categories of root causes and propose immediate fix recommendations.

ABOUT NDSS
The Network and Distributed System Security Symposium (NDSS) fosters information exchange among researchers and practitioners of network and distributed system security. The target audience includes those interested in practical aspects of network and distributed system security, with a focus on actual system design and implementation. A major goal is to encourage and enable the Internet community to apply, deploy, and advance the state of available security technologies.

Our thanks to the Network and Distributed System Security (NDSS) Symposium for publishing their Creators, Authors and Presenter’s superb NDSS Symposium 2025 Conference content on the Organizations' YouTube Channel.

Permalink

The post NDSS 2025 – Hidden And Lost Control: On Security Design Risks In loT User-Facing Matter Controller appeared first on Security Boulevard.

Session4A: IoT Security

Authors, Creators & Presenters: Hangtian Liu (Information Engineering University), Lei Zheng (Institute for Network Sciences and Cyberspace (INSC), Tsinghua University), Shuitao Gan (Laboratory for Advanced Computing and Intelligence Engineering), Chao Zhang (Institute for Network Sciences and Cyberspace (INSC), Tsinghua University), Zicong Gao (Information Engineering University), Hongqi Zhang (Henan Key Laboratory of Information Security), Yishun Zeng (Institute for Network Sciences and Cyberspace (INSC), Tsinghua University), Zhiyuan Jiang (National University of Defense Technology), Jiahai Yang (Institute for Network Sciences and Cyberspace (INSC), Tsinghua University)

PAPER

EAGLEYE: Exposing Hidden Web Interfaces in IoT Devices via Routing Analysis [https://www.ndss-symposium.org/wp-con...](https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbEEzMmJxSkNwUUhDUkMteHZraTQ1blZ5Sk0zUXxBQ3Jtc0tuZldzQXZxQXJaOGt0VDU2RGNPdGVSbnMzcWxiTVZ1UmJsTzcyaUlCTFdvbmhoWnZRdWQ0UlJiUEs4ekR1UXNCNF9KQmp4UGxKOG5kMHdBdHBiaWh6ckxFaGphY0JVRDZDQ21jUWcyREx2Qy1XVTJqWQ&q=https%3A%2F%2Fwww.ndss-symposium.org%2Fwp-content%2Fuploads%2F2025-399-paper.pdf&v=qXDD2iiIeCg) Hidden web interfaces, i.e., undisclosed access channels in IoT devices, introduce great security risks and have resulted in severe attacks in recent years. However, the definition of such threats is vague, and few solutions are able to discover them. Due to their hidden nature, traditional bug detection solutions (e.g., taint analysis, fuzzing) are hard to detect them. In this paper, we present a novel solution EAGLEYE to automatically expose hidden web interfaces in IoT devices. By analyzing input requests to public interfaces, we first identify routing tokens within the requests, i.e., those values (e.g., actions or file names) that are referenced and used as index by the firmware code (routing mechanism) to find associated handler functions. Then, we utilize modern large language models to analyze the contexts of such routing tokens and deduce their common pattern, and then infer other candidate values (e.g., other actions or file names) of these tokens. Lastly, we perform a hidden-interface directed black-box fuzzing, which mutates the routing tokens in input requests with these candidate values as the high-quality dictionary. We have implemented a prototype of EAGLEYE and evaluated it on 13 different commercial IoT devices. EAGLEYE successfully found 79 hidden interfaces, 25X more than the state-of-the-art (SOTA) solution IoTScope. Among them, we further discovered 29 unknown vulnerabilities including backdoor, XSS (cross-site scripting), command injection, and information leakage, and have received 7 CVEs.

ABOUT NDSS
The Network and Distributed System Security Symposium (NDSS) fosters information exchange among researchers and practitioners of network and distributed system security. The target audience includes those interested in practical aspects of network and distributed system security, with a focus on actual system design and implementation. A major goal is to encourage and enable the Internet community to apply, deploy, and advance the state of available security technologies.

Our thanks to the Network and Distributed System Security (NDSS) Symposium for publishing their Creators, Authors and Presenter’s superb NDSS Symposium 2025 Conference content on the Organizations' YouTube Channel.

Permalink

The post NDSS 2025 – EAGLEYE: Exposing Hidden Web Interfaces In loT Devices Via Routing Analysis appeared first on Security Boulevard.

