• EFF Launches Searchable Database of Police Use of Surveillance Technologies

    The Electronic Frontier Foundation (EFF), in partnership with the Reynolds School of Journalism at the University of Nevada, Reno, the other day launched what the EFF describes as “the largest-ever collection of searchable data on police use of surveillance technologies,” created as a tool for the public to learn about facial recognition, drones, license plate readers, and other devices law enforcement agencies are acquiring to spy on our communities.

  • Large-Scale Facial Recognition Is Incompatible with a Free Society

    By Seth Lazar, Claire Benn, and Mario Günther

    In the U.S., tireless opposition to state use of facial recognition algorithms has recently won some victories. Outside the U.S., however, the tide is heading in the other direction. To decide whether to expand or limit the use of facial recognition technology, nations will need to answer fundamental questions about the kind of people, and the kind of society, they want to be. Face surveillance is based on morally compromised research, violates our rights, is harmful, and exacerbates structural injustice, both when it works and when it fails. Its adoption harms individuals, and makes our society as a whole more unjust, and less free. A moratorium on its use is the least we should demand.

  • Police with Lots of Military Gear Kill Civilians More Often than Less-Militarized Officers

    By Casey Delehanty

    Police departments that get more equipment from the military kill more civilians than departments that get less military gear. That’s the finding from research on a federal program — called the “1033 Program.” — that has operated since 1997. The seeds of this program came in 1988 as the Cold War was ending. The military was shrinking, while police were feeling overwhelmed fighting the drug war. Over the past 23 years police all across America received billions of dollars in military-grade hardware often designed specifically to fight in the battlefields of Afghanistan and Iraq. And yet, all that equipment has done more harm than good.

  • How Much Control Would People Be Willing to Grant to a Personal Privacy Assistant?

    CyLab’s Jessica Colnago believes that in the future, the simple act of walking down the street is going to be a little weird. “You know how every time you enter a website, and it says: ‘We use cookies. Do you consent?’ Imagine that same thing walking down the street, but for a light pole, or a surveillance camera, or an energy sensor on a house,” Colnago says.

  • Bans on Facial Recognition Are Naïve — Hold Law Enforcement Accountable for Its Abuse

    The use of facial recognition technology has become a new target in the fight against racism and brutality in law enforcement. The current controversy over facial recognition purports to be about bias — inaccurate results related to race or gender. Osonde A. Osoba and Douglas Yeung write that “That could be fixed in the near future, but it wouldn’t repair the underlying dilemma: The imbalance of power between citizens and law enforcement. On this, facial recognition ups the ante. These tools can strip individuals of their privacy and enable mass surveillance.

  • Yes, Big Brother IS Watching: Russian Schools Installing Surveillance Systems Called “Orwell”

    By Matthew Luxmoore

    You might think governments seeking digital oversight of their citizens would avoid invoking the author who coined the phrase “Big Brother is watching you” and implanted the nightmare of total state surveillance in the imaginations of millions of readers. Think again, because Russian officials appear to disagree. In the first phase of the project, the “total surveillance” system will be installed in 43,000 schools across Russia.

  • “Black Box” Study: Testing the Accuracy of Computer, Mobile Phone Forensics

    Digital forensics experts often extract data from computers and mobile phones that may contain evidence of a crime. Now, researchers at the National Institute of Standards and Technology (NIST) will conduct the first large-scale study to measure how well those experts do their job. But rather than testing the proficiency of individual experts, the study aims to measure the performance of the digital forensics community overall.

  • Forensics Laser Technology Can Detect Crime Scene Smokers

    Raman spectroscopy is a technique that shines a monochromatic light (i.e. from a laser) on a sample and measures the intensity of scattered light. No two samples will produce the same Raman spectrum, offering a unique measurement that is similar to a fingerprint. Results are instantaneous and nondestructive, preserving the sample for future testing. Researchers developed a laser-light technology which allows investigators to determine if a smoker was at the crime scene based on biological evidence.

  • European Police Services Turn to Tasers as Weapon of Choice

    On Friday, the French government announced that French police would no longer be allowed to use chokeholds on suspects. More police officers would instead be equipped with stun guns. About 15,000 French police officers, out of a force of 240,000 officers nationwide, are already equipped with stun guns. The police in Italy, the Netherlands, England, Wales and other European countries have been increasing their use of tasers to subdue suspects instead of other methods.

  • High-Tech Surveillance Amplifies Police Bias and Overreach

    By Andrew Guthrie Ferguson

    Local, state and federal law enforcement organizations use an array of surveillance technologies to identify and track protesters, from facial recognition to military-grade drones. Police use of these national security-style surveillance techniques – justified as cost-effective techniques that avoid human bias and error – has grown hand-in-hand with the increased militarization of law enforcement. Extensive research, including my own, has shown that these expansive and powerful surveillance capabilities have exacerbated rather than reduced bias, overreach and abuse in policing, and they pose a growing threat to civil liberties.

  • Calls for New Federal Authority to Regulate Facial Recognition Tech

    A group of artificial intelligence experts — citing profiling, breach of privacy and surveillance as potential societal risks — recently proposed a new model for managing facial recognition technologies at the federal level. The experts propose an FDA-inspired model that categorizes these technologies by degrees of risk and would institute corresponding controls.

  • Slime Scene: Unusual Forensic Investigation Technique Put to the Test

    Could household slime become a tool to help solve crimes? This is the question researchers sought to answer in a recent study that tested a popular children’s “slime” recipe as a technique to enhance the appearance of hard-to-see fingerprints in forensic investigations.

  • Germany: Revised Domestic Surveillance Bill Submitted to Bundestag

    A draft law to reform Germany’s BfV domestic intelligence agency is to be re-submitted to parliament after long debate. It will allow German domestic intelligence and law enforcement to conduct electronic surveillance of telephone calls and SMS text services, including encrypted “chats” via services such as WhatsApp and Telegram, but will  not allow the use of cyber “Trojan” trawling tools.

  • COVID Is Ushering in a Surveillance State That May Never Be Dismantled

    Is the “new normal” to be a surveillance society, with tracing apps and facial recognition health passports? Philip Johnston writes in The Telegraph that the British government insists not; but if we are hit by a second wave of COVID-19, the temptation to extend the monitoring will be hard to resist.

  • Students Take Witness Stand in Virtual Courtroom

    USC students took the stand as part of the capstone project in their advanced digital forensics class at the USC Viterbi School of Engineering. In years past, students in the class traveled to a real courtroom, but this year the COVID-19 pandemic pushed them to a digital venue: a videoconference on Zoom.