Sam Ransbotham teaches a class in machine learning as a professor of business analytics at Boston College, and what he’s witnessing in the classroom both excites and terrifies him.

Some students are using AI tools to create and accomplish amazing things, learning and getting more out of the technology than he could have imagined. But in other situations, he sees a concerning trend: students “phoning things into the machine.”

The result is a new kind of digital divide — but it’s not the one you’d expect.

Boston College provides premier tools to students at no cost, to ensure that socioeconomics aren’t the differentiator in the classroom. But Ransbotham, who hosts the “Me, Myself and AI” podcast from MIT Sloan Management Review, worries about “a divide in technology interest.”

“The deeper that someone is able to understand tools and technology, the more that they’re able to get out of those tools,” he explained. “A cursory usage of a tool will get a cursory result, and a deeper use will get a deeper result.”

The problem? “It’s a race to mediocre. If mediocre is what you’re shooting for, then it’s really quick to get to mediocre.”

He explained, “Boston College’s motto is ‘Ever to Excel.’ It’s not ‘Ever to Mediocre.’ And the ability of students to get to excellence can be hampered by their ease of getting to mediocre.”

That’s one of the topics on this special episode of the GeekWire Podcast, a collaboration with Me, Myself and AI. Sam and I compare notes from our podcasts and share our own observations on emerging trends and long-term implications of AI. This is a two-part series across our podcasts — you can find the rest of our conversation on the Me, Myself and AI feed.

Continue reading for takeaways from this episode.

AI has a measurement problem: Sam, who researched Wikipedia extensively more than a decade ago, sees parallels to the present day. Before Wikipedia, Encyclopedia Britannica was a company with employees that produced books, paid a printer, and created measurable economic value. Then Wikipedia came along, and Encyclopedia Britannica didn’t last.

Its economic value was lost. But as he puts it: “Would any rational person say that the world is a worse place because we now have Wikipedia versus Encyclopedia Britannica?”

In other words, traditional economic metrics don’t fully capture the net gain in value that Wikipedia created for society. He sees the same measurement problem with AI. 

“The data gives better insights about what you’re doing, about the documents you have, and you can make a slightly better decision,” he said. “How do you measure that?”

Content summarization vs. generation: Sam’s “gotta have it” AI feature isn’t about creating content — it’s about distilling information to fit more into his 24 hours.

“We talk a lot about generation and the generational capabilities, what these things can create,” he said. “I find myself using it far more for what it can summarize, what it can distill.”

Finding value in AI, even when it’s wrong: Despite his concerns about students using AI to achieve mediocrity, Sam remains optimistic about what people can accomplish with AI tools.

“Often I find that the tool is completely wrong and ridiculous and it says just absolute garbage,” he said. “But that garbage sparks me to think about something — the way that it’s wrong pushes me to think: why is that wrong? … and how can I push on that?”

Searching for the signal in the noise: Sam described the goal of the Me, Myself and AI podcast as cutting through the polarizing narratives about artificial intelligence.

“There’s a lot of hype about artificial intelligence,” he said. “There’s a lot of naysaying about artificial intelligence. And somewhere between those, there is some signal, and some truth.”

Listen to the full episode above, subscribe to GeekWire in Apple, Spotify, or wherever you listen, and find the rest of our conversation on the Me, Myself and AI podcast feed.

Session4A: IoT Security

Authors, Creators & Presenters: Christopher Ellis (The Ohio State University), Yue Zhang (Drexel University), Mohit Kumar Jangid (The Ohio State University), Shixuan Zhao (The Ohio State University), Zhiqiang Lin (The Ohio State University)

PAPER

Deanonymizing Device Identities via Side-channel Attacks in Exclusive-use IoTs & Mitigation Wireless technologies like Bluetooth Low Energy (BLE) and Wi-Fi are essential to the Internet of Things (IoT), facilitating seamless device communication without physical connections. However, this convenience comes at a cost--exposed data exchanges that are susceptible to observation by attackers, leading to serious security and privacy threats such as device tracking. Although protocol designers have traditionally relied on strategies like address and identity randomization as a countermeasure, our research reveals that these attacks remain a significant threat due to a historically overlooked, fundamental flaw in exclusive-use wireless communication. We define exclusive-use as a scenario where devices are designed to provide functionality solely to an associated or paired device. The unique communication patterns inherent in these relationships create an observable boolean side-channel that attackers can exploit to discover whether two devices "trust" each other. This information leak allows for the deanonymization of devices, enabling tracking even in the presence of modern countermeasures. We introduce our tracking attacks as IDBleed and demonstrate that BLE and Wi-Fi protocols that support confidentiality, integrity, and authentication remain vulnerable to deanonymization due to this fundamental flaw in exclusive-use communication patterns. Finally, we propose and quantitatively evaluate a generalized, privacy-preserving mitigation we call Anonymization Layer to find a negligible 2% approximate overhead in performance and power consumption on tested smartphones and PCs.

ABOUT NDSS
The Network and Distributed System Security Symposium (NDSS) fosters information exchange among researchers and practitioners of network and distributed system security. The target audience includes those interested in practical aspects of network and distributed system security, with a focus on actual system design and implementation. A major goal is to encourage and enable the Internet community to apply, deploy, and advance the state of available security technologies.

Our thanks to the Network and Distributed System Security (NDSS) Symposium for publishing their Creators, Authors and Presenter’s superb NDSS Symposium 2025 Conference content on the Organizations' YouTube Channel.

Permalink

The post NDSS 2025 – Deanonymizing Device Identities Via Side-Channel Attacks In Exclusive-Use IoTs appeared first on Security Boulevard.

The Office of Personnel Management has launched a new training series, designed to educate senior executives in the federal workforce, while incorporating common themes from the Trump administration on “accountability,” performance management and adherence to the president’s priorities.

Two new training programs that OPM announced last week are targeted toward both career and political members of the Senior Executive Service, as well as GS-14 and GS-15 federal employees. The trainings largely reflect the Trump administration’s reshaping of the federal workforce this year, according to OPM Director Scott Kupor.

“We’re trying to move towards a performance-based culture in government. It’s only fair if we’re going to do that, that we give people the tools and the training necessary, so that they understand very clearly what they’re held accountable to,” Kupor said Friday in an interview with Federal News Network. “Now we have a mechanism ultimately to, as part of their performance review, make sure that [federal executives] are adhering to those principles.”

Through the new programs, OPM is aiming to inform senior leaders in more depth how the Trump administration has changed various federal workforce policies, and how senior leaders can best embed those changes at agencies.

As an example, Kupor pointed to the administration’s overhauls of the government’s performance management system. In February, OPM updated performance standards for the SES, to set much stricter limits on how many SES members can be rated as high performers, and make adherence to the president’s policies the “most critical element” of their performance reviews.

“For things that are within the bailiwick of what we expect managers to do, that are now represented in the form of executive orders, we want to make sure people really do understand both the derivation of those, as well as how we think about the appropriate implementation of those policies,” Kupor said.

In a memo last week, OPM called on agencies to encourage their senior leaders to sign up for the optional training programs, which are available governmentwide. Agencies have until Dec. 19 to inform executives that the trainings are open for registration on OPM’s website.

Details of OPM’s development programs

OPM’s two new programs for training federal executives differ in both content and cost. One of the new trainings, called the “Senior Executive Development Program,” uses a combination of video modules and “podcast-style discussions” among federal experts. It will train executives on topics like “constitutional governance,” budget, policy and strategic human capital management, according to OPM’s memo.

The SEDP is a fully online course that executives can complete at their own pace, for a tuition cost of $1,500.

OPM’s other new training program, called “Leadership for an Efficient and Accountable Government,” includes a combination of in-person and online trainings, costing $8,500 per registrant for the 80-hour course. OPM said the LEAG program is focused on “efficiency” and “accountability,” and includes modules centered on “President Trump’s executive orders and other executive branch priorities.”

“LEAG participants will gain essential skills to bridge policy and implementation, drive efficiency, uphold accountability, and expand their impact as senior leaders serving the American people,” OPM wrote in its memo.

Although both programs are optional, OPM still told agencies to “set the expectation” that all career SES members should at least complete training modules on “returning to founding principles” and “implementing administration priorities” within the next year.

Marcus Hill, president of the Senior Executives Association, said there is a continuous need for training among SES members, to “strengthen their ability to manage people, programs and resources responsibly.”

“Above all, these programs should reinforce what every federal leader swears to uphold: the obligation to ‘support and defend the Constitution of the United States’ and to ‘faithfully discharge the duties of the office’ to which they were appointed,” Hill said in a statement. “Understanding the legal and constitutional framework in which we operate is fundamental to maintaining public trust and carrying out our responsibilities with integrity.”

Next steps for federal workforce training

In part, OPM’s two new programs appear to replace prior opportunities from the Federal Executive Institute. The FEI was a long-time training program OPM ran for federal employees governmentwide — until President Donald Trump directed the dismantling of FEI in February.

When initially announcing plans to launch new trainings in August, OPM said the upcoming SES programs would be “radically different” from what existed previously through FEI.

Kupor told Federal News Network that FEI “was lacking in a couple areas,” and argued that the cost of the program surpassed its overall value to senior executives.

“It literally had a physical campus to it, so it required people to be away from office for several days in order to do it,” Kupor said. “Unfortunately, it was prohibitive both in terms of dollars, as well as just people’s time.”

Earlier this year, OPM eliminated its Center for Leadership Development through a reduction in force (RIF). The office was previously responsible for running various training and development programs for the federal workforce, but in the absence of CLD, the new training programs are being run through OPM’s Human Resources Solutions office, in partnership with the director’s office.

Some workforce experts, however, have previously questioned OPM’s internal capacity to manage new training programs. Since January, the agency has reduced its workforce by about one-third, as part of the Trump administration’s efforts to reduce headcount across government.

Jason Briefel, a federal workforce policy expert, said he generally considers the idea of a governmentwide SES training program from OPM to be a positive development. But he expressed reservations about what the trainings would actually entail — and what types of results the programs may deliver.

“With agencies shrinking their workforces, and with more demands being placed on executive leaders, how will they balance actually doing the training, and then applying what they’ve learned, while still trying to do their job?” Briefel said.

Briefel also questioned whether agencies would have the budget to afford the new OPM trainings, as most are still operating under a continuing resolution and uncertain of their long-term funding options.

Moving forward, Kupor said OPM plans to update the training modules over time, as well as expand the program to add more development opportunities for other sectors of the federal workforce.

“We will need help from external parties to do that — OPM doesn’t have this view that we need to own and develop everything,” Kupor said. “There are plenty of organizations external to OPM who, to the extent they have ways in which they can help us further develop the curriculum, we’re very open to that.”

The post OPM touts new training programs, aligned with Trump administration’s federal workforce reshaping first appeared on Federal News Network.

SESSION
Session 3D: AI Safety

-----------

-----------

Authors, Creators & Presenters: Yan Pang (University of Virginia), Aiping Xiong (Penn State University), Yang Zhang (CISPA Helmholtz Center for Information Security), Tianhao Wang (University of Virginia)

-----------

PAPER
Towards Understanding Unsafe Video Generation
Video generation models (VGMs) have demonstrated the capability to synthesize high-quality output. It is important to understand their potential to produce unsafe content, such as violent or terrifying videos. In this work, we provide a comprehensive understanding of unsafe video generation.

First, to confirm the possibility that these models could indeed generate unsafe videos, we choose unsafe content generation prompts collected from 4chan and Lexica, and three open-source SOTA VGMs to generate unsafe videos. After filtering out duplicates and poorly generated content, we created an initial set of 2112 unsafe videos from an original pool of 5607 videos. Through clustering and thematic coding analysis of these generated videos, we identify 5 unsafe video categories: Distorted/Weird, Terrifying, Pornographic, Violent/Bloody, and Political. With IRB approval, we then recruit online participants to help label the generated videos. Based on the annotations submitted by 403 participants, we identified 937 unsafe videos from the initial video set. With the labeled information and the corresponding prompts, we created the first dataset of unsafe videos generated by VGMs. We then study possible defense mechanisms to prevent the generation of unsafe videos. Existing defense methods in image generation focus on filtering either input prompt or output results. We propose a new approach called sysname, which works within the model's internal sampling process. sysname can achieve 0.90 defense accuracy while reducing time and computing resources by 10 times when sampling a large number of unsafe prompts. Our experiment includes three open-source SOTA video diffusion models, each achieving accuracy rates of 0.99, 0.92, and 0.91, respectively. Additionally, our method was tested with adversarial prompts and on image-to-video diffusion models, and achieved nearly 1.0 accuracy on both settings. Our method also shows its interoperability by improving the performance of other defenses when combined with them.

-----------

ABOUT NDSS
The Network and Distributed System Security Symposium (NDSS) fosters information exchange among researchers and practitioners of network and distributed system security. The target audience includes those interested in practical aspects of network and distributed system security, with a focus on actual system design and implementation. A major goal is to encourage and enable the Internet community to apply, deploy, and advance the state of available security technologies.

-----------

Our thanks to the Network and Distributed System Security (NDSS) Symposium for publishing their Creators, Authors and Presenter’s superb NDSS Symposium 2025 Conference content on the Organizations' YouTube Channel.

Permalink

The post NDSS 2025 – Towards Understanding Unsafe Video Generation appeared first on Security Boulevard.

The BBC wanted to show everyone how a computer might be used in schools. A program aired in 1979 asks, “Will Computers Revolutionise Education?” There’s vintage hardware and an appearance of PILOT, made for computer instructions.

Using PILOT looks suspiciously like working with a modern chatbot without as much AI noise. The French teacher in the video likes that schoolboys were practicing their French verb conjugation on the computer instead of playing football.

If you want a better look at hardware, around the five-minute mark, you see schoolkids making printed circuit boards, and some truly vintage oscilloscope close-ups. There are plenty of tiny monitors and large, noisy printing terminals.

You have to wonder where the eight-year-olds who learned about computers in the video are today, and what kind of computer they have. They learned binary and the Towers of Hanoi. Their teacher said the kids now knew more about computers than their parents did.

As a future prediction, [James Bellini] did pretty well. Like many forecasters, he almost didn’t go far enough, as we look back almost 50 years. Sure, Prestel didn’t work out as well as they thought, dying in 1994. But he shouldn’t feel bad. Predicting the future is tough. Unless, of course,  you are [Arthur C. Clarke].

SESSION
Session 3D: AI Safety

-----------

-----------

Authors, Creators & Presenters: Haotian Zhu (Nanjing University of Science and Technology), Shuchao Pang (Nanjing University of Science and Technology), Zhigang Lu (Western Sydney University), Yongbin Zhou (Nanjing University of Science and Technology), Minhui Xue (CSIRO's Data61)

-----------

PAPER
GAP-Diff: Protecting JPEG-Compressed Images From Diffusion-Based Facial Customization
Text-to-image diffusion model's fine-tuning technology allows people to easily generate a large number of customized photos using limited identity images. Although this technology is easy to use, its misuse could lead to violations of personal portraits and privacy, with false information and harmful content potentially causing further harm to individuals. Several methods have been proposed to protect faces from customization via adding protective noise to user images by disrupting the fine-tuned models.
Unfortunately, simple pre-processing techniques like JPEG compression, a normal pre-processing operation performed by modern social networks, can easily erase the protective effects of existing methods. To counter JPEG compression and other potential pre-processing, we propose GAP-Diff, a framework of Generating data with Adversarial Perturbations for text-to-image Diffusion models using unsupervised learning-based optimization, including three functional modules. Specifically, our framework learns robust representations against JPEG compression by backpropagating gradient information through a pre-processing simulation module while learning adversarial characteristics for disrupting fine-tuned text-to-image diffusion models. Furthermore, we achieve an adversarial mapping from clean images to protected images by designing adversarial losses against these fine-tuning methods and JPEG compression, with stronger protective noises within milliseconds. Facial benchmark experiments, compared to state-of-the-art protective methods, demonstrate that GAP-Diff significantly enhances the resistance of protective noise to JPEG compression, thereby better safeguarding user privacy and copyrights in the digital world.

ABOUT NDSS
The Network and Distributed System Security Symposium (NDSS) fosters information exchange among researchers and practitioners of network and distributed system security. The target audience includes those interested in practical aspects of network and distributed system security, with a focus on actual system design and implementation. A major goal is to encourage and enable the Internet community to apply, deploy, and advance the state of available security technologies.

Our thanks to the Network and Distributed System Security (NDSS) Symposium for publishing their Creators, Authors and Presenter’s superb NDSS Symposium 2025 Conference content on the Organizations' YouTube Channel.

Permalink

The post NDSS 2025 – GAP-Diff: Protecting JPEG-Compressed Images From Diffusion-Based Facial Customization appeared first on Security Boulevard.

SESSION
Session 3D: AI Safety

-----------

-----------

Authors, Creators & Presenters: Shuo Shao (Zhejiang University), Yiming Li (Zhejiang University), Hongwei Yao (Zhejiang University), Yiling He (Zhejiang University), Zhan Qin (Zhejiang University), Kui Ren (Zhejiang University)

-----------

PAPER
Explanation as a Watermark: Towards Harmless and Multi-bit Model Ownership Verification via Watermarking Feature Attribution
Ownership verification is currently the most critical and widely adopted post-hoc method to safeguard model copyright. In general, model owners exploit it to identify whether a given suspicious third-party model is stolen from them by examining whether it has particular properties 'inherited' from their released models. Currently, backdoor-based model watermarks are the primary and cutting-edge methods to implant such properties in the released models. However, backdoor-based methods have two fatal drawbacks, including harmfulness and ambiguity. The former indicates that they introduce maliciously controllable misclassification behaviors ( backdoor) to the watermarked released models. The latter denotes that malicious users can easily pass the verification by finding other misclassified samples, leading to ownership ambiguity.

In this paper, we argue that both limitations stem from the 'zero-bit' nature of existing watermarking schemes, where they exploit the status (misclassified) of predictions for verification. Motivated by this understanding, we design a new watermarking paradigm "Explanation as a Watermark (EaaW)", that implants verification behaviors into the explanation of feature attribution instead of model predictions. Specifically, EaaW embeds a 'multi-bit' watermark into the feature attribution explanation of specific trigger samples without changing the original prediction. We correspondingly design the watermark embedding and extraction algorithms inspired by explainable artificial intelligence. In particular, our approach can be used for different tasks (image classification and text generation). Extensive experiments verify the effectiveness and harmlessness of our EaaW and its resistance to potential attacks.

-----------

ABOUT NDSS
The Network and Distributed System Security Symposium (NDSS) fosters information exchange among researchers and practitioners of network and distributed system security. The target audience includes those interested in practical aspects of network and distributed system security, with a focus on actual system design and implementation. A major goal is to encourage and enable the Internet community to apply, deploy, and advance the state of available security technologies.

Our thanks to the Network and Distributed System Security (NDSS) Symposium for publishing their Creators, Authors and Presenter’s superb NDSS Symposium 2025 Conference content on the Organizations' YouTube Channel.

Permalink

The post NDSS 2025 – Explanation As A Watermark appeared first on Security Boulevard.

Last week’s conclusion of the record-breaking government shutdown was great news for federal employees in general. But for a few thousand specific feds, it was even better news. They’d been told they were about to lose their jobs completely, and as of Friday, almost all of them have now had those notices formally rescinded.

Filings the Justice Department submitted to a federal court in San Francisco on Friday indicate that each of the more than 3,000 federal workers who had received reduction in force (RIF) notices after the shutdown began have now been formally notified that those RIFs have been cancelled.

That action came as a result of several provisions in the continuing resolution Congress passed last week to reopen the government. The legislation provided that not only any RIF notice an agency issued on Oct. 1 or later “shall have no force or effect,” but it also barred federal agencies from using any funding to conduct any further RIFs for as long as the current CR is in effect.

Those same RIFs were the subject of a union lawsuit that had already resulted in a preliminary injunction putting the layoffs on hold. But the Trump administration argues the continuing resolution means there’s no longer a need to litigate over whether the RIFs were legal in the first place.

“In light of these developments, defendants believe this case is moot,” attorneys wrote in a filing Friday.

In all, agency-by-agency filings show the administration attempted to fire a total of 3,605 employees during the shutdown — with RIF notices ranging from more than 1,300 at the Internal Revenue Service to 54 at the Cybersecurity and Infrastructure Security Agency.

(Story continues below table)

Agencies updated their filings on Friday to indicate that they had complied with the directive Congress included in the CR to notify each employee that their RIF notices have been withdrawn.

However, there is some doubt as to the fate of 299 positions in the Department of Education’s civil rights division. Although the department notified those workers on Oct. 14 — a time period during which Congress undid all other RIF notices — the government argues that those specific notices were first issued in March, and consequently weren’t covered by the continuing resolution.

“Although the March 2025 RIF group of OCR employees is an entirely separate group from the 137 OCR employees to whom October 10 RIF notices were issued, and finalizing the March 2025 RIF does not involve issuing or implementing a RIF during and because of the shutdown, ED has paused separating the March RIF OCR employees pursuant to this court’s preliminary injunction pending clarification from the court that the current preliminary injunction does not encompass ED’s March 2025 RIF,” Jacqueline Clay, the department’s chief human capital officer wrote in a declaration.

The post More than 3,600 feds get notice their shutdown RIFs are rescinded first appeared on Federal News Network.